Technology
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 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 Chart I-3Expected Returns Given Starting Point Shiller P/E 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 Chart I-5U.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) 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 Chart I-8Timing 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 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 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 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 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 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 Chart I-11Composition Of Voting FOMC Members 2017 Vs. 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 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 Chart II-3Global Robot Usage By Industry (2016) 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) Chart II-5Stock Of Robots By Country (II) (2016) 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 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 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 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 Chart II-10U.S.: Unit Labor Costs Vs. Robot Density 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 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 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 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 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 Chart II-16Japan: 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 Chart III-2Willingness To Pay For Risk Chart III-3U.S. Equity Sentiment Indicators Chart III-4Revealed Preference Indicator Chart III-5U.S. Stock Market Valuation Chart III-6U.S. Earnings Chart III-7Global Stock Market And Earnings: ##br##Relative Performance Chart III-8Global Stock Market And Earnings: ##br##Relative Performance FIXED INCOME: Chart III-9U.S. Treasurys And Valuations Chart III-10U.S. Treasury Indicators Chart III-11Selected U.S. Bond Yields Chart III-1210-Year Treasury Yield ComponentsChart III-13U.S. Corporate Bonds And Health Monitor Chart III-14Global Bonds: Developed Markets Chart III-15Global Bonds: Emerging Markets CURRENCIES: Chart III-16U.S. Dollar And PPP Chart III-17U.S. Dollar And Indicator Chart III-18U.S. Dollar Fundamentals Chart III-19Japanese Yen Technicals Chart III-20Euro Technicals Chart III-21Euro/Yen Technicals Chart III-22Euro/Pound Technicals COMMODITIES: Chart III-23Broad Commodity Indicators Chart III-24Commodity Prices Chart III-25Commodity Prices Chart III-26Commodity Sentiment Chart III-27Speculative Positioning ECONOMY: Chart III-28U.S. And Global Macro Backdrop Chart III-29U.S. Macro Snapshot Chart III-30U.S. Growth Outlook Chart III-31U.S. Cyclical Spending Chart III-32U.S. Labor Market Chart III-33U.S. Consumption Chart III-34U.S. Housing Chart III-35U.S. Debt And Deleveraging Chart III-36U.S. Financial Conditions Chart III-37Global Economic Snapshot: Europe Chart III-38Global Economic Snapshot: China Mark McClellan Senior Vice President The Bank Credit Analyst
Dear Client, This is our final publication for the year. We will be back on January 5th. On behalf of the entire Global Investment Strategy team, I would like to wish you a Merry Christmas, Happy Holidays, and a Prosperous New Year! Best regards, Peter Berezin, Chief Global Strategist Highlights Global bonds have sold off in recent days, but the spread between long-term and short-term Treasury yields remains well below where it was at the start of the year. A flatter Treasury yield curve suggests that the ongoing U.S. business-cycle expansion is getting long in the tooth. Nevertheless, three factors dilute the potentially bearish message from the curve. First, the yield curve has flattened largely because short-term rate expectations have risen thanks to better economic data. Second, both the 10-year/2-year and 10-year/3-month spreads are still above levels that have foreshadowed poor returns for risk assets in the past. This is particularly true for equities. Third, a structurally low term premium has distorted the signal from the yield curve. The U.S. yield curve is likely to steepen over the next six months, before flattening again in the lead-up to a recession in late-2019. We reveal the One Number that will kill bitcoin. Feature A Harbinger Of Recession? The U.S. yield curve has steepened in recent days, but is still much flatter than it was at the start of the year. The 10-year/3-month spread currently stands at 113 bps, down 84 bps year-to-date. The 10-year/2-year spread has fallen from 125 bps to 62 bps. Numerous academic studies have highlighted the importance of the yield curve as a leading indicator of recessions.1 In fact, every U.S. recession over the past 50 years has been preceded