Global

Dear Client, In light of recent market turbulence, we are publishing our weekly report earlier than usual. Caroline Miller, Garry Evans, and I will also be hosting a webcast Wednesday morning at 10am EST to discuss the investment outlook. Best regards, Peter Berezin, Chief Global Strategist Highlights Monday's stock market rout was largely driven by technical factors. Strong economic growth and positive earnings surprises should keep the equity bull market intact. Nevertheless, investors need to adjust to the fact that volatility is likely to pick up, just as it did in the last few years of the 1990s bull market. The market's expectations of where the funds rate will be over the next two years have almost converged with the Fed dots. In the near term, this will limit the ability of the 10-year Treasury yield to rise much above 3%. Looking further out, inflation is likely to move above the Fed's target early next year, setting the stage for a recession starting in late 2019. A modest overweight on global risk assets is warranted for now, but investors should consider reducing risk exposure later this year. Feature VIX Kicks Last week's Global Investment Strategy report, entitled "Take Out Some Insurance," argued that equities had become dangerously overbought and were highly vulnerable to a correction.1 We noted that the VIX had likely bottomed for the cycle and that going long volatility had now become an attractive hedge against stock market declines. As many of my colleagues have noted, betting on continued low volatility had become an increasingly crowded trade in recent years. Back in January, we observed that net short volatility positions had reached record-high levels (Chart 1). We warned that "traders have been able to reap huge gains over the past few years by betting volatility will decline. The problem is that if volatility starts to rise, those same traders could start to unload their positions, leading to even higher volatility."2 Precisely such a vicious cycle erupted on Monday, causing the S&P 500 to suffer its worst daily percentage loss since August 18, 2011. The question is where do we go from here? So far, the sell-off in stocks looks largely technical in nature. Chart 2 shows that the VIX soared by roughly four times more on Monday than one would have expected based solely on the decline in equity prices. This suggests that the spike in volatility caused the stock market plunge, rather than the other way around. The relatively muted reaction of other "risk gauges" such as junk bonds, EM stocks, and gold prices over the past few days is consistent with this thesis. Chart 1Volatility Is Back Volatility Is Back Volatility Is Back Chart 2Monday's VIX Spike Was Abnormally Large The Return Of Vol The Return Of Vol Cyclical Outlook Still Solid It is impossible to know if today's rebound will persist or if the correction still has further to run. What we do know is that the cyclical underpinnings for the bull market remain intact. Leading economic data remain buoyant (Chart 3). Corporate earnings continue to come in above expectations (Chart 4). Chart 3Global Economic Backdrop Remains Buoyant Global Economic Backdrop Remains Buoyant Global Economic Backdrop Remains Buoyant Chart 4Optimism Over 2018 Earnings Growth Optimism Over 2018 Earnings Growth Optimism Over 2018 Earnings Growth None of our recession-timing indicators are flashing red (Chart 5). The Conference Board's LEI is rising at a healthy 5.5% y/y pace. Historically, a decisive break below zero in the year-over-year change in the LEI has been a reliable recession indicator. Likewise, while the U.S. 2/10-year Treasury curve has flattened, it has not inverted yet. Moreover, even once the yield curve inverts, the lags can be quite long before the recession begins. For example, in the last cycle, the yield curve inverted in early 2006, but the recession did not begin until December 2007. This does not mean that everything will be smooth sailing from here. Monday's sell-off marked an inflection point in the low-volatility world that has prevailed over the past few years. The VIX Humpty-Dumpty has been irrevocably broken. Going forward, volatility will remain elevated relative to what investors have come to expect. As the experience of the 1990s shows, stocks can still go up when volatility is trending higher (Chart 6), but this is going to make for a much more challenging investment environment. Chart 5No Signs Of An Imminent End To This Business Cycle No Signs Of An Imminent End To This Business Cycle No Signs Of An Imminent End To This Business Cycle Chart 6Volatility Can Increase As Stock Prices Rise Volatility Can Increase As Stock Prices Rise Volatility Can Increase As Stock Prices Rise The Powell Put? How the Fed and other central banks react to this new world will be critical. It is perhaps not a complete coincidence that Monday's crash occurred on the first day that Jay Powell took over the helm of the Fed. Investors are increasingly worried that the Fed will turn from friend to foe. The faster-than-expected increase in average hourly earnings in January put those fears in stark relief. Accelerating wage growth suggests supply-side constraints are beginning to bite. This, in turn, means that the runway for low inflation and easy monetary policy may not be as long as some had hoped. As BCA editors discussed in our 2018 Outlook, "Policy And The Markets: On A Collision Course," central banks are in the process of winding down the extraordinary stimulus that investors have gotten used to.3 Whether this undermines the case for holding stocks and other risk assets depends on how quickly the adjustment occurs. On the plus side, we continue to think the adjustment will be fairly gradual, at least for the time being. Core CPI inflation outside of shelter is still running at 0.7% (Chart 7). This gives the Fed plenty of wiggle room. Just like Janet Yellen, Jay Powell will seek to build a consensus among his colleagues. Granted, the composition of the FOMC is likely to shift in a somewhat more hawkish direction. However, the evolution will be slow. In the meantime, the recommendations of career Fed staff will represent an important, and often underappreciated, source of continuity. As in the past, the Fed will continue to monitor incoming economic and financial data and react accordingly. The stock market rout has led to some tightening in financial conditions, but FCIs in the U.S. and most other countries remain more expansionary than they were six months ago (Chart 8). Chart 7Core Inflation Outside Housing Is Still Low Core Inflation Outside Housing Is Still Low Core Inflation Outside Housing Is Still Low Chart 8Financial Conditions Have Tightened Recently, But Are Still Easier Than They Were Last Year Financial Conditions Have Tightened Recently, But Are Still Easier Than They Were Last Year Financial Conditions Have Tightened Recently, But Are Still Easier Than They Were Last Year Just as importantly, the implosion of volatility funds is unlikely to reverberate across the financial system in the same way as it did during the financial crisis. What made the mortgage crisis so toxic was that the losses were concentrated in the books of highly leveraged financial institutions. In the case of volatility funds, that does not appear to be the case. Investment Implications Global bond yields remain quite low by historic standards and this should continue to support stocks. Indeed, even after the recent bond sell-off, average global bond yields are still close to half of what they were in 2011 - a time when global excess capacity was much greater than it is today (Chart 9). In keeping with our structurally bearish view on bonds, which we first articulated on July 5, 2016 in a note entitled "The End of 35-Year Bond Bull Market," we expect global bond yields to grind higher.4 However, in rate-of-change terms, the swift repricing of yields over the past few months has likely run its course. Chart 10 shows that market expectations of where the funds rate will be at the end of 2018 and 2019 have almost converged with the Fed dots. This convergence helped our short December-2018 fed funds futures trade, which we closed at our stop for a gain of 70 bps last Friday. A sustained move above 3% on the 10-year Treasury yield will require a more durable increase in inflation. Ultimately, we do expect core inflation to move above 2%, forcing the Fed to lift interest rates into restrictive territory. However, this is likely to be a story for 2019 rather than 2018. Stocks tend to peak about six months before the start of recessions (Table 1). If the next recession occurs in late 2019, as we expect, the equity bull market could last a while longer. A modest overweight on global risk assets is warranted for now, but investors should consider reducing risk exposure later this year. Chart 9Yields Are Still Low By Historic Standards Yields Are Still Low By Historic Standards Yields Are Still Low By Historic Standards Chart 10Market Pricing Has Almost Caught Up To The Fed's Dots Market Pricing Has Almost Caught Up To The Fed's Dots Market Pricing Has Almost Caught Up To The Fed's Dots Table 1Too Soon To Get Out The Return Of Vol The Return Of Vol Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com 1 Please see Global Investment Strategy Weekly Report, "Take Out Some Insurance," dated February 2, 2018. 2 Please see Global Investment Strategy Weekly Report, "Will Bitcoin Be DeFANGed?" dated January 12, 2018. 3 Please see The Bank Credit Analyst, "2018 Outlook - Policy And The Markets: On A Collision Course," dated November 20, 2017. 4 Please see Global Investment Strategy Special Report, "End Of The 35-Year Bond Bull Market," dated July 5, 2016. Strategy & Market Trends* The Return Of Vol The Return Of Vol Tactical Trades The Return Of Vol The Return Of Vol Strategic Recommendations The Return Of Vol The Return Of Vol Trades Closed In 2015-2018 The Return Of Vol The Return Of Vol

Highlights Global equities are technically overbought, making them highly vulnerable to a correction. The cyclical picture for stocks still looks good, thanks to strong economic growth and rising corporate profits, but the recent spike in bond yields is becoming a headwind. Valuations are highly stretched, particularly in the U.S. This points to subpar long-term returns. On balance, we recommend staying overweight global equities. However, investors should consider buying some insurance against a market selloff. The VIX has probably bottomed for this cycle and high-yield spreads are unlikely to move much lower. This makes long volatility and short credit positions attractive hedges. Going short AUD/JPY is also an appealing hedge, given the yen's defensive characteristics and the Aussie dollar's vulnerability to slower Chinese growth. We were stopped out of our long global industrials versus utilities trade for a gain of 12%. We are also raising our stop on our short fed funds futures trade to 70 bps. Feature A Cloudy Picture As a rule of thumb, technical factors drive stocks over short-term horizons of one-to-three months, business cycle developments and financial conditions drive stocks over horizons of one-to-two years, and valuations drive stocks over ultra long-term horizons of five years and beyond. Occasionally, all three sets of signals line up in the same direction. In March 2009, the combination of bombed-out sentiment, cheap valuations, green shoots in the economy, and the expansion of the Fed's QE program all aligned to mark the beginning of a powerful bull market in stocks. Unfortunately, today the calculus is not so simple. Stocks Are Technically Overbought Technically, the stock market has gotten ahead of itself. The S&P 500 Relative Strength Index hit a record high earlier this week, while our Technical Indicator reached a post-recession high (Chart 1). The S&P has now gone 310 days without a 3% drawdown and 402 days without a 5% drawdown - both records (Chart 2). Chart 1U.S. Equities Are Technically Overbought U.S. Equities Are Technically Overbought U.S. Equities Are Technically Overbought Chart 2It's Been A Long Time Since U.S. Stocks Corrected Take Out Some Insurance Take Out Some Insurance Irrational exuberance is back. Our Composite Sentiment Indicator has jumped to the highest level since right before the 1987 crash (Chart 3). Retail investors are also flooding back into the market. Discount brokers such as E*TRADE and Ameritrade have seen a flurry of activity (Chart 4).The latest monthly survey conducted by the American Association of Individual Investors showed that respondents had the largest allocation to stocks since 2000 (Chart 5). Chart 3Equity Investors Are Mega-Bullish Equity Investors Are Mega-Bullish Equity Investors Are Mega-Bullish Chart 4Retail Investors Have Piled In (Part I) Retail Investors Have Piled In (Part I) Retail Investors Have Piled In (Part I) Chart 5Retail Investors Have Piled In (Part II) Retail Investors Have Piled In (Part II) Retail Investors Have Piled In (Part II) The Economy And Earnings Still Paint A Bullish Backdrop Chart 6Economic Outlook Remains Solid Economic Outlook Remains Solid Economic Outlook Remains Solid In contrast to the ominous technical picture, the cyclical outlook for stocks looks reasonably solid (Chart 6). The Citigroup Economic Surprise Index for major advanced economies has risen to near record-high levels. Goldman's Global Current Activity Indicator stands close to a cycle high of 5%, up from 2.2% at the start of 2016. Our Global Leading Indicator has decelerated somewhat, but is still pointing to above-trend growth this year. Growth in the euro area remains strong. The economy grew by 2.5% in 2017, the fastest pace since 2007. U.S. growth is gathering steam. Real private final demand increased by 4.6% in Q4. The Atlanta Fed's GDPNow model is signaling growth of 5.4% in the first quarter, while the New York Fed Staff Nowcast is pointing to a more plausible growth rate of 3.1%. Reflecting the strong economy, corporate profits are ripping higher. 45% of S&P 500 companies have reported 2017 Q4 results. 80% have beaten consensus EPS projections, above the long-term average of 69%. 82% have beaten revenue projections, which also exceeds the long-term average of 56%. The fact that earnings and revenue have surprised so strongly to the upside is all the more impressive given the sharp increase in EPS estimates over the past few months (Chart 7). Moreover, the improvement in earnings has been broad-based across sectors (Table 1). Chart 7Analysts Scramble To Revise 2018 Earnings Estimates Higher Analysts Scramble To Revise 2018 Earnings Estimates Higher Analysts Scramble To Revise 2018 Earnings Estimates Higher Table 1Estimated Earnings Growth For 2018 Take Out Some Insurance Take Out Some Insurance Financial Conditions Are Supportive, But Rising Bond Yields Are A Risk Financial and monetary conditions remain accommodative, as judged by an assortment of financial conditions indices (Chart 8). The global credit impulse has surged (Chart 9). Chart 8Financial Conditions Have Eased Financial Conditions Have Eased Financial Conditions Have Eased Chart 9Global Credit Impulse Is Positive Global Credit Impulse Is Positive Global Credit Impulse Is Positive The recent rapid ascent in global bond yields complicates matters. So far, much of the increase in yields has been driven by higher inflation expectations. This has kept real yields down. Indeed, real 2-year yields have actually declined in the euro area and Japan over the last several months. In absolute terms, yields are still low by historic standards (Chart 10). As my colleague Doug Peta, who heads our Global ETF Strategy service, has documented, rising bond yields pose a bigger problem for the economy and risk assets when they move into restrictive territory (Table 2). We are not there yet (Chart 11). Stronger global growth and diminished spare capacity have pushed up the pain threshold for when rising bond yields begin to bite. In the U.S., fiscal stimulus and a cheaper dollar have also caused the neutral rate to rise. Chart 10Yields Are Still Low ##br## By Historic Standards Yields Are Still Low By Historic Standards Yields Are Still Low By Historic Standards Table 2Aggregate Real S&P 500 Returns ##br## During Rate Cycle Phases From August 1961 Take Out Some Insurance Take Out Some Insurance Chart 11Rates Not Hurting ... Yet Rates Not Hurting ... Yet Rates Not Hurting ... Yet Nevertheless, equities often struggle to digest rapid increases in bond yields. Although the late 2016 episode stands out as an exception, stocks have typically floundered following an increase in global bond yields of around 50 bps (Table 3). The yield on the JP Morgan Global Government Bond index has risen by 27 bps since last autumn. If yields continue their swift ascent, stocks could come under pressure. Table 3What Happens When Bond Yields Spike? Take Out Some Insurance Take Out Some Insurance Valuation Concerns Chart 12Demanding U.S. Valuations Point To Low Long-Term Returns Demanding U.S. Valuations Point To Low Long-Term Returns Demanding U.S. Valuations Point To Low Long-Term Returns Valuations are not much use for timing the stock market, but they are the most important driver of returns over the long haul. Chart 12 shows the close correlation between the Shiller P/E ratio in the U.S. and the subsequent 10-year total return for stocks. Even though realized earnings growth tends to be higher following periods when the P/E ratio is elevated, this is more than offset by a lower dividend yield and the compression of P/E multiples. Today's Shiller P/E ratio of 34 presages subpar returns over the next decade. The picture is somewhat better outside the U.S. Our composite valuation measure - which combines trailing P/E, price-to-sales, price-to-book, Tobin's Q, and market capitalization-to-GDP - suggests that most stock markets outside the U.S. will see returns in the low-to-mid single-digit range over the next ten years (Appendix 1). Nevertheless, this is still well below the historic average return for these markets. What To Do? Our cyclical overweight in global equities has worked out well, and barring evidence that the global economy is tipping into recession, we intend to maintain this recommendation. Nevertheless, the discussion above suggests that stocks are vulnerable to a near-term correction and that long-term returns are likely to be lackluster at best. As such, it is sensible to take out some insurance against a market selloff. The question, as always, is how to guard against a drop in equity prices without suffering too much of a drag if global bourses continue to grind higher. We noted three weeks ago that today's equity bull market is starting to look increasingly like the one in the late 1990s.1 Back then, rising equity prices were accompanied by both higher volatility and wider credit spreads (Chart 13). History seems to be repeating itself. The VIX bottomed on November 24 at 8.56 and ended last week at 11.08, even as the S&P 500 hit another record high. Investors should consider buying volatility futures on any major dip in the VIX. Junk bonds have also underperformed equities year-to-date, which has benefited our long S&P 500/short high-yield credit recommendation. As we go to press, the Barclays high-yield total return index is flat for the year, while the S&P 500 has gained 5.7%. Given the deterioration in our Corporate Health Monitor, and the likelihood that rising inflation will keep Treasury yields in an uptrend, investors should consider hedging equity risk by shorting junk bonds. Chart 13Volatility Can Increase And Spreads Can Widen As Stock Prices Rise Volatility Can Increase And Spreads Can Widen As Stock Prices Rise Volatility Can Increase And Spreads Can Widen As Stock Prices Rise Chart 14Chinese Growth Is Decelerating Moderately Chinese Growth Is Decelerating Moderately Chinese Growth Is Decelerating Moderately Go Short AUD/JPY Chart 15Iron Ore Stockpiles Are Hitting New Highs In China Iron Ore Stockpiles Are Hitting New Highs In China Iron Ore Stockpiles Are Hitting New Highs In China Going short the Australian dollar versus the Japanese yen is also an appealing hedge against a broad-based retreat from risk assets. The yen is a highly defensive currency. Japan has a healthy current account surplus of 4% of GDP. Its accumulated foreign assets outstrip foreign liabilities by a whopping 65% of GDP. When Japanese investors get nervous about the world and start repatriating funds back home, the yen invariably strengthens. The Aussie dollar is highly levered to the Chinese economy. While we do not expect a steep deceleration in Chinese growth this year, we do think that growth will fall from last year's heady pace. This can already be seen in the deterioration in the Li Keqiang index (Chart 14). The growth rate of railway freight, one of the index's components, has fallen from above 20% in early 2017 to -1%. Crucially for Australia, iron ore stockpiles in Chinese ports are hitting record highs (Chart 15). Meanwhile, the Reserve Bank of Australia's commodity index has rolled over. The year-over-year change in the index has dropped from a high of 47% six months ago to -1%. Domestically, the output gap stands at 2% of GDP. Both core CPI inflation and wage growth remain subdued (Chart 16). The household saving rate has dropped to 3%, while debt levels have reached nosebleed levels (Chart 17). This will limit consumer spending. Business confidence has dipped recently, as has the PMI new orders index (Chart 18). Mining capex has been trending lower, falling from over 6% of GDP in 2012 to 2.1% of GDP in 2017. The Australian government expects mining capex to sink further to 1.3% of GDP in 2018 (Chart 19). All this will limit the RBA's ability to hike rates. Chart 16Australian Core CPI Inflation And Wage Growth Remain Subdued Australian Core CPI Inflation And Wage Growth Remain Subdued Australian Core CPI Inflation And Wage Growth Remain Subdued Chart 17Australian Household Debt At Unsustainable Levels Australian Household Debt At Unsustainable Levels Australian Household Debt At Unsustainable Levels Chart 18Australia: Business Confidence And Orders Have Dipped Australia: Business Confidence And Orders Have Dipped Australia: Business Confidence And Orders Have Dipped Chart 19Mining Capex To Fall Further Mining Capex To Fall Further Mining Capex To Fall Further From a valuation perspective, AUD/JPY currently trades at a 27% premium to its Purchasing Power Parity exchange rate, having traded at a discount of as much as 50% back in 2000 (Chart 20). Speculators are heavily short the yen right now. As my colleague Mathieu Savary has noted, this could supercharge any short covering rally.2 Higher asset market volatility should also weaken the Aussie dollar. Chart 21 shows that AUD/JPY tends to be inversely correlated with the CVIX, an index of currency volatility. Chart 20AUD/JPY Trading At A Premium AUD/JPY Trading At A Premium AUD/JPY Trading At A Premium Chart 21Higher Vol Will Weaken AUD Higher Vol Will Weaken AUD Higher Vol Will Weaken AUD With this in mind, we are opening a new tactical trade recommendation to go short AUD/JPY. As a housekeeping matter, we are closing our long AUD/NZD trade for a loss of 1.8%. We were also stopped out of our long global industrial stocks versus utilities trade for a gain of 12%. Lastly, we are raising our stop on our short fed funds futures trade to 70 bps. Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com 1 Please see Global Investment Strategy Weekly Report, "Will Bitcoin be Defanged," dated January 12, 2018, available at gis.bcaresearch.com 2 Please see Foreign Exchange Strategy Weekly Report, "Yen: QQE Is Dead! Long Live YCC!," dated January 12, 2018, available at fes.bcaresearch.com Appendix 1 Chart A1Long-Term Return Prospects Are Slightly Better Outside The U.S. Take Out Some Insurance Take Out Some Insurance Long-Term Return Prospects Are Slightly Better Outside The U.S. Take Out Some Insurance Take Out Some Insurance Long-Term Return Prospects Are Slightly Better Outside The U.S. Take Out Some Insurance Take Out Some Insurance Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Watch Inflation Expectations How much longer can this go on? Global equities were up 6% in January alone (the 15th consecutive month of positive returns), and investors are increasingly asking how much further this bull market has to run. There are no signs we can see that suggest it will end imminently. Our watch-list of key recession indicators (decline in global PMIs, inverted yield curve, rise in credit spreads - Chart 1) is sending no warning signals. U.S. GDP growth was a little weaker than expected in Q4, at 2.6% QoQ annualized, but this was mainly due to inventories and strong imports: final private demand, a better guide to future growth, was strong at 4.3%. Fed NowCasts for Q1 growth point to 3.1-4.2%. The euro zone grew even faster than the U.S. last year, and even Japan probably saw 1.8% GDP growth. Corporate earnings expectations have accelerated sharply over just the past few weeks - particularly in the U.S. as a result of the tax cuts (Chart 2) - with analysts now expecting 16% EPS growth for the S&P 500 this year. BCA U.S. Equity Strategy service's earnings models suggest that this forecast may still be too cautious (Chart 3). Recommended Allocation Monthly Portfolio Update Monthly Portfolio Update Chart 1No Recession Signals Flashing No Recession Signals Flashing No Recession Signals Flashing Chart 2A Dramatic Rise In Earnings Forecasts... A Dramatic Rise In Earnings Forecasts... A Dramatic Rise In Earnings Forecasts... Chart 3...But Forecasts May Still Be Too Cautious ...But Forecasts May Still Be Too Cautious ...But Forecasts May Still Be Too Cautious While it is true that equity valuations are stretched, particularly in the U.S. (with BCA's Composite Valuation Index having just tipped into the "Extremely Overvalued" zone - Chart 4), valuations are not usually a good timing tool. Investor euphoria seems not yet to have reached the extremes that usually characterize a bull-market peak. The message we hear consistently from wealth managers is that their clients who missed last year's rally are now looking to get into risk assets. The American Association of Individual Investors' latest weekly survey shows 45% bulls to 24% bears - not especially optimistic by past standards (Chart 5). Flows into equity funds have started to accelerate, but have been weaker than bond flows over the past year (Chart 6). Chart 4U.S. Equities Now 'Extremely Overvalued' U.S. Equities Now 'Extremely Overvalued' U.S. Equities Now 'Extremely Overvalued' Chart 5Investors Are Not Particularly Bullish Investors Are Not Particularly Bullish Investors Are Not Particularly Bullish Chart 6Flows Into Equities Starting To Accelerate Flows Into Equities Starting To Accelerate Flows Into Equities Starting To Accelerate Chart 7Key: Inflation Expectations Getting to 2.5% Key: Inflation Expectations Getting to 2.5% Key: Inflation Expectations Getting to 2.5% We think the key to timing the top lies in inflation expectations. With the U.S. economy at full capacity and unemployment at 4.1%, well below the NAIRU of 4.6%, the Fed believes that a pick-up in inflation is just a matter of time - an analysis we agree with. The market has started to come round to this view too, with implied inflation rising by about 40 BPs over the past two months (Chart 7). The market has now priced in a 65% probability of the Fed's projected three rate hikes this year, and even a 27% probability of four. Inflation expectations hitting 2.5% (which would be compatible with the Fed's 2% PCE inflation target - CPI inflation is typically 50 BPs higher) could be the tipping-point. This is because it would remove the Fed put - with inflation expectations elevated, the Fed would no longer be able to back off from tightening in the event of a global risk-off event such as a stock-market correction or a slowdown in China. Such a rise in inflation expectations would also push the 10-year U.S. Treasury yield above 3%, which would increase the attraction of fixed income, and represent a threat to highly indebted borrowers, especially in emerging markets. This is how bull markets typically end: with the Fed having to raise rates to choke off inflation, and either making a policy mistake or tightening monetary policy enough to slow growth. But all this is probably quite a few months away. We expect to turn more defensive perhaps late this year, ahead of a recession that we have for some time now penciled in for the second half of 2019. Given how advanced the cycle is, conservative investors primarily concerned with capital preservation might look to dial down risk or hedge exposure now. But investors focused on quarterly performance should ride the bull market until some of the warning signals mentioned above begin to flash. For now, therefore, we continue to recommend an overweight in equities relative to bonds on the 12-month investment horizon, and mostly pro-risk and pro-cyclical tilts. Equities: We continue to prefer developed over emerging equities. EM will be hurt by the slowdown likely in China (where money supply and credit growth have fallen in response to the authorities' tighter policies - Chart 8), rising U.S. interest rates, sluggish productivity growth, and valuations that are no longer particularly cheap (Chart 9). Within DM, we are overweight euro zone and Japanese equities, which should benefit from their higher beta, more cyclical earnings, still accommodative monetary policy, and cheaper valuations than the U.S. Our sector bets are tilted to late-cycle value sectors such as financials, industrials and energy. Chart 8Tighter Monetary Conditions in China bca.gaa_mu_2018_02_01_c8 bca.gaa_mu_2018_02_01_c8 Chart 9EM No Longer Cheap EM No Longer Cheap EM No Longer Cheap Fixed Income: Rising inflation expectations should push the 10-year U.S. Treasury bond yield up to 3% this year, with German Bunds rising by a similar amount. We recommend an underweight on duration, and a preference for inflation-linked over nominal bonds, in these markets. In the U.K. and Australia, however, central banks are unlikely to tighten as quickly as futures markets have priced in and so we prefer their government bonds. While the expansion continues, spread product should continue to outperform in the fixed-income bucket. The default-adjusted spread on U.S. high-yield bonds remains over 200 BP and, though we see little further spread contraction, carry alone makes this attractive. Currencies: BCA was correct last year to predict a widening of interest-rate differentials between the U.S. and the euro zone, but wrong to conclude that this would lead to a stronger dollar (Chart 10). The drivers of currencies can undergo regime shifts, and it seems now that valuation (both the euro and yen are cheap compared to their purchasing power parity, 1.32 and 99 to the U.S. dollar respectively), current account surpluses (3.3% for the euro zone and 3.7% for Japan), and other factors have become more important. Tactically, the euro, in particular, looks very overbought. Speculative investors are very long euros, the ECB is likely to remain dovish relative to the Fed, and the strong euro could put some downward pressure on growth in the short-term. However, if the dollar were to rebound by 5% or so we would be likely to end our dollar bull call. Chart 10Rate Differentials No Longer Moving Currencies Rate Differentials No Longer Moving Currencies Rate Differentials No Longer Moving Currencies Chart 11Oil Supply To Increase In 2019 Oil Supply To Increase In 2019 Oil Supply To Increase In 2019 Commodities: Oil prices have risen on the back of strong global demand, OPEC discipline, and a lag in the response of U.S. shale oil producers. We forecast an average of $67 a barrel for Brent crude this year, with spikes to as high as $80 in the event of disruptions in producer countries such as Venezuela. However, with one-year forward crude prices around $62, shale producers (whose marginal costs average about $52 a barrel) are likely to pick up production soon. OPEC, too, should be happy with crude around $50-60. Our energy team forecasts a pick-up in supply next year (Chart 11), which should bring the crude price down to an average of $55 in 2019. Industrial commodities are a product of Chinese demand, global growth, and the U.S. dollar. These drivers look likely to be mixed over the coming months and so we remain neutral. Gold has risen, in the face of rising interest rates, because of the weak dollar - it remains an excellent hedge against inflation, recession, and geopolitical risks and so should be a modest part of any balanced portfolio. Garry Evans, Senior Vice President Global Asset Allocation garry@bcaresearch.com GAA Asset Allocation

Dear Client, In addition to this abbreviated Weekly Report, I am sending you a Special Report co-authored by Mark McClellan, Managing Editor of the monthly Bank Credit Analyst, and Brian Piccioni of Technology Sector Strategy. Mark and Brian argue that the deflationary impact of robot automation will not prevent inflation from rising as the labor market tightens. I hope you will find their report interesting and informative. Best regards, Peter Berezin, Chief Global Strategist Global Investment Strategy Highlights Our cyclically overweight stance on global equities/underweight stance on bonds is working. Stick with it. U.S. Treasury Secretary Mnuchin's comments about the dollar are unlikely to have any lasting effects. EUR/USD has decoupled from terminal rate expectations since the start of this year. Tactical trade recommendation: Go short EUR/USD while simultaneously going long 30-year U.S. Treasurys/short 30-year German bunds. Feature Global Equities Enter A Blow-Off Phase Valuations do not matter on the way up, but they sure do matter on the way down. Once the market reaches that Wile E. Coyote moment - the one where the poor sap runs off the cliff, pauses in mid-air, looks down, and sees the ground below - all hell will break loose. On every valuation measure, U.S. stocks, and increasingly global stocks, have become very expensive (Chart 1). Chart 1AU.S. Stocks Are Expensive... U.S. Stocks Are Expensive... U.S. Stocks Are Expensive... Chart 1B...While Global Stocks Are Getting There ...While Global Stocks Are Getting There ...While Global Stocks Are Getting There That moment, however, is unlikely to arrive until the global economy and earnings growth begin to stall out. As we have argued in past reports, this probably will not happen until late next year. Historically, it has not paid to get defensive until six months before the start of a recession (Table 1). This suggests that stocks could continue to rally right through 2018. Beep beep. Table 1Too Soon To Get Out The Indefatigable Euro The Indefatigable Euro Granted, the timing of our recession call could turn out to be wrong, which is why we are watching a wide number of leading variables for signs that a slowdown is around the corner (Chart 2). In the U.S., these include credit spreads, the slope of the yield curve, financial conditions, business and consumer confidence, ISM new orders minus inventories, building permits, core capital goods orders, and initial unemployment claims. We have consolidated these variables and dozens of others into our MacroQuant model. The model is still pointing to a reasonably rosy cyclical outlook for stocks (Chart 3). Chart 2Leading Cyclical Data Still Strong Leading Cyclical Data Still Strong Leading Cyclical Data Still Strong Chart 3Cyclical Outlook For Stocks Is Still Rosy The Indefatigable Euro The Indefatigable Euro The Dollar Takes A Pounding While our cyclical bullish view on stocks and bearish view on bonds has paid off this year, our expectation that the dollar would recoup some of last year's losses has not worked out. Time will tell if December 2016 marked the beginning of a secular dollar bear market. The dollar tends to suffer when global growth accelerates. This happened last year. The dollar also tends to weaken when the composition of growth shifts away from the United States. That also happened in 2017. The remainder of this year could be different. We expect global growth to remain solidly above-trend in 2018, but ease from the torrid pace of 2017. This is already being foreshadowed by the decline in our Global LEI diffusion index to below 50%, a slowdown in Korean and Taiwanese exports, a deceleration in the Chinese Li Keqiang Index, and the loss of momentum in EM carry trades (Chart 4). Meanwhile, the composition of global growth should shift back in favor of the U.S. The fact that the U.S. Economic Surprise index has recovered in recent months relative to other economies suggests that this reversal of fortunes is already underway (Chart 5). The end result for asset markets could be slightly reminiscent of the late 1990s, a period when both equities and the dollar rallied. Chart 4Global Growth Will Remain Above-Trend ##br##But Ease From Blistering Pace Global Growth Will Remain Above-Trend But Ease From Blistering Pace Global Growth Will Remain Above-Trend But Ease From Blistering Pace Chart 5Composition Of Global Growth Will Shift ##br##Back In Favor Of The U.S. Composition Of Global Growth Will Shift Back In Favor Of The U.S. Composition Of Global Growth Will Shift Back In Favor Of The U.S. Talk Is Cheap Chart 6Trade-Weighted Dollar No Longer Pricey Trade-Weighted Dollar No Longer Pricey Trade-Weighted Dollar No Longer Pricey We do not put much weight on the remarks concerning the dollar made by Treasury Secretary Steven Mnuchin at Davos this week. While Mnuchin did say that "obviously a weaker dollar is good for us as it relates to trade and opportunities," he added that "longer term, the strength of the dollar is a reflection of the strength of the U.S. economy and the fact that it is and it continues to be the primary currency in terms of the reserve currency." More importantly, history suggests that verbal interventions in currency markets are only effective beyond the near term when backed by a supporting change in monetary policy. Many people remember the success that then-Treasury Secretary James Baker had in driving down the dollar following the Plaza Accord in 1985, but what is often forgotten is that the Federal Reserve steadily cut rates from 11.8% in July 1984 to 5.8% in October 1986. As a result, the 2-year interest rate differential fell by 454 bps against Japan, 630 bps against the U.K., and 407 bps against Germany over this period. It is also worth noting that the Fed's real broad trade-weighted dollar index is now 27% below its 1985 peak and 3% below its long-term average (Chart 6). This makes any effort to talk down the dollar all the more difficult. ECB Sending Mixed Messages About The Euro Chart 7Market Has Brought Forward ECB Rate Hikes Market Has Brought Forward ECB Rate Hikes Market Has Brought Forward ECB Rate Hikes ECB officials continue to send mixed messages about the resurgent euro. Earlier this month, ECB Vice President Vitor Constâncio and Bank of France Governor François Villeroy both expressed concern about the euro's strength, as did Ewald Nowotny, the fairly hawkish President of Austria's central bank. In contrast, Mario Draghi refused to wade into the debate during yesterday's press conference. The lack of angst in his tone sent the euro higher. Draghi's reluctance to say anything concrete about the euro was partly motivated by the desire to avoid the sort of "beggar thy neighbor" criticism that greeted Mnuchin's remarks. Like other central banks, the ECB gives a lot of weight to financial conditions in setting monetary policy. A stronger currency has tightened euro area financial conditions. This is something that must concern the ECB, at least behind closed doors. Ultimately, any effort by the ECB to knock down the euro will only work if it convinces the market to soften its expectations about the future pace of rate hikes. The likelihood of such an outcome is certainly higher now than it was in 2016. Our "months to hike" measure for the ECB has plummeted from over 60 months in mid-2016 to 19 today (Chart 7). Given that the ECB has made it clear that it intends to delay raising rates for some time after asset purchases end later this year, it is hard to see the central bank hiking rates before the summer of 2019. That is not far from where market pricing now stands. In contrast, if euro area growth were to surprise meaningfully on the downside or if core inflation in the peripheral economies continues to fall - it is already close to zero in Italy - the ECB could be forced to bide its time longer than the market currently expects. A Safer Way To Short EUR/USD Chart 8EUR/USD And Rate Decoupling ##br##Will Not Last Long EUR/USD And Rate Decoupling Will Not Last Long EUR/USD And Rate Decoupling Will Not Last Long Still, the euro has a lot going for it. Unlike the U.S., the euro area is running a current account surplus. This means the region does not need to attract foreign capital for there to be excess demand for euros. All it needs to do is keep net capital outflows roughly below 3% of GDP. The ability of the euro area to retain and attract fresh capital has become easier as political risk has ebbed and the ECB's pledge to do "whatever it takes" to preserve the euro has solidified. The euro's share of global central bank reserves currently stands at 20%, well below the 60% share enjoyed by the U.S. dollar. If capital continues to gravitate towards the region, the euro could strengthen further. All this makes shorting the euro a risky bet. With that in mind, investors should consider hedging short EUR/USD positions by wagering that the terminal rate spread between the euro area and the U.S. will narrow. Chart 8 shows that the spread in expected policy rates ten years out has decoupled from EUR/USD since the start of the year. The same is true for the 30-year spread between Treasurys and bunds - another good proxy for the terminal rate spread. While spreads have widened in favor of the dollar, the greenback has nonetheless plunged. Such decoupling rarely lasts long, which makes this a highly attractive trade. With that in mind, we are going short EUR/USD as a tactical trade while hedging the risk of a stronger euro by going long 30-year Treasurys/short 30-year bunds (a bet on further spread compression). Given that the first leg of the trade is more volatile than the second, we are scaling up the latter by a factor of 1.5. We will aim to close the trade for a gain of 5% (EUR/USD of about 1.18), assuming no change in the current spread of 160 bps. Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Dear Client, In addition to this Special Report written by my colleagues Mark McClellan and Brian Piccioni, we are sending you an abbreviated weekly report. Best regards, Peter Berezin, Chief Global Strategist Global Investment Strategy Highlights Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Feature Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart 1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart 1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart 2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart 3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart 2Global Robot Usage Global Robot Usage Global Robot Usage Chart 3Global Robot Usage By Industry (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart 4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart 5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart 4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart 5Stock Of Robots By Country (II) (2016) The Impact Of Robots On Inflation The Impact Of Robots On Inflation While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart 6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 Chart 6U.S. Investment In Robots U.S. Investment In Robots U.S. Investment In Robots The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart 7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart 7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix 1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart 8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart 8U.S.: Productivity Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart 9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart 10). Chart 9GPT Contribution To Productivity The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 10U.S.: Unit Labor Costs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart 11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart 11Inflation Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box 1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart 12). Box 1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart 12U.S. Job Rotation Has Slowed The Impact Of Robots On Inflation The Impact Of Robots On Inflation The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart 13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix 2 for more details. Chart 13Global Manufacturing Jobs Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix 1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart 14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart 14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix 2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart 4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart 15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart 16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart 15Japan: Earnings Vs. Robot Density The Impact Of Robots On Inflation The Impact Of Robots On Inflation Chart 16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood Of Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017) "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against the Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com. 10 OECD Productivity Working Papers, No. 05 (2016) "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 8.