by an inverted yield curve (Chart 1). Chart 1An Inverted Yield Curve Has Often Been A Harbinger Of A Recession The converse has generally been true as well: Most inversions in the yield curve have coincided with a recession. The only two exceptions were in 1967 - when credit conditions tightened and industrial production decelerated, but the U.S. still managed to avoid succumbing to a recession - and in 1998, when the yield curve briefly inverted during the LTCM crisis. Considering that recessions and equity bear markets typically overlap (Chart 2), it is not surprising that investors have begun to fret about what a flatter yield curve may mean for their portfolios. Chart 2Recessions And Bear Markets Usually Overlap Don't Worry... Yet Chart 3U.S. Growth Expectations Revised Higher We would not be as dismissive of a flatter yield curve as Fed Chair Yellen was during her December press conference. Policymakers and investors alike have been too quick to downplay the signal from the yield curve in the past. In 2006, they blamed the "global savings glut" for dragging down long-term yields. In 2000, they argued that the federal government's budget surplus was reducing the supply of long-term bonds. In both cases, the bond market turned out to be seeing something more ominous than they were. That said, there are three reasons why we would discount some of the more bearish interpretations of what a flatter yield curve is telling us. First, the flattening of the yield curve has occurred mainly because of an increase in short-term rate expectations, rather than a decrease in long-term bond yields. The increase in rate expectations has been largely driven by stronger growth data. The economic surprise index has surged far into positive territory and analysts are now scrambling to revise up their 2018 and 2019 U.S. GDP growth projections (Chart 3). The Fed now sees growth of 2.5% in 2018 and an unemployment rate of 3.9% by the end of next year. Back in September, the Fed expected growth of 2.1% and an unemployment rate of 4.1%. Second, our research suggests that the slope of the yield curve only becomes worrisome for the economy when it falls to extremely low levels. This conclusion is reinforced by the New York Fed's Yield Curve Recession Model, which uses the difference between 10-year and 3-month Treasury rates to estimate the probability of a U.S. recession twelve months ahead.2 The model's current recession probability stands at a modest 11% (Chart 4). The last three recessions all began when the implied probability was over 25%. Chart 4NY Fed's Yield Curve Model Suggests That The Probability Of A Recession Is Still Quite Low Third, the slope of the yield curve is weighed down by a structurally low term premium. The term premium measures the additional return investors can expect to receive by locking in their money in a 10-year Treasury note instead of rolling over a short-term Treasury bill for an entire decade. Historically, the term premium has been positive. Over the past few years, however, it has often been negative - meaning that investors have been willing to pay a premium to take on duration risk. Many commentators have attributed this peculiar state of affairs to central bank asset purchases, which they claim have artificially depressed long-term bond yields. There is some truth to this, but we think there is an even more important reason: Bonds today provide a good hedge against bad economic news. When fears of an economic slowdown mount, equities tend to sell off, while bond prices rise. This differs from the circumstances that existed in the 1970s and 1980s, when bad economic news usually meant higher inflation. To the extent that long-term bonds now serve as insurance policies against recessions, investors are more willing to accept the lower yields that they offer. Empirically, one can see this in the shift of the correlation between equity returns and bond yields. It was strongly negative up until the mid-1990s. Now it is strongly positive (Chart 5). A low term premium implies that the slope of the yield curve should be structurally flatter. That is exactly what we see today. Chart 6 shows that the 10-year/3-month spread would be well above its long-term average if the term premium were removed from the picture. This implies that investors have little to fear from the shape of today's yield curve, at least over the next six-to-twelve months. Chart 5Bond Prices Now Tend To Rise When Equity Prices Go Down Chart 6Stripping Out The Term Premium,##BR##The Yield Curve Is Not So Flat Rising Odds Of A Recession In Late-2019 Beyond then, things start to get dicey. The Fed's end-2018 unemployment rate projection of 3.9% is 0.7 percentage points below its long-term estimate of the unemployment rate. This means that at some point in the future, the Fed will need to lift interest