Highlights U.S. equities 'melted up' in January as tax cuts made the robust growth/low inflation sweet spot even sweeter. Ominously, recent market action is beginning to resemble a classic late cycle blow-off phase. The fundamentals supporting the market will persist through most of the year, before an economic downturn in the U.S. takes hold in 2019. The repatriation of overseas corporate cash will also flatter EPS growth this year via buyback and M&A activity. The S&P 500 could return 14% or more this year. Unfortunately, the consensus now shares our upbeat view for 2018. Valuation is stretched and many indicators suggest that investors have become downright giddy. This month we compare valuation across the major asset classes. U.S. equities are the most overvalued, followed by gold, raw industrials and EM assets. Oil is still close to fair value. Long-term investors should already be scaling back on risk assets. Investors with a 6-12 month horizon should stay overweight equities versus bonds for now, but a risk management approach means that they should not try to squeeze out the last few percentage points of return. In terms of the sequencing of the exit from risk, the most consistent lead/lag relationship relative to previous tops in the equity market is provided by U.S. corporate bonds. For this reason, we are likely to take profits on corporates before equities. EM assets are already at underweight. We still see a window for the U.S. dollar to appreciate, although by only about 5%. A lot of good news is discounted in the euro, peripheral core inflation is slowing and ECB policymakers are getting nervous. Monetary policy remains the main risk to a pro-cyclical investment stance, although not because of the coming change in the makeup of the FOMC. The economy and inflation should justify four Fed rate hikes in 2018 no matter the makeup. The bond bear phase will continue. Feature Chart I-1Investors Are Giddy Investors Are Giddy Investors Are Giddy U.S. equities 'melted up' in January as tax cuts made the robust growth/low inflation sweet spot even sweeter. Ominously, though, recent market action is beginning to resemble the classic late cycle blow-off phase. Such blow-offs can be highly profitable, but also make it more difficult to properly time the market top. Our base case is that the fundamentals supporting the market will persist through most of the year, before an economic downturn in the U.S. takes hold in 2019. Unfortunately, the consensus now shares our upbeat view for 2018 and many indicators suggest that investors have become downright giddy (Chart I-1). These indicators include investor sentiment, our speculation index, and the bull-to-bear ratio. Net S&P earnings revisions and the U.S. economic surprise index are also extremely elevated, while equity and bond implied volatility are near all-time lows. From a contrarian perspective, these observations suggest that a lot of good news is discounted and that the market is vulnerable to even slight disappointments. It is also a bad sign that our Revealed Preference Indicator moved off of its bullish equity signal in January (see Section III for more details). Meanwhile, central banks are beginning to take away the punchbowl as global economic slack dissipates. This is all late-cycle stuff. Equity valuation does not help investors time the peak in markets, but it does tell us something about downside risk and medium-term expected returns. The Shiller P/E ratio has surged above 30 (Chart I-2). Chart I-3 highlights that, historically, average total returns were negligible over the subsequent 10-year period when the Shiller P/E was in the 30-40 range. Granted, the Shiller P/E will likely fall mechanically later this year as the collapse of earnings in 2008 begins to drop out of the 10-year EPS calculation. Nonetheless, even the BCA Composite Valuation indicator, which includes some metrics that account for extremely low bond yields, surpassed +1 standard deviations in January (our threshold for overvaluation; Chart I-2, bottom panel). An overvaluation signal means that investors should be biased to take profits early. Chart I-2BCA Valuation Indicator Surpasses One Sigma BCA Valuation Indicator Surpasses One Sigma BCA Valuation Indicator Surpasses One Sigma Chart I-3Expected Returns Given Starting Point Shiller P/E February 2018 February 2018 As we highlighted in our 2018 Outlook Report, long-term investors should already be scaling back on risk assets. We recommend that investors with a 6-12 month horizon should stay overweight equities versus bonds for now, but we need to be vigilant in terms of scouring for signals to take profits. A risk management approach means that investors should not try to get the last few percentage points of return before the peak. U.S. Earnings And Repatriation Before we turn to the timing and sequence of our exit from risk assets, we will first update our thoughts on the earnings cycle. Fourth quarter U.S. earnings season is still in its early innings, but the banking sector has set an upbeat tone. S&P 500 profits are slated to register a 12% growth rate for both Q4/2017 and calendar 2017. Current year EPS growth estimates have been aggressively ratcheted higher (from 12% growth to 16%) in a mere three weeks on the back of Congress' cut to the corporate tax rate.1 U.S. margins fell slightly in the fourth quarter, but remain at a high level on the back of decent corporate pricing power. A pick-up in productivity growth into year-end helped as well. Our short-term profit model remains extremely upbeat (Chart I-4). The positive profit outlook for the first half of the year is broadly based across sectors as well, according to the recently updated EPS forecast models from BCA's U.S. Equity Sector Strategy service.2 The repatriation of overseas corporate cash will also flatter EPS growth this year via buyback and M&A activity. Studies of the 2004 repatriation legislation show that most of the funds "brought home" were paid out to shareholders, mostly in the form of buybacks. A NBER report estimated that for every dollar repatriated, 92 cents was subsequently paid out to shareholders in one form or another. The surge in buybacks occurred in 2005, according to the U.S. Flow of Funds accounts and a proxy using EPS growth less total dollar earnings growth for the S&P 500 (Chart I-5). The contribution to EPS growth from buybacks rose to more than 3 percentage points at the peak in 2005. Chart I-4Profit Growth Still Accelerating Profit Growth Still Accelerating Profit Growth Still Accelerating Chart I-5U.S. Buybacks To Lift EPS U.S. Buybacks To Lift EPS U.S. Buybacks To Lift EPS We expect that most of the repatriated funds will again flow through to shareholders, rather than be used to pay down debt or spent on capital goods. Cash has not been a constraint to capital spending in recent years outside of perhaps the small business sector, which has much less to gain from the tax holiday. A revival in animal spirits and capital spending is underway, but this has more to do with the overall tax package and global growth than the ability of U.S. companies to repatriate overseas earnings. Estimates of how much the repatriation could boost EPS vary widely. Most of it will occur in the Tech and Health Care sectors. Buybacks appear to have lifted EPS growth by roughly one percentage point over the past year. We would not be surprised to see this accelerate by 1-2 percentage points, although the timing could be delayed by a year if the 2004 tax holiday provides the correct timeline. This is certainly positive for the equity market, but much of the impact could already be discounted in prices. Organic earnings growth, and the economic and policy outlook will be the main drivers of equity market returns over the next year. We expect some profit margin contraction later this year, but our 5% EPS growth forecast is beginning to look too conservative. This is especially the case because it does not include the corporate tax cuts. The amount by which the tax cuts will boost earnings on an after-tax basis is difficult to estimate, but we are using 5% as a conservative estimate. Adding 2% for buybacks and 2% for dividends, the S&P 500 could provide an attractive 14% total return this year (assuming no multiple expansion). Timing The Exit Chart I-6Timing The Exit (I) Timing The Exit (I) Timing The Exit (I) That said, we noted in last month's Report and in BCA's 2018 Outlook that this will be a transition year. We expect a recession in the U.S. sometime in 2019 as the Fed lifts rates into restrictive territory. Equities and other risk assets will sniff out the recession about six months in advance, which means that investors should be preparing to take profits sometime during the next 12 months. Last month we discussed some of the indicators we will watch to help us time the exit. The 2/10 Treasury yield curve has been a reliable recession indicator in the past. However, the lead time on the peak in stocks was quite extended at times (Chart I-6). A shift in the 10-year TIPS breakeven rate above 2.4% would be consistent with the Fed's 2% target for the PCE measure of inflation. This would be a signal that the FOMC will have to step-up the pace of rate hikes and aggressively slow economic growth. We expect the Fed to tighten four times in 2018. We are likely to take some money off the table if core inflation is rising, even if it is still below 2%, at the time that the TIPS breakeven reaches 2.4%. We will also be watching seven indicators that we have found to be useful in heralding market tops, which are summarized in our Scorecard Indicator (Chart I-7). At the moment, four out of the seven indicators are positive (Chart I-8): State of the Business Cycle: As early signals that the economy is softening, watch for the ISM new orders minus inventories indicator to slip below zero, or the 3-month growth rate of unemployment claims to rise above zero. Monetary and Financial Conditions: Using interest rates to judge the stance of monetary policy has been complicated by central banks' use of their balance sheet as a policy tool. Thus, it is better to use two of our proprietary indicators: the BCA Monetary Indicator (MI) and the Financial Conditions Indictor. The S&P 500 index has historically rallied strongly when the MI is above its long-term average. Similarly, equities tend to perform well when the FCI is above its 250-day moving average. The MI is sending a negative signal because interest rates have increased and credit growth has slowed. However, the broader FCI remains well in 'bullish' territory. Price Momentum: We simply use the S&P 500 relative to its 200-day moving average to measure momentum. Currently, the index is well above that level, providing a bullish signal for the Scorecard. Sentiment: Our research shows that stock returns have tended to be highest following periods when sentiment is bearish but improving. In contrast, returns have tended to be lowest following periods when sentiment is bullish but deteriorating. The Scorecard includes the BCA Speculation Indicator to capture sentiment, but virtually all measures of sentiment are very high. The next major move has to be down by definition. Thus, sentiment is assigned a negative value in the Scorecard. Value: As discussed above, value is poor based on the Shiller P/E and the BCA Composite Valuation indicator. Valuation may not help with timing, but we include it in our Scorecard because an overvalued signal means investors should err on the side of getting out early. Chart I-7Equity ScoreCard: Watch For A Dip Below 3 Equity ScoreCard: Watch For A Dip Below 3 Equity ScoreCard: Watch For A Dip Below 3 Chart I-8Timing The Exit (II) Timing The Exit (II) Timing The Exit (II) We demonstrated in previous research that a Scorecard reading of three or above was historically associated with positive equity total returns in subsequent months. A drop below three this year would signal the time to de-risk. Table I-1Exit Checklist February 2018 February 2018 To our Checklist we add the U.S. Leading Economic index, which has a good track record of calling recessions. However, we will use the LEI excluding the equity market, since we are using it as an indicator for the stock market. It is bullish at the moment. Our Global LEI is also flashing green. Table I-1 provides a summary checklist for trimming equity exposure. At the moment, 2 out of 9 indicators are bearish. Cross Asset Valuation Comparison Clients have asked our view on the appropriate order in which to scale out of risk assets. One way to approach the question is to compare valuation across asset classes. Presumably, the ones that are most overvalued are at greatest risk, and thus profits should be taken the earliest. It is difficult to compare valuation across asset classes. Should one use fitted values from models or simple deviations from moving averages? Over what time period? Since there is no widely accepted approach, we include multiple measures. More than one time period was used in some cases to capture regime changes. Table I-2 provides out 'best guestimate' for nine asset classes. The approaches range from sophisticated methods developed over many years (i.e. our equity valuation indicators), to regression analysis on the fundamentals (oil), to simple deviations from a time trend (real raw industrial commodity prices and gold). Table I-2Valuation Levels For Major Asset Classes February 2018 February 2018 We averaged the valuation readings in cases where there are multiple estimates for a single asset class. The results are shown in Chart I-9. Chart I-9Valuation Levels For Major Asset Classes February 2018 February 2018 U.S. equities stand out as the most expensive by far, at 1.8 standard deviations above fair value. Gold, raw industrials and EM equities are next at one standard deviation overvalued. EM sovereign bond spreads come next at 0.7, followed closely by U.S. Treasurys (real yield levels) and investment-grade corporate (IG) bonds (expressed as a spread). High-yield (HY) is only about 0.3 sigma expensive, based on default-adjusted spreads over the Treasury curve. That said, both IG and HY are quite expensive in absolute terms based on the fact that government bonds are expensive. Oil is sitting very close to fair value, despite the rapid price run up over the past couple of months. This makes oil exposure doubly attractive at the moment because the fundamentals point to higher prices at a time when the underlying asset is not expensive. Sequencing Around Past S&P 500 Peaks Historical analysis around equity market peaks provides an alternative approach to the sequencing question. Table I-3 presents the number of days that various asset classes peaked before or after the past major five tops in the S&P 500. A negative number indicates that the asset class peaked before U.S. equities, and a positive number means that it peaked after. Table I-3Asset Class Leads & Lags Vs. Peak In S&P 500 February 2018 February 2018 Unfortunately, there is no consistent pattern observed for EM equities, raw industrials, U.S. cyclical stocks, Tech stocks, or small-cap versus large-cap relative returns. Sometimes they peaked before the S&P 500, and sometime after. The EM sovereign bond excess return index peaked about 130 days in advance of the 1998 and 2007 U.S. equity market tops, although we only have three episodes to analyse due to data limitations. Oil is a mixed bag. A peak in the price of gold led the equity market in four out of five episodes, but the lead time is long and variable. The most consistent lead/lag relationship is given by the U.S. corporate bond market. Both investment- and speculative-grade excess returns relative to government bonds peaked in advance of U.S. stocks in four of the five episodes. High-yield excess returns provided the most lead time, peaking on average 154 days in advance. Excess returns to high-yield were a better signal than total returns. This leading relationship is one reason why we plan to trim exposure to corporate bonds within our bond portfolio in advance of scaling back on equities. But the 'return of vol' that we expect to occur later this year will take a toll on carry trades more generally. We are already underweight EM equities and bonds. This EM recommendation has not gone in our favor, but it would make little sense to upgrade them now given our positive views on volatility and the dollar. An unwinding of carry trades will also hit the high-yielding currencies outside of the EM space, such as the Kiwi and Aussie dollar. Base metal prices will be hit particularly hard if the 2019 U.S. recession spills over to the EM economies as we expect. We may downgrade base metals from neutral to underweight around the time that we downgrade equities, but much depends on the evolution of the Chinese economy in the coming months. Oil is a different story. OPEC 2.0 is likely to cut back on supply in the face of an economic downturn, helping to keep prices elevated. We therefore may not trim energy exposure this year. As for equity sectors, our recommended portfolio is still overweight cyclicals for now. Our synchronized global capex boom, rising bond yield, and firm oil price themes keep us overweight the Industrials, Energy and Financial sectors. Utilities and Homebuilders are underweight. Tech is part of the cyclical sector, but poor valuation keeps us underweight. That said, our sector specialists are already beginning a gradual shift away from cyclicals toward defensives for risk management purposes. This transition will continue in the coming months as we de-risk. We are also shifting small caps to neutral on earnings disappointments and elevated debt levels. The Dollar Pain Trade Market shifts since our last publication have largely gone in our favor; stocks have surged, corporate bonds spreads have tightened, oil prices have spiked, bonds have sold off and cyclical stocks have outperformed defensives. One area that has gone against us is the U.S. dollar. Relative interest rate expectations have moved in favor of the dollar as we expected at both the short- and long-ends of the curve. Nonetheless, the dollar has not tracked its historical relationship versus both the yen and euro. The Greenback did not even get a short-term boost from the passage of the tax plan and holiday on overseas earnings. Perhaps this is because the lion's share of "overseas" earnings are already held in U.S. dollars. Reportedly, a large fraction is even held in U.S. banks on U.S. territory. Currency conversion is thus not a major bullish factor for the U.S. dollar. The recent bout of dollar weakness began around the time of the release of the ECB Minutes in January which were interpreted as hawkish because they appeared to be preparing markets for changes in monetary policy. The European debt crisis and economic recession were the reasons for the ECB's asset purchases and negative interest rate policy. Neither of these conditions are in place now. The ECB is meeting as we go to press, and we expect some small adjustments in the Statement that remove references to the need for "crisis" level accommodations. Subsequent steps will be to prepare markets for a complete end to QE, perhaps in September, and then for rates hikes likely in 2019. The key point is that European monetary policy has moved beyond 'peak stimulus' and the normalization process will continue. Perhaps this is partly to blame for euro strength although, as mentioned above, interest rate differentials have moved in favor of the dollar. Does this mean that the dollar has peaked and has entered a cyclical bear phase that will persist over the next 6-12 months? The answer is 'no', although we are less bullish than in the past. We believe there is still a window for the dollar to appreciate against the euro and in broader trade-weighted terms by about 5%. First, a lot of euro-bullish news has been discounted (Chart I-10). Positive economic surprises heavily outstripped that in the U.S. last year, but that phase is now over. The euro appears expensive based on interest rate differentials, and euro sentiment is close to a bullish extreme. This all suggests that market positioning has become a negative factor for the currency. Chart I-10Euro: A Lot Of Bullish News Is Discounted EURO: A Lot Of Bullish News Is Discounted EURO: A Lot Of Bullish News Is Discounted Second, the chorus of complaints against the euro's strength is growing among European central bankers, including Ewald Nowotny, the rather hawkish Austrian central banker. Policymakers' concerns may partly reflect the fact that peripheral inflation excluding food and energy has already weakened to 0.6% from a high of 1.3% in April last year (Chart I-10, fourth panel). Third, U.S. consumer price and wage inflation have yet to pick up meaningfully. The dollar should receive a lift if core U.S. inflation clearly moves toward the Fed's 2% target, as we expect. The FOMC would suddenly appear to have fallen behind the curve and U.S. rate expectations would ratchet higher. Chart I-10, bottom panel, highlights that the euro will weaken if U.S. core inflation rises versus that in the Eurozone. The implication is that the Euro's appreciation has progressed too far and is due for a pullback. As for the yen, the currency surged in January