rates above their "neutral" level in order to push the unemployment rate up to its equilibrium level. That's a risky gambit. There has never been a case in the post-war era where the unemployment rate has risen by more than one-third of a percentage point without a recession ensuing (Chart 7). Modern economies are subject to feedback loops. Once economic conditions begin to deteriorate, households cut back on spending. This leads to less hiring and even less spending. Bad economic news begets worse news. Chart 7Even A Small Uptick In The Unemployment Rate Is Bad News For The Business Cycle Implications For Equities And Credit A flatter Treasury yield curve suggests that the U.S. business cycle is entering the home stretch. Nevertheless, as we pointed out two weeks ago, the 7th-to-8th innings of business-cycle expansions are often the juiciest for equity investors (Table 1).3 Table 1Too Soon To Get Out Chart 8 shows that the term spread today is still at levels that have signaled positive equity returns in the past. In fact, today's term spread is close to levels that prevailed in the second half of the 1990s, a period that coincided with the greatest bull market in American history. This message is echoed by our forthcoming MacroQuant model, which continues to flag upside risks for stocks over the next 6-to-12 months (Chart 9). Chart 8Current Term Spread Is Still Pointing##BR##To Positive Equity Returns Chart 9MacroQuant Still Positive##BR##On The Stock Market Globally, we favor euro area and Japanese equities (in local-currency terms) in the developed market sphere due to our expectation that the euro and yen will depreciate somewhat next year. Both the euro area and Japan also have greater exposure to cyclical sectors. This fits with our bias towards owning cyclicals over defensive stocks. Today's term spread is a bit more worrying for corporate credit. As our bond strategists have noted, a flatter yield curve is consistent with lower, though still positive, monthly excess returns for high-yield bonds (Chart 10).4 Again, the second half of the 1990s provides a potentially useful template: Despite a sizzling stock market, high-yield spreads actually widened as corporations loaded up on debt (Chart 11). The deterioration in our Corporate Health Monitor over the past five years suggests that a similar dynamic may be afoot (Chart 12). Chart 10Junk Monthly Excess Returns##BR##And The Yield Curve Chart 11Second Half Of 1990s: When High-Yield Spreads##BR##Rose With Stock Prices Chart 12Corporate Health Has##BR##Been Deteriorating Yield Curve Should Steepen Over The Coming Months Of course, much depends on what happens to the yield curve going forward. We suspect that it will flatten again towards the end of next year. However, it is likely to steepen over the next six months. U.S. GDP growth will remain above trend next year, as wages start to rise more briskly and firms boost capital spending to meet rising demand for their products. Fiscal policy should also help. Tax cuts will lift growth by 0.2%-to-0.3% in 2018. Higher disaster relief efforts following the hurricanes and a pending agreement to raise caps on discretionary spending will also translate into increased federal government spending. Investors have largely overlooked this source of fiscal stimulus, but increased spending will contribute almost as much to growth next year as lower taxes. Unfortunately, all this additional growth, coming at a time when the output gap is all but closed, is likely to stoke inflationary pressures. Our Pipeline Inflation Pressure Index has risen sharply since early 2016, while the ISM prices paid index has shot up. The New York Fed's Underlying Inflation Gauge has accelerated to an 11-year high of 3% (Chart 13). Historically, rising inflation expectations have led to a steeper yield curve (Chart 14). The implication is that investors should favor inflation-linked securities over government bonds. Chart 13U.S. Inflation Pressure Are Building Chart 14Rising Inflation Expectations Lead To A Steeper Yield Curve The One Number That Will Kill Bitcoin In a normal world, most reasonable people would regard a flatter yield curve and continued weak inflation readings as evidence that fiat money was, if anything, doing too good a job as a store of value. However, nothing is normal or reasonable about bitcoin.5 Chart 15Governments Will Want Their Cut:##BR##U.S. Seigniorage Revenue No one knows when the bitcoin bubble will burst. Only a tiny fraction of the public owns the virtual currency. The value of all bitcoin in circulation represents 0.35% of global GDP. At its peak in 1996, the value of all pyramid scheme assets in Albania amounted to almost half of GDP. Never underestimate the lure of easy money. While we do not know where the price of bitcoin will be ten months from now, we do have a good guess of