when the Bank of Japan (BoJ) announced a reduction in long-dated JGB purchases. This simply acknowledged what has already occurred. It was always going to be impossible to target both the quantity of bond purchases and the level of 10-year yield simultaneously. Keeping yields near the target required less purchases than they thought. The market interpreted the BoJ's move as a possible prelude to lifting the 10-year yield target. It is perhaps not surprising that the market took the news this way. The economy is performing extremely well; our model that incorporates high-frequency economic data suggests that real GDP growth will move above 3% in the coming quarters. The Japanese economy is benefiting from the end of a fiscal drag and from a rebound in EM growth. Nonetheless, following January's BoJ policy meeting, Kuroda poured cold water on speculation that the BoJ may soon end or adjust the YCC. Recent speeches by BoJ officials reinforce the view that the MPC wants to see an overshoot of actual inflation that will lower real interest rates and thereby reinforce the strong economic activity that is driving higher inflation. Only then will officials be convinced that their job is done. Given that inflation excluding food and energy only stands at 0.3%, the BoJ is still a long way from the overshoot it desires. On the positive side, Japan's large current account surplus and yen undervaluation provide underlying support for the currency. Balancing the offsetting positive and negative forces, our foreign exchange strategists have shifted to neutral on the yen. The Euro remains underweight while the dollar is overweight. Similar to our dollar view, we still see a window for U.S. Treasurys to underperform the global hedged fixed-income benchmark as world bond yields shift higher this year. European government bonds will also sell off, but should outperform Treasurys. JGBs will provide the best refuge for bondholders during the global bond bear phase, since the BoJ will prevent a rise in yields inside of the 10-year maturity. Our global bond strategists upgraded U.K. gilts to overweight in January. Momentum in the U.K. economy is slowing, as a weaker consumer, slower housing activity, and softer capital spending are offsetting a pickup in exports. With the inflationary impulse from the 2016 plunge in the Pound now fading, and with Brexit uncertainty weighing on business confidence, the Bank of England will struggle to raise rates in 2018. FOMC Transition Monetary policy remains the main risk to a pro-cyclical investment stance, although not because of the coming change in the makeup of the FOMC. An abrupt shift in policy is unlikely. There was some support at the December 2017 FOMC meeting to study the use of nominal GDP or price level targeting as a policy framework, but this has been an ongoing debate that will likely continue for years to come. The Fed will remain committed to its current monetary policy framework once Powell takes over. Table I-4 provides a summary of who will be on the FOMC next year, including their policy bias. Chart I-11 compares the recent FOMC makeup with the coming Powell FOMC (voting members only). The hawk/dove ratio will not change much under Powell, unless Trump stacks the vacant spots with hawks. Table I-4Composition Of The FOMC February 2018 February 2018 Chart I-11Composition Of Voting FOMC Members 2017 Vs. 2018 February 2018 February 2018 In any event, history shows that the FOMC strives to avoid major shifts in policy around changeovers in the Fed Chair. In previous transitions, the previous path for rates was maintained by an average of 13 months. Moreover, Powell has shown that he is not one to rock the boat during his time on the FOMC. It will be the evolution of the economy and inflation, not the composition of the FOMC, that will have the biggest impact on markets at the end of the day. Recent speeches reveal that policymakers across the hawk/dove spectrum are moving modesty toward the hawkish side because growth has accelerated at a time when unemployment is already considered to be below full-employment by many policymakers. The melt-up in equity indexes in January did little to calm worries about financial excesses either. The Fed is struggling to understand the strength of the structural factors that could be holding down inflation. This month's Special Report, beginning on page 21, focusses on the impact of robot automation. While advances on this front are impressive, we conclude that it is difficult to find evidence that robots are more deflationary than previous technological breakthroughs. Thus, increased robot usage should not prevent inflation from rising as the labor market continues to tighten. The macro backdrop will likely justify the FOMC hiking at least as fast as the dots currently forecast. The risks are skewed to the upside. The median Fed dot calls for an unemployment rate of 3.9% by end-2018, only marginally lower than today's rate of 4.1%. This is inconsistent with real GDP growth well in excess of its supply-side potential. The unemployment rate is more likely to reach a 49-year low of 3.5% by the end of this year. As highlighted in last month's Report, a key risk to the bull market in risk assets is the end of the 'low vol/low rate' world. The selloff in the bond market in January may mark the start of this process. Conclusions We covered a lot of ground in this month's Overview of the markets, so we will keep the conclusions brief and focused on the risks. Our key point is that the fundamentals remain positive for risk assets, but that a lot of good news is discounted and it appears that we have entered a classic blow-off phase. This will be a transition year to a recession in the U.S. in 2019. Given that valuation for most risk assets is quite stretched, and given that the monetary taps are starting to close, investors must plan for the exit and keep an eye on our timing checklist. The main risk to our pro-cyclical portfolio is a rise in U.S. inflation and the Fed's response, which we believe will end the sweet spot for risk assets. Apart from this, our geopolitical strategists point to several other items that could upset the applecart this year:3 1. Trade China has cooperated with the U.S. in trying to tame North Korea. Nonetheless, President Trump is committed to an "America First" trade policy and he may need to show some muscle against China ahead of the midterm elections in November in order to rally his base. It is politically embarrassing to the Administration that China racked up its largest trade surplus ever with the U.S. in Trump's first year in office. A key question is whether the President goes after China via a series of administrative rulings - such as the recently announced tariffs on solar panels and white goods - or whether he applies an across-the-board tariff and/or fine. The latter would have larger negative macroeconomic implications. 2. Iran On January 12, President Trump threatened not to waive sanctions against Iran the next time they come due (May 12), unless some new demands are met. Pressure from the U.S. President comes at a delicate time for Iran. Domestic unrest has been ongoing since December 28. Although protests have largely fizzled out, they have reopened the rift between the clerical regime, led by Supreme Leader Ayatollah Ali Khamenei, and moderate President Hassan Rouhani. Iranian hardliners, who control part of the armed forces, could lash out in the Persian Gulf, either by threatening to close the Straits of Hormuz or by boarding foreign vessels in international waters. The domestic political calculus in both Iran and the U.S. make further Tehran-Washington tensions likely. For the time being, however, we expect only a minor geopolitical risk premium to seep into the energy markets, supporting our bullish House View on oil prices. 3. China Last month's Special Report highlighted that significant structural reforms are on the way in China, now that President Xi has amassed significant political support for his reform agenda. The reforms should be growth-positive in the long term, but could be a net negative for growth in the near term depending on how deftly the authorities handle the monetary and fiscal policy dials. The risk is that the authorities make a policy mistake by staying too tight, as occurred in 2015. We are monitoring a number of indicators that should warn if a policy mistake is unfolding. On this front, January brought some worrying economic data. The latest figures for both nominal imports and money growth slowed. Given that M2 and M3 are components of BCA's Li Keqiang Leading Indicator, and that nominal imports directly impact China's contribution to global growth, this raises the question of whether December's economic data suggest that China is slowing at a more aggressive pace than we expect. For now, our answer is no. First, China's trade numbers are highly volatile; nominal import growth remains elevated after smoothing the data. Second, China's export growth remains buoyant, consistent with a solid December PMI reading. The bottom line is that we are sticking with our view that China will experience a benign deceleration in terms of its impact on DM risk assets, but we will continue to monitor the situation closely. Mark McClellan Senior Vice President The Bank Credit Analyst January 25, 2018 Next Report: February 22, 2018 1 According to Thomson Reuters/IBES. 2 Please see U.S. Equity Sector Strategy Special Report "White Paper: Introducing Our U.S. Equity Sector Earnings Models," dated January 16, 2018, available at uses.bcaresearch.com 3 For more information, please see BCA Geopolitical Strategy Weekly Report "Upside Risks In U.S., Downside Risks In China," dated January 17, 2018, available at gps.bcaresearch.com. Also see "Watching Five Risks," dated January 24, 2018. II. The Impact Of Robots On Inflation Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart II-1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart II-1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart II-2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart II-3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart II-2Global Robot Usage Global Robot Usage Global Robot Usage Chart II-3Global Robot Usage By Industry (2016) February 2018 February 2018 As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart II-4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart II-5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart II-4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart II-5Stock Of Robots By Country (II) (2016) February 2018 February 2018 While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. Chart II-6U.S. Investment In Robots U.S. Investment in Robots U.S. Investment in Robots In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart II-6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart II-7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart II-7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix II-1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart II-8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart II-8U.S.: Productivity Vs. Robot Density February 2018 February 2018 Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart II-9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart II-10). Chart II-9GPT Contribution To Productivity February 2018 February 2018 Chart II-10U.S.: Unit Labor Costs Vs. Robot Density February 2018 February 2018 In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart II-11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart II-11Inflation Vs. Robot Density February 2018 February 2018 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box II-1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart II-12). Box II-1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart II-12U.S. Job Rotation Has Slowed February 2018 February 2018 The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart II-13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix II-2 for more details. Chart II-13Global Manufacturing Jobs Vs. Robot Density February 2018 February 2018 The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix II-1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart II-14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart II-14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix II-2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart II-4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart II-15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart II-16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart II-15Japan: Earnings Vs. Robot Density February 2018 February 2018 Chart II-16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood OF Robots? Japan: Where Is The Flood OF Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017): "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against The Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com 10 OECD Productivity Working Papers, No. 05 (2016): "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 27. III. Indicators And Reference Charts As we highlight in the Overview section, the earnings backdrop for the U.S. equity market remains very upbeat, as highlighted by the rise in the net earnings revisions and net earnings surprises indexes. Bottom-up analysts will likely continue to boost after-tax earnings estimates for the year as they adjust to the U.S. tax cut news. Our main concern is that a lot of good news is now discounted. Our Technical Indicator remains bullish, but our composite valuation indicator surpassed one sigma in January, which is our threshold of overvaluation. From these levels of overvaluation, the medium-term outlook for equity total returns is negligible. Our speculation index is at all-time highs and implied volatility is low, underscoring that investors are extremely bullish. From a contrary perspective, this is a warning sign for the equity market. Our Monetary Indicator has also moved further into 'bearish' territory for equities, although overall financial conditions remain positive for growth. It is also disconcerting that our Revealed Preference Indicator (RPI) shifted to a 'sell' signal for stocks, following five straight months on a 'buy' signal. This occurred because investors may be buying based on speculation rather than on a firm belief in the staying power of the underlying fundamentals. For now, though, our Willingness-to-Pay indicator for the U.S. rose sharply in January, highlighting that investor equity inflows are very strong and are favoring U.S. equities relative to Japan and the Eurozone. This is perhaps not surprising given the U.S. tax cuts just passed by Congress. The RPI indicators track flows, and thus provide information on what investors are actually doing, as opposed to sentiment indexes that track how investors are feeling. Our U.S. bond technical indicator shows that Treasurys are close to oversold territory, suggesting that we may be in store for a consolidation period following January's surge in yields. Treasurys are slightly cheap on our valuation metric, although not by enough to justify closing short duration positions. The U.S. dollar is oversold and due for a bounce. EQUITIES: Chart III-1U.S. Equity Indicators U.S. Equity Indicators U.S. Equity Indicators Chart III-2Willingness To Pay For Risk Willingness To Pay For Risk Willingness To Pay For Risk Chart III-3U.S. Equity Sentiment Indicators U.S. Equity Sentiment Indicators U.S. Equity Sentiment Indicators Chart III-4Revealed Preference Indicator Revealed Preference Indicator Revealed Preference Indicator Chart III-5U.S. Stock Market Valuation U.S. Stock Market Valuation U.S. Stock Market Valuation Chart III-6U.S. Earnings U.S. Earnings U.S. Earnings Chart III-7Global Stock Market And Earnings: ##br##Relative Performance Global Stock Market And Earnings: Relative Performance Global Stock Market And Earnings: Relative Performance Chart III-8Global Stock Market And Earnings: ##br##Relative Performance Global Stock Market And Earnings: Relative Performance Global Stock Market And Earnings: Relative Performance FIXED INCOME: Chart III-9U.S. Treasurys And Valuations U.S. Treasurys and Valuations U.S. Treasurys and Valuations Chart III-10U.S. Treasury Indicators U.S. Treasury Indicators U.S. Treasury Indicators Chart III-11Selected U.S. Bond Yields Selected U.S. Bond Yields Selected U.S. Bond Yields Chart III-1210-Year Treasury Yield Components 10-Year Treasury Yield Components 10-Year Treasury Yield Components Chart III-13U.S. Corporate Bonds And Health Monitor U.S. Corporate Bonds And Health Monitor U.S. Corporate Bonds And Health Monitor Chart III-14Global Bonds: Developed Markets Global Bonds: Developed Markets Global Bonds: Developed Markets Chart III-15Global Bonds: Emerging Markets Global Bonds: Emerging Markets Global Bonds: Emerging Markets CURRENCIES: Chart III-16U.S. Dollar And PPP U.S. Dollar And PPP U.S. Dollar And PPP Chart III-17U.S. Dollar And Indicator U.S. Dollar And Indicator U.S. Dollar And Indicator Chart III-18U.S. Dollar Fundamentals U.S. Dollar Fundamentals U.S. Dollar Fundamentals Chart III-19Japanese Yen Technicals Japanese Yen Technicals Japanese Yen Technicals Chart III-20Euro Technicals Euro Technicals Euro Technicals Chart III-21Euro/Yen Technicals Euro/Yen Technicals Euro/Yen Technicals Chart III-22Euro/Pound Technicals Euro/Pound Technicals Euro/Pound Technicals COMMODITIES: Chart III-23Broad Commodity Indicators Broad Commodity Indicators Broad Commodity Indicators Chart III-24Commodity Prices Commodity Prices Commodity Prices Chart III-25Commodity Prices Commodity Prices Commodity Prices Chart III-26Commodity Sentiment Commodity Sentiment Commodity Sentiment Chart III-27Speculative Positioning Speculative Positioning Speculative Positioning ECONOMY: Chart III-28U.S. And Global Macro Backdrop U.S. And Global Macro Backdrop U.S. And Global Macro Backdrop Chart III-29U.S. Macro Snapshot U.S. Macro Snapshot U.S. Macro Snapshot Chart III-30U.S. Growth Outlook U.S. Growth Outlook U.S. Growth Outlook Chart III-31U.S. Cyclical Spending U.S. Cyclical Spending U.S. Cyclical Spending Chart III-32U.S. Labor Market U.S. Labor Market U.S. Labor Market Chart III-33U.S. Consumption U.S. Consumption U.S. Consumption Chart III-34U.S. Housing U.S. Housing U.S. Housing Chart III-35U.S. Debt And Deleveraging U.S. Debt And Deleveraging U.S. Debt And Deleveraging Chart III-36U.S. Financial Conditions U.S. Financial Conditions U.S. Financial Conditions Chart III-37Global Economic Snapshot: Europe Global Economic Snapshot: Europe Global Economic Snapshot: Europe Chart III-38Global Economic Snapshot: China Global Economic Snapshot: China Global Economic Snapshot: China Mark McClellan Senior Vice President The Bank Credit Analyst