where it will be ten years from today. And that price is zero, or thereabouts. When the U.S. Treasury issues a $100 bill, it gains the ability to buy $100 of goods and services with it. The government's cost is whatever it pays to print the bill, which is next to nothing. This so-called "seigniorage revenue" is set to reach $100 billion this year (Chart 15). That is the number that will kill bitcoin. There is no way the U.S. government will forsake this revenue in order to make room for bitcoin and other cryptocurrencies. Not when there are entitlements to pay and gaping budget deficits to finance. A variety of other countries have a love-hate relationship with bitcoin, partly because of their "the enemy of my enemy is my friend" attitude towards the dollar. But that will change when they see their tax bases eroding as more commerce gets done in the anonymous world of cryptocurrencies. Bitcoin's days are numbered. The only question is who will be holding the bag when the party ends. Peter Berezin, Chief Global Strategist peterb@bcaresearch.com 1 Please see Jonathan H. Wright, "The Yield Curve And Predicting Recessions," FEDs Working Paper No. 2006-7, May 3, 2006; Michael Owyang, "Is the Yield Curve Signaling a Recession?"Federal Reserve Bank Of St. Louis, March 24, 2016; and Arturo Estrella and Mishkin, Frederic S., "The Yield Curve as a Predictor of U.S. Recessions," Federal Reserve Bank Of New York, (2:7), June 1996. 2 Please see "The Yield Curve As A Leading Indicator: Probability of U.S. Recession Charts," Federal Reserve Bank Of New York. 3 Please see Global Investment Strategy Weekly Report, "When To Get Out," dated December 8, 2017. 4 Please see U.S. Bond Strategy, "Proactive, Reactive Or Right?" dated December 12, 2017. 5 Please see European Investment Strategy Weekly Report, "Bitcoins And Fractals," dated December 21, 2017; Technology Sector Strategy Special Report, "Cyber Currencies: Actual Currencies Or Just Speculative Assets?" dated December 12, 2017; Global Investment Strategy Special Report, "Bitcoin's Macro Impact," dated September 15, 2017; and Technology Sector Strategy Special Report, "Blockchain And Cryptocurrencies," dated May 5, 2017. Tactical Global Asset Allocation Recommendations Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades
Highlights As bitcoin has developed into a fledgling form of money, the best valuation framework for it is the quantity theory of money. This states that the bitcoin money supply (in dollars) times bitcoin's velocity of circulation = the amount of world GDP carried out in bitcoin. In the short term, excessive herding signals a likely countertrend reversal, and implies that the bitcoin price will retest $12,750 at some point in the next 130 days. In the long term, the wholesale acceptance of cryptocurrencies in the global economy will be deflationary. Feature Bitcoin's near-vertical price ascent to $19,000 has left many commentators crying "bubble!" The problem with this is that you cannot define an asset bubble simply from the behaviour of a price. You need to assess fundamental value, and the extent of deviation above this fundamental value. Conceivably, bitcoin's near-vertical price ascent could be a correction from an "anti-bubble", in which the price was a long way below its fundamental value and rapidly corrected upwards. Which begs the question: what is the best way to assess the fundamental value of bitcoin and other cryptocurrencies? Chart of the WeekCryptocurrencies Will Prevent Inflation, Just Like The Gold Standard A Valuation Framework For Bitcoin As bitcoin has developed into a fledgling form of money, one potential valuation framework is the quantity theory of money. This states that the money supply times its velocity of circulation equals nominal GDP. Given that the supply of bitcoin will not exceed an upper limit of 21 million coins, we can say that the bitcoin money supply (in dollars) is the bitcoin price times 21 million. We can then use the quantity theory to deduce: Bitcoin price times 21 million times bitcoin's velocity of circulation = Amount of world GDP carried out in bitcoin. If we additionally assume that bitcoin's velocity is similar to that of the stock of broad fiat money, 1.5, then we can rearrange and simplify the equation to approximately: Bitcoin price = Amount of world GDP carried out in bitcoin divided by 30 million So if the market was discounting that $0.5 trillion of world GDP would be carried out in bitcoin, then its price should be $16,700. Given the purported nefarious uses of cryptocurrencies at the moment, and an estimated size of the world's shadow economy at around $16 trillion, an assumption of $0.5 trillion of bitcoin use in the world economy does not seem excessive. On the other hand, nefarious use might make bitcoin's velocity of circulation a lot higher than conventional