Highlights One of the biggest mistakes in finance is to equate risk with volatility. The correct measure of risk is the negative skew in payoff distributions. If 10-year bond yields should rise another 40 bps, equities would become riskier than bonds and elevated equity valuations would become much harder to sustain. This would be the point at which to scale back equity exposure. The corollary for bonds is that 10-year yields cannot sustainably rise more than 40bps before experiencing a tradeable reversal. Feature It is the crucial question that all investors should ask at all times. What is the relative risk of the two major asset classes - bonds and equities - and are their relative return prospects commensurate with the relative risk? Chart of the WeekBelow A 2% Yield, 10-Year Bonds Are Riskier Than Equities Are Bonds A Greater Risk Than Equities? Are Bonds A Greater Risk Than Equities? But first, there is an even more fundamental question: what do we mean by risk? Conventional wisdom says that the risk of an investment is captured by its volatility. Indeed, through instruments such as the VIX futures and currency volatility options, volatility has become a multi-trillion dollar asset-class in its own right. Therefore, volatility must measure the risk of an investment, right? Wrong. The Biggest Mistake In Finance As a measure of risk, volatility is clearly wrong. Volatility regards price gains in exactly the same way as it regards price losses. But investors don't mind gains, they only mind losses! Consider an investment whose price moves alternately sideways and sharply higher. The maths would say that the returns have high volatility, implying that the investment is very risky. In truth though, the investment is highly desirable and 'risk-free' - because its price never declines. At our recent New York conference, Nobel Laureate Daniel Kahneman warned that one of the biggest mistakes in finance is to equate risk with volatility. After decades of empirical and theoretical studies - which culminated in the 2002 Nobel Prize for Economics - Kahneman proved that investors are not concerned about the symmetrical fluctuations in investment returns. Instead, they are concerned about the asymmetry - or skew - in payoff distributions. Kahneman explained the underlying psychology. "People are limited in their ability to comprehend and evaluate extreme probabilities, so highly unlikely events are overweighted." If the payoff distribution is symmetric, the overweighting of unlikely events in the loss tail and the gain tail exactly cancels out. But if the distribution is asymmetric, the longer tail determines the perceived attractiveness of the payoff. Where the longer tail is on the gain side, the distribution is said to have positive skew (Figure I-1). The classic example is a lottery. When people play the lottery, their loss is limited to the ticket price, but their gain could be tens of millions. People perceive the positive skew as attractive because they overweight the minuscule probability of becoming a millionaire. As a result, they overpay for the lottery ticket versus its expected value. Where the longer tail is on the loss side, the distribution is said to have negative skew (Figure I-2). This is like a lottery in reverse. The gain size is relatively limited, but the loss could be very large. People perceive the negative skew as unattractive because they overweight the probability of a large loss. As a result, they demand overpayment to take it on. Figure I-1People Like Positive Skew Are Bonds A Greater Risk Than Equities? Are Bonds A Greater Risk Than Equities? Figure I-2People Dislike Negative Skew Are Bonds A Greater Risk Than Equities? Are Bonds A Greater Risk Than Equities? For investments with negative skew, this overpayment takes the form of an excess return demanded from the market - a 'risk premium' - versus investments with less negative skew. Are Bonds A Greater Risk Than Equities? We are now in a position to tackle the question in the title. To determine whether bonds are riskier than equities or vice-versa, we must compare the skews of their return profiles.1 The important point is that for a bond, the skew of its return profile changes with its yield. At yields above 2.5%, 10-year bond returns show no skew. Worst losses broadly equal best gains. However, when yields drop below 2%, returns start to exhibit negative skew (Chart I-2). And at yields below 1%, the negative skew becomes extreme. Chart I-2Bond Risk Increases At ##br##Low Bond Yields Are Bonds A Greater Risk Than Equities? Are Bonds A Greater Risk Than Equities? Chart I-3Equity Risk Does Not Increase At##br## Low Bond Yields Are Bonds A Greater Risk Than Equities? Are Bonds A Greater Risk Than Equities? The reason is obvious. Central banks accept that there is a 'lower bound' for policy interest rates - perhaps slightly negative - below which there would be an exodus of bank deposits. The limit also marks the lower bound for bond yields. Close to this lower bound for yields, bond mathematics necessarily creates a negatively skewed return profile. Simply put, prices have little upside, but they have a lot of downside! Chart I-4A 40Bps Rise In Yields Would Make Global ##br##Bonds Riskier Than Equities A 40Bps Rise In Yields Would Make Global Bonds Riskier Than Equities A 40Bps Rise In Yields Would Make Global Bonds Riskier Than Equities Turning to equities, the empirical evidence shows that equity returns always exhibit negative skew. Worst losses are typically around 1.5 times the size of best gains (Chart I-3). But the negative skew of equity returns is largely independent of the bond yield. The upshot is that there is a crossover bond yield below which the negative skew on 10-year bonds exceeds that on equities. This crossover bond yield is around 2%. In negative skew terms, we can say that at a 10-year bond yield below 2%, 10-year bonds are riskier than equities. And at a yield above 2%, equities are riskier than 10-year bonds (Chart of the Week). So in negative skew terms, 10-year bonds are riskier investments than equities in Europe and in Japan. But equities are riskier investments than 10-year bonds in the United States. Still, given that developed financial markets tend to move en masse, the relationship that is most significant is the aggregate one. At a global level, 10-year bond yields are 40bps below the crossover yield at which equities become riskier than bonds (Chart I-4). QE Distorted The Relative Valuation Of Equities Versus Bonds Which segues us neatly to today's ECB monetary policy meeting. Many people, worried about the end of QE, point out that the $10 trillion of bonds that the 'big four'2 central banks have bought is not far short of the size of the euro area economy. However, in the context of a global fixed income market of $220 trillion,3 $10 trillion of buying is small change. For the $220 trillion global bond and bank loan complex, the much more significant driver of yields has been the expected path of policy interest rates. As ECB Chief Economist Peter Praet put it, serial QE has been nothing more than "a signalling channel which reinforces the credibility of forward guidance on (ultra-low) policy rates." Chart I-5A Promise To Keep The Policy Rate Ultra-Low ##br##Pulls Down Bond Yields A Promise To Keep The Policy Rate Ultra-Low Pulls Down Bond Yields A Promise To Keep The Policy Rate Ultra-Low Pulls Down Bond Yields Central bankers know that QE depressed bond yields by signalling an extended period of ultra-low interest rates (Chart I-5). They also know that if the prospective return on bonds drops, so must the prospective return on competing investments such as equities. Thereby, the absolute valuations of bonds and equities both rise. However, one largely overlooked impact of QE - even by central bankers - has been the effect on the relative valuation of equities versus bonds. To repeat, when 10-year bond yields drop below 2%, their return distribution becomes more negatively skewed than that for equities. But if bonds become riskier investments, the 'risk premium' (excess return) on equities must disappear. Meaning equity valuations and prices get a second boost, compressing the prospective 10-year equity return to become 'bond-like'. Is this the case? Unlike for 10-year bonds, we do not know the 10-year prospective return from equities with certainty. However, we can get a good estimate from today's starting valuation. But which valuation metric to use? We are cautious of using profit based metrics as these will be flattered by the advanced position in the business cycle as well as the structural uptrend in profit margins. Instead, at an aggregate level, world equity market capitalisation to world GDP has been an excellent predictor of the prospective 10-year return on world equities. Today, this valuation metric is at the same level as in 2000 and 2007, and implies a prospective return of less than 2% a year (Chart I-6). Chart I-6World Equity Market Cap To GDP Implies A Feeble Prospective 10-Year Return World Equity Market Cap To GDP Implies A Feeble Prospective 10-Year Return World Equity Market Cap To GDP Implies A Feeble Prospective 10-Year Return Nevertheless, while the global 10-year bond yield stays below 2%, this is a sustainable valuation for equities. Effectively, equities and bonds are offering broadly similar negative skews, and therefore should offer broadly similar prospective returns. However, if 10-year bond yields should rise another 40 bps, equities would become riskier than bonds and elevated equity valuations would become much harder to sustain. Though not there yet, this would be the point when we would scale back equity exposure. The corollary for bonds is that 10-year yields cannot sustainably rise more than 40bps before experiencing a tradeable reversal. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com 1 One simple way to quantify this skew is to find an extended period of time in which the price ended where it started, and then to calculate the period's worst 3-month loss as a multiple of the best 3-month gain. We define skew = -ln(worst 3-month loss / best 3-month gain) using log returns for 3-month loss and 3-month gain. 2 The Federal Reserve, ECB, Bank of Japan and Bank of England. 3 Source: The Institute of International Finance (IIF) https://www.iif.com/publication/global-debt-monitor/global-debt-monitor-june-2017. Fractal Trading Model* This week's trade is to position for an underperformance of the Japanese energy sector (led by JXTG Holdings And Inpex) versus the overall Japanese market. This is a longer trade than normal with a maximum duration of 26 weeks. Set a profit-target at 8% with a symmetrical stop-loss. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment's fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-7 Short Japan Oil & Gas Short Japan Oil & Gas The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions. * For more details please see the European Investment Strategy Special Report "Fractals, Liquidity & A Trading Model," dated December 11, 2014, available at eis.bcaresearch.com Fractal Trading Model Recommendations Equities Bond & Interest Rates Currency & Other Positions Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch##br## - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations

Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. Technological advance in the past has not prevented improving living standards or led to ever rising joblessness over the decades, but pessimists argue that recent advances are different. The issue is important for financial markets. If structural factors such as automation are holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. We see no compelling evidence that the displacement effect of emerging technologies is any stronger than in the past. Robot usage has had a modest positive impact on overall productivity. Despite this contribution, overall productivity growth has been dismal over the past decade. If automation is increasing 'exponentially' and displacing workers on a broad scale as some claim, one would expect to see accelerating productivity growth, robust capital spending and more violent shifts in occupational shares. Exactly the opposite has occurred. Periods of strong growth in automation have historically been associated with robust, not lackluster, wage gains, contrary to the consensus view. The Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. This and other evidence suggest that it is difficult to make the case that robots will make it tougher for central banks to reach their inflation goals than did previous technological breakthroughs. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. Recent breakthroughs in technology are awe-inspiring and unsettling. These advances are viewed with great trepidation by many because of the potential to replace humans in the production process. Hype over robots is particularly shrill. Media reports warn of a "Robot Apocalypse" that is already laying waste to jobs and depressing wages on a broad scale. In the first in our series of Special Reports focusing on the structural factors that might be preventing central banks from reaching their inflation targets, we demonstrated that the impact of Amazon is overstated in the press. We estimated that E-commerce is depressing inflation in the U.S. by a mere 0.1 to 0.2 percentage points. This Special Report tackles the impact of automation. We are optimistic that robot technology and artificial intelligence will significantly boost future productivity, and thus reduce costs. But, is there any evidence at the macro level that robot usage has been more deflationary than technological breakthroughs in the past and is, thus, a major driver of the low inflation rates we observe today across the major countries? The question matters, especially for the outlook for central bank policy and the bond market. If structural factors are indeed holding back inflation by more than in previous decades, then the Fed will have to proceed very slowly in raising rates. However, if low inflation simply reflects long lags between wages and the tightening labor market, then inflation may suddenly lurch to life as it has at the end of past cycles. The bond market is not priced for that scenario. Are Robots Different? A Special Report from BCA's Technology Sector Strategy service suggested that the "robot revolution" could be as transformative as previous General Purpose Technologies (GPT), including the steam engine, electricity and the microchip.1 GPTs are technologies that radically alter the economy's production process and make a major contribution to living standards over time. The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks," and this encompasses a broad range of machines: From the Jacquard Loom, which was invented over 200 years ago, on to Numerically Controlled (NC) mills and lathes, pick and place machines used in the manufacture of electronics, Autonomous Vehicles (AVs), and even homicidal robots from the future such as the Terminator. Our Technology Sector report made the case that there is nothing particularly sinister about robots. They are just another chapter in a long history of automation. Nor is the displacement of workers unprecedented. The industrial revolution was about replacing human craft labor with capital (machines), which did high-volume work with better quality and productivity. This freed humans for work which had not yet been automated, along with designing, producing and maintaining the machinery. Agriculture offers a good example. This sector involved over 50% of the U.S. labor force until the late 1800s. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," contributed to a massive rise in output-per-man hour. The number of hours worked to produce a bushel of wheat fell by almost 98% from the mid-1800s to 1955. This put a lot of farm hands out of work, but these laborers were absorbed over time in other growing areas of the economy. It is the same story for all other historical technological breakthroughs. Change is stressful for those directly affected, but rising productivity ultimately lifts average living standards. Robots will be no different. As we discuss below, however, the increasing use of robots and AI may have a deeper and longer-lasting impact on inequality. Strong Tailwinds Chart II-1Robots Are Getting Cheaper Robots Are Getting Cheaper Robots Are Getting Cheaper Factory robots have improved immensely due to cheaper and more capable control and vision systems. As these systems evolve, the abilities of robots to move around their environment while avoiding obstacles will improve, as will their ability to perform increasingly complex tasks. Most importantly, robots are already able to do more than just routine tasks, thus enabling them to replace or aid humans in higher-skilled processes. Robot prices are also falling fast, especially after quality-adjusting the data (Chart II-1). Units are becoming easier to install, program and operate. These trends will help to reduce the barriers-to-entry for the large, untapped, market of small and medium sized enterprises. Robots also offer the ability to do low-volume "customized" production and still keep unit costs low. In the future, self-learning robots will be able to optimize their own performance by analyzing the production of other robots around the world. Robot usage is growing quickly according to data collected by the International Federation of Robotics (IFR) that covers 23 countries. Industrial robot sales worldwide increased to almost 300,000 units in 2016, up 16% from the year before (Chart II-2). The stock of industrial robots globally has grown at an annual average pace of 10% since 2010, reaching slightly more than 1.8 million units in 2016.2 Robot usage is far from evenly distributed across industries. The automotive industry is the major consumer of industrial robots, holding 45% of the total stock in 2016 (Chart II-3). The computer & electronics industry is a distant second at 17%. Metals, chemicals and electrical/electronic appliances comprise the bulk of the remaining stock. Chart II-2Global Robot Usage Global Robot Usage Global Robot Usage Chart II-3Global Robot Usage By Industry (2016) February 2018 February 2018 As far as countries go, Japan has traditionally been the largest market for robots in the world. However, sales have been in a long-term downtrend and the stock of robots has recently been surpassed by China, which has ramped up robot purchases in recent years (Chart II-4). Robot density, which is the stock of robots per 10 thousand employed in manufacturing, makes it easier to compare robot usage across countries (Chart II-5, panel 2). By this measure, China is not a heavy user of robots compared to other countries. South Korea stands at the top, well above the second-place finishers (Germany and Japan). Large automobile sectors in these three countries explain their high relative robot densities. Chart II-4Stock Of Robots By Country (I) Stock Of Robots By Country (I) Stock Of Robots By Country (I) Chart II-5Stock Of Robots By Country (II) (2016) February 2018 February 2018 While the growth rate of robot usage is impressive, it is from a very low base (outside of the automotive industry). The average number of robots per 10,000 employees is only 74 for the 23 countries in the IFR database. Robot use is tiny compared to total man hours worked. Chart II-6U.S. Investment In Robots U.S. Investment in Robots U.S. Investment in Robots In the U.S., spending on robots is only about 5% of total business spending on equipment and software (Chart II-6). To put this into perspective, U.S. spending on information, communication and technology (ICT) equipment represented 35-40% of total capital equipment spending during the tech boom in the 1990s and early 2000s.3 The bottom line is that there is a lot of hype in the press, but robots are not yet widely used across countries or industries. It will be many years before business spending on robots approaches the scale of the 1990s/2000s IT boom. A Deflationary Impact? As noted above, we view robotics as another chapter in a long history of technological advancements. Pessimists suggest that the latest advances are different because they are inherently more threatening to the overall job market and wage share of total income. If the pessimists are right, what are the theoretical channels though which this would have a greater disinflationary effect relative to previous GPT technologies? Faster Productivity Gains: Enhanced productivity drives down unit labor costs, which may be passed along to other industries (as cheaper inputs) and to the end consumer. More Human Displacement: The jobs created in other areas may be insufficient to replace the jobs displaced by robots, leading to lower aggregate income and spending. The loss of income for labor will simply go to the owners of capital, but the point is that the labor share of income might decline. Deflationary pressures could build as aggregate demand falls short of supply. Even in industries that are slow to automate, just the threat of being replaced by robots may curtail wage demands. Inequality: Some have argued that rising inequality is partly because the spoils of new technologies over the past 20 years have largely gone to the owners of capital. This shift may have undermined aggregate demand because upper income households tend to have a high saving rate, thereby depressing overall aggregate demand and inflationary pressures. The human displacement effect, described above, would exacerbate the inequality effect by transferring income from labor to the owners of capital. 1. Productivity It is difficult to see the benefits of robots on productivity at the economy-wide level. Productivity growth has been abysmal across the major developed countries since the Great Recession, but the productivity slowdown was evident long before Lehman collapsed (Chart II-7). The productivity slowdown continued even as automation using robots accelerated after 2010. Chart II-7Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Productivity Collapsed Despite Automation Some analysts argue that lackluster productivity is simply a statistical mirage because of the difficulties in measuring output in today's economy. We will not get into the details of the mismeasurement debate here. We encourage interested clients to read a Special Report by the BCA Global Investment Strategy service entitled "Weak Productivity Growth: Don't Blame The Statisticians." 