money. Which would pull bitcoin's fair price much lower. Suffice to say, the above assumptions are broad-brush and open to challenge. Nevertheless, despite the many caveats, the above framework is probably the most valid for valuing a cryptocurrency once it gains acceptance as a fledgling form of money. Putting Bitcoin Through Fractal Analysis The behaviour of price alone cannot gauge an asset bubble. But the behaviour of price alone can gauge a shortage of liquidity in the asset which implies a potential countertrend reversal. Liquidity is plentiful when the market is split between short-term momentum traders and longer-term value investors. This is because the two herds generally disagree with each other. If the price fluctuates up, the momentum trader wants to buy while the value investor wants to sell; and vice-versa. So the herds trade with each other with plentiful liquidity and little movement in price. This raises an obvious question. Can there really be any value investors in cryptocurrencies? The answer is potentially yes, if these investors believe that cryptocurrency acceptance will increase over time. And if they apply the aforementioned valuation framework from the quantity theory of money. Still, liquidity will periodically evaporate if too many value investors join the short-term momentum herd. Instead of dispassionately investing on the basis of a valuation framework, value investors get lured into participating in a strong rally, and their buy orders add fuel to the rally. A tipping point comes when all the value investors have joined the momentum herd. If a value investor then suddenly reverts to type and puts in a sell order, he will find that there are no buyers left. Liquidity has evaporated, and finding new liquidity might require a substantial reversal in the price to attract a buy order from an ultra-long-term deep value investor. As regular readers know, fractal analysis measures whether the herding behaviour in any financial instrument has reached its tipping point, signalling a likely end of its price trend. Today, the 130-day herding indicator for bitcoin is at a level which has indicated three previous countertrend reversals of at least one fifth of the preceding 130-day move (Chart I-2, Chart I-3, Chart I-4). Chart I-2Bitcoin: The 130 Day Fractal Dimension Signalled A Reversal In 2015 Chart I-3Bitcoin: The 130 Day Fractal Dimension Signalled Two Reversals In 2017 Chart I-4Bitcoin: The 65 Day Fractal Dimension Also Signalled Two Previous Reversals If this herding indicator signals a fourth countertrend reversal, it implies that the bitcoin price will retest $12,750 at some point in the next 130 days. Are Cryptocurrencies Inflationary Or Deflationary? On the face of it, the emergence of cryptocurrencies sounds inflationary. After all, if the general acceptance of cryptocurrencies for commercial transactions increases, there will be new money supply. And this new money supply will increase the nominal demand for goods and services. However, the truth is more nuanced. Unlike fiat money supply - which can expand without limit - each cryptocurrency has a defined limit to its supply. Although new cryptocurrencies can emerge, there seems to be a limit to the aggregate amount of cryptocurrency supply. The limiting factor is that it takes energy to create cryptocurrency through so-called 'mining'. Miners must compete to validate transactions that occur in a cryptocurrency. The competition takes the form of solving a mathematical problem - for example, finding the prime factors of a very large number. And the computational demands are energy sapping. Furthermore, the computational demands - known as 'proof of work' - get progressively more difficult for each additional new coin mined. Given that the computational resources in the world are finite and growing at a gentle and predictable rate, the implication is that the growth in the total amount of cryptocurrency is also limited. So while the emergence of cryptocurrencies does increase the money supply in the near-term (Chart I-5), a large-scale rejection of fiat money would make it impossible for uncouth policymakers to spike the overall money supply over the longer-term. Chart I-5Cryptocurrencies: Market Cap Is Now Non-Trivial Here's a further thought. Imagine if the proof of work computations, instead of being random mathematical calculations, solved useful problems that expanded the envelope of knowledge. This could boost real productivity, which is ultimately just a function of the stock of human ingenuity. In which case, any increase in money supply would be matched by an increase in potential real output. Interestingly, a recent paper from the Bank of Canada proposes that a wholesale acceptance of cryptocurrencies in the global economy could act as a new gold standard, whose effect would be mildly deflationary1 (Chart of the Week) and Table I-1). We fully agree with the Bank of Canada analysis. Table I-1No Persistent Inflation For 700 Years! The sting in the tail is that the analysis describes prices denominated in cryptocurrency terms. In fiat currency terms, the quantity theory of money implies that prices would rise2 - unless central banks reacted to the emergence of cryptocurrencies by shrinking the supply of fiat money. Would they? Very likely yes. If they didn't, the demise of fiat money would accelerate as people voted with their wallets and switched to superior stores of purchasing power. Nevertheless, we suspect that any central bank response would just delay the inevitable. As Larry Summers puts it: I am much more confident that the world of payments will look very different 20 years from now than I am about how it will look. And with that observation, I am signing off for 2017. I do hope you have enjoyed our provocative and counterintuitive insights this year. In the vast majority of cases, these insights have led to highly profitable investment recommendations. We promise to continue the success in 2018! Early next year, we will also unveil a major enhancement to our proprietary fractal trading strategy. So stay tuned. It just remains for me to wish you all a very enjoyable Festive Season and a prosperous 2018. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com 1 Bank of Canada Staff Working Paper, A Bitcoin Standard: Lessons from the Gold Standard https://www.bankofcanada.ca/2016/03/staff-working-paper-2016-14/ 2 Please see the Global Investment Strategy Special Report titled "Bitcoin's Macro Impact", dated September 15, 2017 available at gis.bcaresearch.com and Technology Sector Strategy Special Report titled "Cyber Currencies: Actual Currencies Or Just Speculative Assets?", dated December 12, 2017 available at tech.bcaresearch.com. Fractal Trading Model* As discussed in the main body of this report, this week's trade is to expect a countertrend reversal in bitcoin. Go short with a profit target at $12750 and stop-loss at $28000. In other trades, long silver has had a strong 1-week bounce while long U.K. personal products / short U.K. food and beverages reached the end of its 65 day maximum holding period and closed with a small profit. 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-6 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 Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch##br## - Interest Rate Expectations Chart II-6Indicators To Watch ##br##- Interest Rate Expectations Chart II-7Indicators To Watch ##br##- Interest Rate Expectations Chart II-7Indicators To Watch ##br##- Interest Rate Expectations
Highlights Overweighting Eurostoxx50 versus S&P500 is just a sector play - you must believe that banks are going to outperform technology. It is categorically not a relative economic growth or relative valuation play. The best expression of euro area economic outperformance - as we believe is likely - is not through mainstream equity indexes. It is through the euro. Could Spain in 2014-17 be Italy in 2018-21? If so, the cleanest play is through Italian bonds: long Italian BTPs versus French OATs. Play the lottery for free: when the price gap between the second and first month VIX future is greater than that between the first month and VIX spot - as it is now - it signals a potentially free lottery ticket. Feature Don't Play The Euro Area Economy Through The Stock Market The fallacy of division is a logical fallacy. It occurs when somebody falsely infers that what is true for the whole is also true for the parts that make up the whole. For example, somebody might see that their computer screen appears purple, and infer that the pixels that make up the screen are also purple. In fact, pixels are never purple. They are either red or blue. The fallacy of division is that the property of the whole - purpleness - does not translate to the property of the parts - redness or blueness. Chart of the WeekEuro Area Vs. U.S. Equities Is Just A Sector Play: Banks Vs. Technology The fallacy of division also affects investors. Since global equities are a play on the global economy, some investors infer that major equity indexes such as the Eurostoxx50 are relative plays on their regional economies. In fact, this is a fallacy of division: the property of the equity market as a global aggregate does not translate to the relative property of an equity market as a regional or national part. Through the past three years, the euro area economy has comfortably outperformed the U.S. economy1 (Chart I-2). Yet the Eurostoxx50 has substantially underperformed the S&P500 (Chart I-3). Why? Because the Eurostoxx50 has a major 14% weighting to banks and a minor 7% weighting to technology. The S&P500 is the mirror image; a minor 7% weighting to banks and a major 24% weighting to