4 Our colleague Peter Berezin makes the case that the unmeasured utility accruing from free internet services is large, but so was the unmeasured utility from antibiotics, radio, indoor plumbing and air conditioning. He argues that the real reason that productivity growth has slowed is that educational attainment has decelerated and businesses have plucked many of the low-hanging fruit made possible by the IT revolution. Cyclical factors stemming from the Great Recession and financial crisis are also to blame, as capital spending has been slow to recover in most of the advanced economies. Some other factors that help to explain the decline in aggregate productivity are provided in Appendix II-1. Nonetheless, the poor aggregate productivity performance does not mean that there are no benefits to using robots. The benefits are evident at the industrial level, where measurement issues are presumably less vexing for statisticians (i.e., it is easier to measure the output of the auto industry, for example, than for the economy as a whole). Chart II-8 plots the level of robot density in 2016 with average annual productivity growth since 2004 for 10 U.S. manufacturing industries (robot density is presented in deciles). A loose positive relationship is apparent. Chart II-8U.S.: Productivity Vs. Robot Density February 2018 February 2018 Academic studies estimate that robots have contributed importantly to economy-wide productivity growth. The Centre for Economic and Business Research (CEBR) estimated that labor productivity growth rises by 0.07 to 0.08 percentage points for every 1% rise in the rate of robot density.5 This implies that robots accounted for roughly 10% of the productivity growth experienced since the early 1990s in the major economies. Another study of 14 industries across 17 countries by the Centre for Economic Performance (CEP) found that robots boosted annual productivity growth by 0.36 percentage points over the 1993-2007 period.6 This is impressive because, if this estimate holds true for the U.S., robots' contribution to the 2½% average annual U.S. total productivity growth over the period was 14%. To put the importance of robotics into historical context, its contribution to productivity so far is roughly on par with that of the steam engine (Chart II-9). It falls well short of the 0.6 percentage point annual productivity contribution from the IT revolution. The implication is that, while the overall productivity performance has been dismal since 2007, it would have been even worse in the absence of robots. What does this mean for inflation? According to the "cost push" model of the inflation process, an increase in productivity of 0.36% that is not accompanied by associated wage gains would reduce unit labor costs (ULC) by the same amount. This should trim inflation if the cost savings are passed on to the end consumer, although by less than 0.36% because robots can only depress variable costs, not fixed costs. There indeed appears to be a slight negative relationship between robot density and unit labor costs at the industrial level in the U.S., although the relationship is loose at best (Chart II-10). Chart II-9GPT Contribution To Productivity February 2018 February 2018 Chart II-10U.S.: Unit Labor Costs Vs. Robot Density February 2018 February 2018 In theory, divergences in productivity across industries should only generate shifts in relative prices, and "cost push" inflation dynamics should only operate in the short term. Most economists believe that inflation is a purely monetary phenomenon in the long run, which means that central banks should be able to offset positive productivity shocks by lowering interest rates enough that aggregate demand keeps up with supply. Indeed, the Fed was successful in meeting the 2% inflation target on average from 2000 to 2007, when the impact of the IT revolution on productivity (and costs) was stronger than that of robot automation today. Also, note that inflation is currently low across the major advanced economies, irrespective of the level of robot intensity (Chart II-11). From this perspective, it is hard to see that robots should take much of the credit for today's low inflation backdrop. Chart II-11Inflation Vs. Robot Density February 2018 February 2018 2. Human Displacement A key question is whether robots and humans are perfect substitutes. If new technologies introduced in the past were perfect substitutes, then it would have led to massive underemployment and all of the income in the economy would eventually have migrated to the owners of capital. The fact that average real household incomes have risen over time, and that there has been no secular upward trend in unemployment rates over the centuries, means that new technologies were at least partly complementary with labor (i.e., the jobs lost as a direct result of productivity gains were more than replaced in other areas of the economy over time). Rather than replacing workers, in many cases tech made humans more productive in their jobs. Rising productivity lifted income and thereby led to the creation of new jobs in other areas. The capital that workers bring to the production process - the skills, know-how and special talents - became more valuable as interaction with technology increased. Like today, there were concerns in the 1950s and 1960s that computerization would displace many types of jobs and lead to widespread idleness and falling household income. With hindsight, there was little to worry about. Some argue that this time is different. Futurists frequently assert that the pace of innovation is not just accelerating, it is accelerating 'exponentially'. Robots can now, or will soon be able to, replace humans in tasks that require cognitive skills. This means that they will be far less complementary to humans than in the past. The displacement effect could thus be much larger, especially given the impressive advances in artificial intelligence. However, Box II-1 discusses why the threat to workers posed by AI is also heavily overblown in the media. The CEP multi-country study cited above did not find a large displacement effect; robot usage did not affect the overall number of hours worked in the 23 countries studied (although it found distributional effects - see below). In other words, rather than suppressing overall labor input, robot usage has led to more output, higher productivity, more jobs and stronger wage and income growth. A report by the Economic Policy Institute (EPI)7 takes a broader look at automation, using productivity growth and capital spending as proxies. Automation is what occurs as the implementation of new technologies is incorporated along with new capital equipment or software to replace human labor in the workplace. If automation is increasing 'exponentially' and displacing workers on a broad scale, one would expect to see accelerating productivity growth, robust capital spending, and more violent shifts in occupational shares. Exactly the opposite has occurred. Indeed, the report demonstrates that occupational employment shifts were far slower in the 2000-2015 period than in any decade in the 1900s (Chart II-12). Box II-1 The Threat From AI Is Overblown Media coverage of AI/Deep Learning has established a consensus view that we believe is well off the mark. A recent Special Report from BCA's Technology Sector Strategy service dispels the myths surrounding AI.8 We believe the consensus, in conjunction with warnings from a variety of sources, is leading to predictions, policy discussions, and even career choices based on a flawed premise. It is worth noting that the most vocal proponents of AI as a threat to jobs and even humanity are not AI experts. At the root of this consensus is the false view that emerging AI technology is anything like true intelligence. Modern AI is not remotely comparable in function to a biological brain. Scientists have a limited understanding of how brains work, and it is unlikely that a poorly understood system can be modeled on a computer. The misconception of intelligence is amplified by headlines claiming an AI "taught itself" a particular task. No AI has ever "taught itself" anything: All AI results have come about after careful programming by often PhD-level experts, who then supplied the system with vast amounts of high quality data to train it. Often these systems have been iterated a number of times and we only hear of successes, not the failures. The need for careful preparation of the AI system and the requirement for high quality data limits the applicability of AI to specific classes of problems where the application justifies the investment in development and where sufficient high-quality data exists. There may be numerous such applications but doubtless many more where AI would not be suitable. Similarly, an AI system is highly adapted to a single problem, or type of problem, and becomes less useful when its application set is expanded. In other words, unlike a human whose abilities improve as they learn more things, an AI's performance on a particular task declines as it does more things. There is a popular misconception that increased computing power will somehow lead to ever improving AI. It is the algorithm which determines the outcome, not the computer performance: Increased computing power leads to faster results, not different results. Advanced computers might lead to more advanced algorithms, but it is pointless to speculate where that may lead: A spreadsheet from 2001 may work faster today but it still gives the same answer. In any event, it is worth noting that a tool ceases to be a tool when it starts having an opinion: there is little reason to develop a machine capable of cognition even if that were possible. Chart II-12U.S. Job Rotation Has Slowed February 2018 February 2018 The EPI report also notes that these indicators of automation increased rapidly in the late 1990s and early 2000s, a period that saw solid wage growth for American workers. These indicators weakened in the two periods of stagnant wage growth: from 1973 to 1995 and from 2002 to the present. Thus, there is no historical correlation between increases in automation and wage stagnation. Rather than automation, the report argues that it was China's entry into the global trading system that was largely responsible for the hollowing out of the U.S. manufacturing sector. We have also made this argument in previous research. The fact that the major advanced economies are all at, or close to, full employment supports the view that automation has not been an overwhelming headwind for job creation. Chart II-13 demonstrates that there has been no relationship between the change in robot density and the loss of manufacturing jobs since 1993. Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. Interestingly, despite a worsening labor shortage, robot density among Japanese firms is falling. Moreover, the Japanese data show that the industries that have a high robot usage tend to be more, not less, generous with wages than the robot laggard industries. Please see Appendix II-2 for more details. Chart II-13Global Manufacturing Jobs Vs. Robot Density February 2018 February 2018 The bottom line is that it does not appear that labor displacement related to automation has been responsible in any meaningful way for the lackluster average real income growth in the advanced economies since 2007. 3. Inequality That said, there is evidence suggesting that robots are having important distributional effects. The CEP study found that robot use has reduced hours for low-skilled and (to a lesser extent) middle-skilled workers relative to the highly skilled. This finding makes sense conceptually. Technological change can exacerbate inequality by either increasing the relative demand for skilled over unskilled workers (so-called "skill-biased" technological change), or by inducing companies to substitute machinery and other forms of physical capital for workers (so-called "capital-biased" technological change). The former affects the distribution of labor income, while the latter affects the share of income in GDP that labor receives. A Special Report appearing in this publication in 2014 focused on the relationship between technology and inequality.9 The report highlighted that much of the recent technological change has been skill-biased, which heavily favors workers with the talent and education to perform cognitively-demanding tasks, even as it reduces demand for workers with only rudimentary skills. Moreover, technological innovations and globalization increasingly allow the most talented individuals to market their skills to a much larger audience, thus bidding up their wages. The evidence suggests that faster productivity growth leads to higher average real wages and improved living standards, at least over reasonably long horizons. Nonetheless, technological change can, and in the future almost certainly will, increase income inequality. The poor will gain, but not as much as the rich. The fact that higher-income households tend to maintain a higher savings rate than low-income households means that the shift in the distribution of income toward the higher-income households will continue to modestly weigh on aggregate demand. Can the distribution effect be large enough to have a meaningful depressing impact on inflation? We believe that it has played some role in the lackluster recovery since the Great Recession, with the result that an extended period of underemployment has delivered a persistent deflationary impulse in the major developed economies. However, as discussed above, stimulative monetary policy has managed to overcome the impact of inequality and other headwinds on aggregate demand, and has returned the major countries roughly to full employment. Indeed, this year will be the first since 2007 that the G20 economies as a group will be operating slightly above a full employment level. Inflation should respond to excess demand conditions, irrespective of any ongoing demand headwind stemming from inequality. Conclusions Technological change has led to rising living standards over the decades. It did not lead to widespread joblessness and did not prevent central banks from meeting their inflation targets over time. The pessimists argue that this time is different because robots/AI have a much larger displacement effect. Perhaps it will be 20 years before we will know the answer. But our main point is that we have found no evidence that recent advances in robotics and AI, while very impressive, will be any different in their macro impact. There is little evidence that the modern economy is less capable in replacing the jobs lost to automation, although the nature of new technologies may be affecting the distribution of income more than in the past. Real incomes for the middle- and lower-income classes have been stagnant for some time, but this is partly due to productivity growth that is too low, not too high. Moreover, it is not at all clear that positive productivity shocks are disinflationary beyond the near term. The link between robot usage and unit labor costs over the past couple of decades is loose at best at the industry level, and is non-existent when looking across the major countries. The Fed was able to roughly meet its 2% inflation target in the 1990s and the first half of the 2000s, despite IT's impressive contribution to productivity growth during that period. For investors, this means that we cannot rely on automation to keep inflation depressed irrespective of how tight labor markets become. The global output gap will shift into positive territory this year for the first time since the Great Recession. Any resulting rise in inflation will come as a shock since the bond market has discounted continued low inflation for as far as the eye can see. We expect bond yields and implied volatility to rise this year, which may undermine risk assets in the second half. Mark McClellan Senior Vice President The Bank Credit Analyst Brian Piccioni Vice President Technology Sector Strategy Appendix II-1 Why Is Productivity So Low? A recent study by the OECD10 reveals that, while frontier firms are charging ahead, there is a widening gap between these firms and the laggards. The study analyzed firm-level data on labor productivity and total factor productivity for 24 countries. "Frontier" firms are defined to be those with productivity in the top 5%. These firms are 3-4 times as productive as the remaining 95%. The authors argue that the underlying cause of this yawning gap is that the diffusion rate of new technologies from the frontier firms to the laggards has slowed within industries. This could be due to rising barriers to entry, which has reduced contestability in markets. Curtailing the creative-destruction process means that there is less pressure to innovate. Barriers to entry may have increased because "...the importance of tacit knowledge as a source of competitive advantage for frontier firms may have risen if increasingly complex technologies were to increase the amount and sophistication of complementary investments required for technological adoption." 11 The bottom line is that aggregate productivity is low because the robust productivity gains for the tech-savvy frontier companies are offset by the long tail of firms that have been slow to adopt the latest technology. Indeed, business spending has been especially weak in this expansion. Chart II-14 highlights that the slowdown in U.S. productivity growth has mirrored that of the capital stock. Chart II-14U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity U.S. Capex Shortfall Partly To Blame For Poor Productivity Appendix II-2 Japan - The Leading Edge Japan is an interesting case study because it is on the leading edge of the problems associated with an aging population. The popular press is full of stories of how robots are taking over. If the stories are to be believed, robots are the answer to the country's shrinking workforce. Robots now serve as helpers for the elderly, priests for weddings and funerals, concierges for hotels and even sexual partners (don't ask). Prime Minister Abe's government has launched a 5-year push to deepen the use of intelligent machines in manufacturing, supply chains, construction and health care. Indeed, Japan was the leader in robotics use for decades. Nonetheless, despite all the hype, Japan's stock of industrial robots has actually been eroding since the late 1990s (Chart II-4). Numerous surveys show that firms plan to use robots more in the future because of the difficulty in hiring humans. And there is huge potential: 90% of Japanese firms are small- and medium-sized (SME) and most are not currently using robots. Yet, there has been no wave of robot purchases as of 2016. One problem is the cost; most sophisticated robots are simply too expensive for SMEs to consider. This suggests that one cannot blame robots for Japan's lack of wage growth. The labor shortage has become so acute that there are examples of companies that have turned down sales due to insufficient manpower. Possible reasons why these companies do not offer higher wages to entice workers are beyond the scope of this report. But the fact that the stock of robots has been in decline since the late 1990s does not support the view that Japanese firms are using automation on a broad scale to avoid handing out pay hikes. Indeed, Chart II-15 highlights that wage deflation has been the greatest in industries that use almost no robots. Highly automated industries, such as Transportation Equipment and Electronics, have been among the most generous. This supports the view that the productivity afforded by increased robot usage encourages firms to pay their workers more. Looking ahead, it seems implausible that robots can replace all the retiring Japanese workers in the years to come. The workforce will shrink at an annual average pace of 0.33% between 2020 and 2030, according to the Japan Institute for Labour Policy and Training. Productivity growth would have to rise by the same amount to fully offset the dwindling number of workers. But that would require a surge in robot density of 4.1, assuming that each rise in robot density of one adds 0.08% to the level of productivity (Chart II-16). The level of robot sales would have to jump by a whopping 2½ times in the first year and continue to rise at the same pace each year thereafter to make this happen. Of course, the productivity afforded by new robots may accelerate in the coming years, but the point is that robot usage would likely have to rise astronomically to offset the impact of the shrinking population. Chart II-15Japan: Earnings Vs. Robot Density February 2018 February 2018 Chart II-16Japan: Where Is The Flood Of Robots? Japan: Where Is The Flood OF Robots? Japan: Where Is The Flood OF Robots? The implication is that, as long as the Japanese economy continues to grow above roughly 1%, the labor market will continue to tighten and wage rates will eventually begin to rise. 1 Please see Technology Sector Strategy Special Report "The Coming Robotics Revolution," dated May 16, 2017, available at tech.bcaresearch.com 2 Note that this includes only robots used in manufacturing industry, and thus excludes robots used in the service sector and households. However, robot usage in services is quite limited and those used in households do not add to GDP. 3 Note that ICT investment and capital stock data includes robots. 4 Please see BCA Global Investment Strategy Special Report "Weak Productivity Growth: Don't Blame The Statisticians," dated March 25, 2016, available at gis.bcaresearch.com 5 Centre for Economic and Business Research (January 2017): "The Impact of Automation." A Report for Redwood. In this report, robot density is defined to be the number of robots per million hours worked. 6 Graetz, G., and Michaels, G. (2015): "Robots At Work." CEP Discussion Paper No 1335. 7 Mishel, L., and Bivens, J. (2017): "The Zombie Robot Argument Lurches On," Economic Policy Institute. 8 Please see BCA Technology Sector Strategy Special Report "Bad Information - Why Misreporting Deep Learning Advances Is A Problem," dated January 9, 2018, available at tech.bcaresearch.com 9 Please see The Bank Credit Analyst, "Rage Against The Machines: Is Technology Exacerbating Inequality?" dated June 2014, available at bca.bcaresearch.com 10 OECD Productivity Working Papers, No. 05 (2016): "The Best Versus the Rest: The Global Productivity Slowdown, Divergence Across Firms and the Role of Public Policy." 11 Please refer to page 27.