technology. Chart I-2The Euro Area Economy ##br##Has Outperformed... Chart I-3...But The Eurostoxx50 ##br##Has Underperformed Hence, for the Eurostoxx50 the distinguishing property is 'bank'; for the S&P500 it is 'technology'. And as banks have underperformed technology, the Eurostoxx50 has underperformed the S&P500. This large difference in sector exposure also means that a head-to-head comparison of equity market valuation is misleading. The euro area, trading on a forward price to earnings (PE) multiple of 15, appears considerably cheaper than the U.S., trading on a forward PE of 19. But this head-to-head difference just reflects the forward PEs of banks at 11 and technology at 19. As banks will likely generate less long-term growth than technology, banks are rightfully cheaper than technology and the Eurostoxx50 is rightfully cheaper than the S&P500. Some people suggest sector-adjusting stock market valuations to allow for the sector biases. The problem is that this suggestion cannot avoid the inescapable end-result. The bank-heavy Eurostoxx50 versus the tech-heavy S&P500 relative performance will still depend on banks versus technology (Chart of the Week). Remarkably, this overarching driver is captured in just the three largest euro area banks versus the three largest U.S. tech stocks. This means that relative performance simply reduces to whether Banco Santander, BNP Paribas and ING outperform Apple, Microsoft and Google,2 or vice-versa (Chart I-4). Chart I-4Eurostoxx50 Vs. S&P500 Reduces To: Santander, BNP & ING Vs. Apple, Microsoft & Google Everything else is largely irrelevant. Hence, the counterintuitive conclusion is that overweight Eurostoxx50 versus S&P500 is actually a sector play. You must hold the view that banks are going to outperform technology. At the moment, we are agnostic on this view. The best expression of euro area economic outperformance - as we believe is likely - is not through mainstream equity indexes. It is through bond yield spread compression and through exchange rates. Our preferred expression is structurally long EUR/USD. Could Spain In 2014-17 Be Italy In 2018-21? In 2013, Spain seemed to be on its knees. The economy had slumped by almost 10%, unemployment stood at 27%, and the stock of bank loans which were non-performing exceeded 13%. Doomsayers abounded. Standard and Poor's downgraded Spain's sovereign credit rating to BBB-, one notch above junk, and esteemed Wall Street strategists predicted the unemployment rate would remain above 25% for the rest of the decade. But the esteemed strategists were completely wrong. Through 2014-17, Spanish real GDP per head has grown by almost 15% (Chart I-5) - making it one of the top performing developed economies; unemployment has plunged by 10% (Chart I-6); and non-performing loans have declined sharply. What suddenly transformed Spain from zero to hero? The answer is that Spain recapitalised its banks. Chart I-5Through 2014-17 Spanish Real GDP ##br##Per Head Is Up Almost 15%... Chart I-6...And Unemployment##br## Is Down 10% After a financial crisis, the golden rule of recovery is to repair the banking system as soon as possible. In the aftermath of housing-related banking crises in 2008, the U.S. and U.K. quickly recapitalised their damaged banking systems; Ireland followed a couple of years later; Spain waited until 2013. But in each case, the economies rebounded very strongly as soon as the banks' aggressive deleveraging ended. Which brings us to Italy. Many people claim that Italy's long-standing economic underperformance is due to deep-seated structural problems. We do not dispute that such problems exist, but they cannot be the main cause of the economic underperformance. After all, through 1999-2007, Italian real GDP per head performed more or less in line with the U.S., Canada and France (Chart I-7), even without a private sector credit boom which the other economies had. Italy's underperformance really started after the 2008 financial crisis. And the most plausible explanation is that its dysfunctional banking system has been left broken for so long. Italy has procrastinated because its government is more indebted than other sovereigns and its banking problems have not caused an outright crisis - yet. But now policymakers in Rome, Brussels and Frankfurt realise that a hamstrung economy carries risks of a populist backlash against the European project. Finally, Italian banks' equity capital is rising, their solvency is improving and the share of non-performing loans appears to have peaked at the same level as in Spain in 2013 (Chart I-8). Chart I-7Through 1999-2007 Italy Performed In##br## Line With Other Major Economies Chart I-8Spanish NPLs Peaked In 2013, ##br##Italian NPLs Are Peaking Now So could Spain in 2014-17 be Italy in 2018-21? Once again, doomsayers abound and the counterintuitive