Highlights While bullish sentiment for copper remains high, concerns that policymakers' attempts at a managed slowdown in China this year goes too far will weigh on the market. Fundamentally, support for copper prices from potential supply shortfalls at both the mining and refining levels will be offset by a stronger USD and slower growth in China this year (Chart of the Week). Despite our expectation a slight physical supply deficit will emerge this year, we remain neutral copper. We do not believe this will be enough to rally prices in a meaningful way. Energy: Overweight. Ministers from Saudi Arabia and Russia confirmed OPEC 2.0 - the oil-producer coalition led by these states - will survive beyond the expiry of their production-management deal at the end of this year. What and how they will manage the production of coalition members, however, remains unknown. Base Metals: Neutral. Positive fundamentals for copper are at risk if the USD rallies on the back of Fed tightening this year or China's managed economic slowdown is too severe (see below). Precious Metals: Neutral. Gold prices remained well bid, despite expectations for three or four Fed rate hikes this year, suggesting the market is pricing in either fewer rate hikes and lower real rates, or geopolitical risk - most prominently in Venezuela or North Korea. We remain long gold as a strategic portfolio hedge. Ags/Softs: Underweight. Soybean has been gaining ground on concerns about yield damage due to droughts in parts of Argentina. Expectations of a bumper year for Brazil will mitigate the impact on global supply. Feature Bullish copper sentiment is at a multi-year high, with four bulls for every bear in the market (Chart 2). The strong global economy, weak USD, and elevated risk of further supply-side disruptions - at mines as well as at the refining level - are feeding into buyers' optimism. Chart of the WeekChina Fears Weighing##BR##On Copper Prices China Fears Weighing On Copper Prices China Fears Weighing On Copper Prices Chart 2Bullish Sentiment Remains##BR##At Multi-Year Highs Bullish Sentiment Remains At Multi-Year Highs Bullish Sentiment Remains At Multi-Year Highs Our outlook for 2018 calls for another, albeit smaller, refined copper deficit (Chart 3). This will come on the back of escalated risks from supply side disruptions at mines in Chile and Peru, and potential constraints on primary and secondary refined output from China, the largest refined copper producer (Table 1). Chart 3A (Smaller) Deficit##BR##In 2018 A (Smaller) Deficit In 2018 A (Smaller) Deficit In 2018 Table 1China Is Significant For##BR##Copper Supply And Demand Stronger USD, Slower China Growth Threaten Copper Stronger USD, Slower China Growth Threaten Copper China also is the world's largest refined-copper consumer, which makes the risk of a more severe downturn in China arising from too much policy-driven restraint in the metal's top consumer acute. In the following sections, we present our expectations for the fundamentals: copper mine output, refined copper production, and refined copper consumption. Industrial Action Will Threaten Mine Output Again In 2018 Copper had an exceptional year in 2017. The synchronized global upturn and weak USD set the stage for a memorable performance. On the supply-side, disruptions at some of the world's largest mines pushed prices up 8% in 1H17. Although the risk of further production shocks had subsided by 2H17, copper gained another 22% on the back of restrictive Chinese scrap import policies and better than expected demand fundamentals. Last year, the copper market registered a physical deficit, mainly on the back of a decline in copper mine supply. A 0.3% yoy fall in copper ores and concentrate output in the first eleven months of the year kept production broadly unchanged compared to the same period last year. In fact, this was the first yoy decline for that period since 2002, and contrasts with an average 5% expansion in ore and concentrate output for that period since 2012 (Chart 4). The most notable supply side disruptions last year were: Chart 4Supply Disruptions Put##BR##Copper In Deficit Last Year Supply Disruptions Put Copper In Deficit Last Year Supply Disruptions Put Copper In Deficit Last Year A 9% yoy decline in output from top producer Chile in 1H17. Chile accounts for more than a quarter of global ore & concentrate supply. The decline is a result of strikes at the Escondida mine as well as lower output from Codelco mines. The Indonesian government's ban on exports of copper ores in the first four months of the year led to a 6% yoy decline in production in the first eleven months. U.S. output, which accounts for~7% of global copper ores & concentrates supply is down 12% yoy in the first eleven months of 2017. In fact, the last time the U.S. recorded a positive yoy growth rate was in October 2016. The decline in U.S. output came mainly on the back of lower grade ores, a fall in mining rates, and poor weather conditions. The majority of these disruptions occurred in 1H17 - the first five months of the year witnessed a 1.6% yoy fall in output, while the Jun-Oct period experienced a 0.7% yoy increase. Nonetheless, the ramp up in second part of the year is significantly slower than the 6% yoy and 5% yoy increases in the same period in 2015 and 2016. Global supply was partially supported by Peruvian and European production. Peruvian output grew 3.6% yoy in the first eleven months of the year. However this rate is dwarfed in comparison to previous years. Output grew almost 40% yoy in 2016 and 23% yoy in 2015. Similarly, European output - which accounts for 8% of global supply - seems to be continuing its uptrend. It expanded by 2.4% in the first eleven months of 2017 to record the highest level of output for that period. In fact, growth in output is above the average 0.8% yoy pace in the same period in 2014-2016. We expect a small rebound in mine production in 2018. According to the International Copper Study Group, temporarily shut down capacity in the Democratic Republic of Congo (DRC) and Zambia will resume operations, supporting mine supply this year. Supply-side disruptions pose a significant risk to mine supply again this year. An estimated more than 30 labor contracts, representing ~5mm MT of mined copper - a quarter of global production - will expire this year.1 While surely not all of these negotiations will result in strikes and supply disruptions, the figure is noteworthy as it is significantly above the average 1.7mm MT worth of annual copper supply at risk from contract renewal between 2011 and 2016. The most significant of these renewals is that which was most damaging last year. The 44-day strike at BHP Billiton's Escondida mine in Chile last year, which resulted in a 7.8% yoy fall at the world's most productive copper mine, ended without agreement. Although the contracts were extended, they are due for renegotiation in June. In fact, one of the unions at Escondida held a day long "warning strike" in November, an indication that they do not intend to back down from their demands. Unless management gives in, this implies a heightened risk of disruptions. Bottom Line: Supply disruptions negatively impacted mine supply in some of the world's top producers in 1H17. Although European and Peruvian supply has been somewhat supportive, global supply stagnated in 2017. Industrial action remains the major risk to mined copper this year. 5mm MT worth of copper ores and concentrates are at risk of supply side disruptions in 2018 - the highest figure since 2010. Environmental Reforms Limit Refined Production From China Chart 5China's Scrap Imports Cushion##BR##Against High Prices China's Scrap Imports Cushion Against High Prices China's Scrap Imports Cushion Against High Prices World refined production grew 1.3% yoy in the first eleven months of 2017, the slowest growth rate for that period since 2009. This reflects significant declines in refined copper production in Chile and the U.S. Supply disruptions at mines in Chile - the world's second-largest producer of refined copper - led to a 182k MT fall in refined output in the first eleven months of 2017, compared to the same period in 2016. Refined output from the U.S. fell by 91.4k MT in that period. However, the downside pressure on refined output from lower ore production was mitigated by increased secondary production from scrap, which accounts for ~20% of global refined copper production. Chinese copper producers took advantage of the oversupply in global scrap and ramped up their production. According to the ICSG global secondary output expanded by almost 10% yoy in the first ten months of last year. China's copper scrap imports increased 9% yoy in the first eleven months of last year, following four years of declines (Chart 5). China makes up less than 10% of global mined copper, but it is the largest producer of refined copper in the world, accounting for 36% of the global production. China is expected to remain the main contributor to world refined production growth (Chart 6). However, Beijing's environmental reforms, and measures to curb the imports of "foreign trash" will limit secondary refined production. Chart 6China Remains Most Significant Factor In Refined Production Growth Stronger USD, Slower China Growth Threaten Copper Stronger USD, Slower China Growth Threaten Copper New policies affecting refined output in China are supportive of copper prices this year: 1. In relation to scrap copper, Beijing recently imposed two policy changes, in line with its environmental reforms. First, since the start of 2018, only copper scrap end-users and processors will be granted import licenses. Second, a proposal to limit the hazardous impurity levels in scrap copper imports to 1% by March. Both these policies will curtail China's scrap copper imports. China imports an estimated 3mm MT of scrap copper annually, accounting for roughly half of its total scrap copper supply. Such limitations would severely dent China's scrap supply. Furthermore, scrap copper imports play a significant role in China. They act as a buffer against high prices, soaring during periods of high prices and dwindling when prices are low - as they were between 2013 and 2016. If China does in fact go through with the tighter regulations on scrap imports, Chinese copper consumers would not be able to fall back on the secondary metal when prices rise - as they have been over the past year - leading to greater demand for imports of primary products, chasing prices higher. However, over the long term, we are likely to see Chinese scrap traders move their businesses offshore, notably in Southeast Asia, where they will process the scrap until it meets the regulations necessary to be imported by China.2 In fact, this has already started to happen in the case of the category 7 scrap - derived from end-of-life electronics, households, cars and industrial products - which is widely believed will be banned by year-end. Nevertheless, these recycling plants do not yet exist. Thus, the transition cannot occur overnight, and we expect the tighter policies on scrap imports to support prices in the interim as China increases its imports of ores and refined copper in order to fill the supply gap. 2. China's environmental reforms also pose a risk on refined supply this year. Smelters and refiners risk being shut down if they do not comply with tighter pollution controls. This could limit copper output this year. Similar to the winter production cuts occurring at steel and aluminum producers, China's second largest copper smelter - Tongling Nonferrous Metals Group - announced plans to reduce its smelter capacity by up to 30% during the winter.3 In addition, late last month, China's largest smelter - Jiangxi Copper Co. - was forced to curb output while local pollution levels were assessed.4 The extent to which these measures are adopted by other producers will interrupt refined output this year. Given the more elevated pollution levels during the winter months, this risk is most notable in the November to March period. Bottom Line: The major risk to refined copper supply is China's environmental reforms which will likely constrain copper scrap imports, and could lead to temporary shutdowns of polluting smelters and refineries. If Beijing tightens these regulations, we are likely to witness disruptions in both primary and secondary refined output, while the copper supply chain readjusts to be able to comply with these policies. Slowdown In China Would Temper Copper World refined copper consumption grew 0.8% yoy in the first eleven months of 2017. Weaker consumption was mainly in the 1H17, during which global consumption fell 1.8% yoy, whereas consumption in the July-to-November period accelerated by 3.9% yoy. Weaker demand in the first half of the year came on the back of weaker demand from China, which accounts for half of global consumption. China recorded a 7.7% yoy fall in consumption of refined copper in the January-to-April period. However, Chinese copper demand subsequently strengthened, accelerating by 7.4% yoy in the May-to-November period. While demand from the rest of the world muted the impact of weaker Chinese consumption in the first half of the year, it weakened in the second half of the year, falling 3.3% yoy in the May-to-October period. This fall in copper demand was driven by a 5.5% yoy fall in the U.S., and to a lesser extent, a 2.0% yoy fall in demand in Japan in the May-to-November period. According to China Customs data, China's refined copper imports fell 5.1% in 2017 after growing 3.7% in 2016 (Chart 7). However, what is noteworthy is that while imports fell 18.3% yoy in H1, they picked up in H2, increasing by 11.3% yoy, mainly on the back of strong demand in Q3. This is in line with strong economic performance in China in 2H17 - an upside surprise which supported copper prices. Going into 2018, we expect a managed deceleration in China - and in China's demand for copper - to be mitigated by stronger demand from the rest of the world. In fact, the IMF revised up its 2018 and 2019 global growth forecasts in the latest WEO Update earlier this week (Table 2). Global growth is now forecast to reach 3.9% in 2018, up from the estimated 3.7% last year. Chart 7China's Q4 Imports Were Strong China's Q4 Imports Were Strong China's Q4 Imports Were Strong Table 2Upward Revisions To IMF Growth Projections Stronger USD, Slower China Growth Threaten Copper Stronger USD, Slower China Growth Threaten Copper Chart 8Speed Bump Ahead For China? Speed Bump Ahead For China? Speed Bump Ahead For China? That said, our China construction Indicator - which includes several variables measuring construction activity in China - shows strong growth in the main end-user for copper (Chart 8). Given that building construction accounts for 43% of copper end-use in China, this indicates demand for copper should remain healthy in the near term. Furthermore, despite concerns of a slowdown, China's manufacturing PMI still points to a healthy economy. Even so, a decline in the Li Keqiang Index, which tracks industrial activity, warrants caution and could be signaling trouble ahead for the Chinese economy. In addition, government spending has decelerated significantly from its mid-2017 peak. Against these risks, the global economy is expected to remain strong. Thus the biggest risk to our assessment is a pronounced deceleration in China which would hit demand for the red metal. Bottom Line: The major risk to refined copper demand this year is a slowdown from China. Downside Risk From A Stronger USD In addition to the fundamental variables highlighted above, U.S. monetary policy - and its effect on the USD - will also be an important driver of the copper market. We expect the Fed to embark on its interest rate normalization process more aggressively this year, hiking its policy rate up to four times. This would see copper prices weaken as the red metal becomes more expensive in USD terms. The USD is significant because a weaker dollar means that dollar-based commodities are cheaper for foreign buyers. Thus, foreigners tend to buy dollar-denominated commodities when the USD is weak, and sell when the USD is strong, in order to also benefit from exchange rate differentials. Continued weakness of the USD has been supportive of copper prices since the beginning of 2017. A risk to our outlook is an unexpectedly dovish Fed, which would keep the dollar muted and be favorable to copper. Bottom Line: We expect the copper market to record a small physical deficit this year. A stronger USD and deceleration in China will prevent a repeat of 2017's performance. However supply side disruptions at the mine and refined levels will provide opportunities for some upside in the market. Synchronized global demand will be a tailwind throughout the year. In the near term, we expect copper to continue gyrating around its current level of $3.10/lb. Absent a marked slowdown in China, we expect a rally into mid-year as contract renegotiations get underway. Roukaya Ibrahim, Associate Editor Commodity & Energy Strategy RoukayaI@bcaresearch.com Hugo Bélanger, Research Analyst HugoB@bcaresearch.com 1 Please see "Copper soars to 4-year high as funds bet on shortages," dated December 28, 2017, available at reuters.com. 2 Please see "As China restricts scrap metal companies look to process copper abroad," dated January 8, 2018, available at reuters.com. 3 Please see "Chinese Copper Smelter Halts Capacity to Ease Winter Pollution," dated December 7, 2017, available at Bloomberg.com. 4 Please see "Copper Rallies to Three-Year High as China Plant Halts Output," dated December 26, 2017, available at Bloomberg.com. Investment Views and Themes Recommendations Strategic Recommendations Tactical Trades Commodity Prices and Plays Reference Table Stronger USD, Slower China Growth Threaten Copper Stronger USD, Slower China Growth Threaten Copper Trades Closed in 2018 Summary of Trades Closed in 2017 Stronger USD, Slower China Growth Threaten Copper Stronger USD, Slower China Growth Threaten Copper

Highlights Global Duration Strategy: Global bond yields continue to move higher, driven by rising inflation expectations and falling investor risk aversion. With global interest rates still not at levels that will restrict growth or draw capital away from booming equity markets, the path of least resistance for yields remains upward. Maintain a below-benchmark overall portfolio duration stance, with a bearish curve steepening bias in the U.S. and core Europe. U.K. Gilts: The momentum in the U.K. economy is slowing, as a weaker consumer, slower housing activity, and softer capital spending are offsetting a pickup in exports. With the inflationary impulse from the 2016 plunge in the Pound now fading, and with Brexit uncertainty weighing on business confidence, the Bank of England will struggle to raise rates in 2018. Stay overweight Gilts. Feature Revisiting Our Duration Strategy After The Rise In Yields Global government bond markets have started 2018 in a grumpy mood. The price return on the overall Barclays Global Treasury index is already down -0.6% so far in January, and yields are up for almost every country and maturity bucket within the developed market universe. Only longer-dated Peripheral European debt (Italy, Spain, Portugal, even Greece) has seen lower yields month-to-date, as the powerful growth upturn in the Euro Area has resulted in sovereign credit upgrades and narrowing spreads to core European bonds. The global sell-off has been led by the U.S., with the benchmark 10-year U.S. Treasury yield climbing all the way to 2.66% last week, already surpassing the 2016 high seen last March. Rising inflation expectations are the biggest culprit, with the 10-year TIPS breakeven rate climbing to 2.07%, the highest level since 2014. Chart of the WeekNo Good News For Bonds Right Now No Good News For Bonds Right Now No Good News For Bonds Right Now The relentless surge in global stock markets - driven by faster worldwide economic growth and an absence of volatility - is also helping fuel the bearishness in government bond markets. The economic growth momentum is showing no signs of abating. The IMF just raised its global growth forecast for both 2018 and 2019 to 3.9% in both years - the fastest pace since 2011 - largely because of the impact of the U.S. tax cuts but also because of much faster expected growth in Europe.1 The IMF noted that "the cyclical rebound could prove stronger in the near term as the pickup in activity and easier financial conditions reinforce each other." We could not agree more. With robust growth pushing a majority of economies to operate beyond full employment, and with financial conditions remaining highly accommodative, global bond markets are now pricing in both higher inflation expectations and less accommodative monetary policy (Chart of the Week). While we only expect actual rate increases in the U.S. and Canada in 2018, the pressures on global central banks to respond to the coordinated growth upturn with hawkish talk will keep government bond markets on the defensive - especially if global inflation rates are moving up at the same time. Diminishing demand for government bonds from recently reliable sources may also act to push up yields in the months ahead. A reduced pace of asset purchases from the European Central Bank (ECB) and Bank of Japan (BoJ), combined with the Fed reducing the reinvestments of its maturing Treasury holdings, means that the private sector must now absorb a greater share of bond issuance, on the margin. In the U.S. in particular, the biggest swing factor for the Treasury market could end up being the retail investor. Households have been notably risk-averse in the years since the Great Financial Crisis, keeping relatively high allocations to fixed income and relatively low allocations to equities after suffering such steep losses in the 2008 crash. Those attitudes are changing, however, with the U.S. equity market continuing to hit new all-time highs amid increased media coverage of the rally (as well as the bullish Tweets from the White House taking credit for it). The latest University of Michigan U.S. consumer confidence survey showed that the expected probability of another year of rising stock prices is now at the highest level (66%) in the fifteen years that question was asked. U.S. investment advisors are also very optimistic, with the Investors' Intelligence bull/bear ratio back to the highest level since 1987! (Chart 2) Yet actual equity returns over the past three years have lagged those seen during periods of elevated investor sentiment, like in 1987, 2005 and 2014 (Chart 2). What is missing now is a big surge of retail investor money into equities that can fuel the next leg of the equity rally, particularly through mutual funds and ETFs. Chart 2The Bond-Bearish Equity Party##BR##Is Just Getting Started The Bond-Bearish Equity Party Is Just Getting Started The Bond-Bearish Equity Party Is Just Getting Started This is starting to happen. The rolling 12-month total of net flows into U.S. equity mutual funds and ETFs is about to accelerate into positive territory for the first time since 2012, according to data from the Investment Company Institute (3rd panel). This could soon pose a problem for U.S. bond markets as, since 2008, there has been a reliable negative correlation between U.S. retail flows into equity funds and flows into fixed income funds, especially at major turning points (bottom panel). For example, after that 2012 bottom in net equity flows, the rolling total of net flows into bond funds collapsed from over $400bn to zero in a span of 18 months, with the vast majority of the outflow from bonds going into equities. An exodus of U.S. retail investors from fixed income would be a major problem for bond markets, especially at a time when net Treasury issuance is expected to increase due to wider fiscal deficits and the Fed will be buying fewer bonds as it begins to unwind its massive balance sheet. Other buyers like commercial banks and global reserve fund managers can pick up some of the slack if the retail bid fades from U.S. Treasuries. However, in an environment of strong global growth, rising inflation and more hawkish central banks, it may require higher yields to entice those buyers to ramp up their allocations. In the near-term, the next wave of global bond-bearish news will have to come from upside surprises in inflation, not growth. The Citi Global Economic Data Surprise index - which has historically correlated with swings in global bond yields - is now at elevated levels which should raise the odds of data disappointments as growth expectations get revised up (Chart 3). The Citi Global Inflation Data Surprise index, however, remains just below zero after last year's plunge, but is showing signs of stabilizing (bottom panel). U.S. inflation is already starting to bottom out, but Euro Area core inflation has been underwhelming of late. It will likely take a rise in the latter to trigger the next move higher in global yields, as the market will begin to more aggressively price in less accommodative monetary policy from the ECB. For now, U.S. Treasuries are driving the path of yields, with the "leadership" of the bond bear market expected to switch to Europe later on in 2018. In terms of our recommend duration strategy and country allocations, we are sticking with our current positions which are finally beginning to move in favor of our forecasts (Chart 4): Chart 3The Next Leg Higher In Global Yields##BR##Must Be Driven By Inflation Surprises The Next Leg Higher In Global Yields Must Be Driven By Inflation Surprises The Next Leg Higher In Global Yields Must Be Driven By Inflation Surprises Chart 4Our Recommended##BR##Country & Curve Allocations Our Recommended Country & Curve Allocations Our Recommended Country & Curve Allocations Underweights to countries where we expect central banks to hike rates (U.S., Canada) or more openly discuss a tapering of asset purchases (Germany, France). Overweights to countries where we expect no change in policy rates (U.K., Australia) or only modest changes to asset purchase programs (Japan). Positioning for steeper yield curves in countries where growth is strong, economies are at or beyond full employment, but where inflation expectations remain far enough below central bank targets to prevent policymakers from turning more hawkish faster than expected (U.S., Germany, Japan). Bottom Line: Global bond yields continue to move higher, driven by rising inflation expectations and falling investor risk aversion. With global interest rates still not at levels that will restrict growth or draw capital away from booming equity markets, the path of least resistance for yields remains upward. Maintain a below-benchmark overall portfolio duration stance, with a bearish curve steepening bias in the U.S. and core Europe. U.K. Gilts: The BoE's Hands Are Tied In our final report of 2017, we updated our recommended allocations in our Model Bond Portfolio based on the key views stemming from the 2018 BCA Outlook.2 We upgraded our country allocation to U.K. Gilts to overweight, primarily as a "defensive" position within a portfolio positioned for an expected rise in global bond yields. That may sound surprising given the current elevated level of inflation and low unemployment rate in the U.K. Yet our view is based on the notion that the Bank of England (BoE) will have a very difficult time trying to raise interest rates at all in 2018 when other major global central banks are likely to take a more hawkish turn. The main reason that the BoE will be unable to do much on the interest rate front is that the U.K. economy is likely to slow in the coming quarters. The OECD leading economic indicator is decelerating steadily, and is pointing to a real GDP growth rate below 2% in 2018 (Chart 5). The updated IMF forecast for the U.K. calls for growth to only reach 1.5% in both 2018 and 2019. The biggest factors that will weigh on growth will be a sluggish consumer and softer capex. Household consumption growth has already been slowing since early 2017, driven by diminishing consumer confidence (Chart 6, top panel). High realized inflation which has sapped the purchasing power of U.K. workers who have not seen matching increases in wages, is weighing on confidence (3rd panel). Consumers were able to maintain a decent pace of spending during a period of stagnant real income growth by drawing down on savings, but that looks to be tapped out now with the saving rate down to a 19-year low of 5.5% (bottom panel). Chart 5U.K. Growth Set To Slow U.K. Growth Set To Slow U.K. Growth Set To Slow Chart 6The U.K. Consumer Looks Tapped Out The U.K. Consumer Looks Tapped Out The U.K. Consumer Looks Tapped Out Making matters worse, U.K. consumers are not seeing much of a wealth effect from the housing market. The December 2017 readings of the year-over-year growth rate of U.K. house prices from the Halifax and Nationwide house prices came in at 1.1% and 2.5% respectively (Chart 7, top panel). In addition, the net balance of national house price expectations from the Royal Institution of Chartered Surveyors (RICS) survey has steadily declined since mid-2016 and now sits just above zero (i.e. equal number of respondents expecting higher prices and falling prices). The same indicator for London was a staggering -54% in November 2017. U.K. homeowners have had to take a lot of hits over the past couple of years. A 2016 hike in the stamp duty for second homes and buy-to-let properties prompted a plunge in more "speculative" property transactions. The squeeze on real household incomes that has damaged consumer spending has also made homes less affordable, even with very low mortgage rates. Most importantly, the 2016 Brexit vote and subsequent uncertainty over the U.K.'s future relationship with Europe has placed an enormous cloud over housing demand - both from potential reduced immigration to the U.K. and businesses and jobs potentially relocating to European Union countries. The Brexit uncertainty is also weighing on U.K. business investment spending. U.K. capital expenditure growth slowed to 4.3% year-over-year in nominal terms in Q3 2017, and is even lower in real terms (Chart 8, top panel). Capex is generally import-intensive, and the rise in import costs due to the depreciation of the Pound after the 2016 Brexit vote raised the cost of investment. Chart 7No Growth In##BR##U.K. Housing No Growth In U.K. Housing No Growth In U.K. Housing Chart 8Brexit Gloom Trumps Export##BR##Boom For U.K. Companies Brexit Gloom Trumps Export Boom For U.K. Companies Brexit Gloom Trumps Export Boom For U.K. Companies This explains why U.K. capital spending has lagged even with manufacturing indicators in decent shape, such as the Confederation of British Industry (CBI) survey which shows the highest readings on total industrial orders and export orders since 1988 and 1995, respectively (2nd panel). Yet non-financial credit growth stalled out in the latter half of 2017, while the CBI survey of business optimism has turned into negative territory. Brexit uncertainties are clearly trumping strong export demand, thus U.K. capital investment is likely to remain sluggish in 2018 even with robust global growth. With U.K. economic growth likely to slow in 2018, the lingering problem of high inflation should start to fade. Already, both headline and core CPI inflation have stabilized, with the latter actually drifting a touch lower in the latter half of 2017 (Chart 9). The small gap between the two can be explained by the rise in global oil prices seen over the past year. The impact of oil on U.K. inflation expectations is relatively modest compared to other countries with much lower realized inflation rates, as we discussed in last week's Weekly Report.3 What is far more relevant is the path of British pound. The 16% plunge in the trade-weighted sterling index after the 2016 Brexit vote was a major reason why U.K. realized inflation blew through the BoE's 2% target last year. The currency has since stabilized at a depressed level and traded in a relatively narrow range in 2017. The trade-weighted index is now 3% above year-ago-levels, which should help U.K. inflation rates drift lower in the next 6-12 months - especially if U.K. growth underwhelms at the same time. Already, the more stable currency has allowed the inflation rates of import prices and producer prices to fall sharply last year (bottom panel), which should soon start to feed through into overall inflation rates. Lower realized inflation would be a welcome boost for the spending power of U.K. households and businesses, but will likely be dwarfed by the impact of oil prices in the near term. More importantly, the slowing momentum of economic growth, now fueled more by Brexit uncertainty than high inflation, will limit the BoE's ability to continue normalizing the very low level of U.K. interest rates. Our 12-month U.K. discounter shows that markets are pricing in 25bps of rate hikes over the next twelve months (Chart 10). The forward path of interest rates shown in the U.K. Overnight Index Swaps curve suggests that the hike could come by October. That is unlikely to happen given the slump in leading economic indicators, and peaking in currency-fueled inflation, currently underway. Chart 9Currency-Fueled U.K. Inflation Is Peaking Out Currency-Fueled U.K. Inflation Is Peaking Out Currency-Fueled U.K. Inflation Is Peaking Out Chart 10Stay Overweight U.K. Gilts Stay Overweight U.K. Gilts Stay Overweight U.K. Gilts A stand-pat BoE, combined with more stable and potentially falling U.K. inflation, will limit the ability for U.K. Gilt yields to rise by as much as we are expecting in the U.S., and even core Europe, over the next 6-12 months. Gilts have become a relative safe haven within a global bond bear market in the developed markets, with a yield beta of around 0.5 to U.S. Treasuries and German government bonds. This has already allowed Gilts to outperform the Barclays Global Treasury index (in currency-hedged terms) since the most recent cyclical low in global bond yields last September (bottom panel). We continue to expect Gilts to outperform in 2018. Stay overweight. Bottom Line: The momentum in the U.K. economy is slowing, as a weaker consumer, slower housing activity, and softer capital spending are offsetting a pickup in exports. With the inflationary impulse from the 2016 plunge in the Pound now fading, and with Brexit uncertainty weighing on business confidence, the Bank of England will struggle to raise rates in 2018. Stay overweight Gilts. Robert Robis, Senior Vice President Global Fixed Income Strategy rrobis@bcaresearch.com Ray Park, Research Analyst Ray@bcaresearch.com 1 http://www.imf.org/en/Publications/WEO/Issues/2018/01/11/world-economic-outlook-update-january-2018 2 Please see BCA Global Fixed Income Strategy Weekly Report, "Our Model Bond Allocation In 2018: A Tale Of Two Halves", dated December 19th 2017, available at gfis.bcaresearch.com. 3 Please see BCA Global Fixed Income Strategy Weekly Report, "The Importance Of Oil", dated January 16th 2018, available at gfis.bcaresearch.com. 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