thought could pay off. The cleanest way to play this is through Italian bonds: long Italian BTPs versus French OATs. Play The Lottery For Free As everybody knows, playing the lottery is not a good investment strategy. Most of the time your Lotto ticket brings zero reward, though occasionally you do win a prize. In fact, the U.K. National Lottery has said that the expected win per £1 played averages £0.47. Meaning the long-term return on this strategy is -53%. In the financial markets, the equivalent of a Lotto ticket is to buy volatility. In practice, this means buying a future on a volatility index such as the VIX. The problem is that the VIX futures curve usually slopes upwards. So if the curve doesn't change, a future bought above the spot price loses value when it expires at the spot price (Chart I-9). The upshot is that most of the time, the future 'rolls down the curve', and you lose money, though occasionally when volatility spikes you win. But counterintuitively, sometimes you can play the lottery for free. Look at the VIX futures curve: when the price gap between the second and first month is greater than that between the first month and spot - as it is now (Chart I-10) - it signals a potentially free lottery ticket. Chart I-9VIX Futures "Roll Down The Curve" Chart I-10Spotting A Free Lottery Ticket Under these circumstances, the strategy is to go long the first month future and short the second month future. If the futures curve stays broadly as it is - and both futures contracts roll down the curve - the loss on the first month long position will be made up by the gain on the second month short position. Effectively, the combined position becomes costless. Yet this potentially costless position is still playing the lottery. Because if volatility does spike, the volatility futures curve tends to invert sharply (go into backwardation). Hence, the gain on the first month long position substantially outweighs the loss on the second month short position. Now might be a good time to play the lottery for free. Dhaval Joshi, Senior Vice President Chief European Investment Strategist dhaval@bcaresearch.com 1 On a real GDP per capita basis. 2 Listed as Alphabet. Fractal Trading Model* Silver's 65-day fractal dimension is at a level which has previously indicated four tradeable trend reversals. Go long silver with a profit target / stop-loss of 4.5% In other trades, we are pleased to report that short basic materials versus market and short copper / long tin both hit their respective profit targets. This leaves us with six open positions. 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-11 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 Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch##br## - Interest Rate Expectations Chart II-6Indicators To Watch##br## - Interest Rate Expectations Chart II-7Indicators To Watch##br## - Interest Rate Expectations Chart II-8Indicators To Watch##br## - Interest Rate Expectations
Highlights Growth in the Taiwanese economy has trended sideways this year, but a budding turnaround in weak domestic demand suggests that growth should improve in 2018. The appreciation of the TWD from its 2016 low reflects investor inflows rather than bullish fundamentals. The risk of a protectionist backlash means that monetary authorities are reluctant to intervene aggressively to limit the rise. We recommend that investors stick with our existing long MSCI China / short Taiwan trade, for now. A breakout in relative Taiwanese tech sector performance coupled with a weakening TWD would likely be a sufficient basis to close the trade at a healthy profit. Feature We last wrote about Taiwan in February of this year,1 when the risk of protectionist action from the Trump administration loomed large. While there have been no negative trade actions levied against Taiwan this year, macro factors, particularly the strength of the currency, continue to argue for an underweight stance within the greater China bourses (China, Hong Kong, and Taiwan). Our long MSCI China / short Taiwan trade has generated an impressive 19% return since its inception in February. The trade has become significantly overbought, but we recommend that investors stick with it, for now. A material easing in pressure on Taiwan's trade-weighted exchange rate appears to be the most likely catalyst to close the trade and to upgrade Taiwan within a portfolio of greater China equities. The Taiwanese Economy In 2017: What Has Changed? Real GDP growth in Taiwan has generally trended sideways in 2017, decelerating in the first half of the year and then recovering in the third quarter (Chart 1). While these fluctuations in its growth profile have been somewhat muted, overall GDP growth has masked a sizeable divergence between domestic demand and export growth. Taiwan is a highly trade-oriented economy, with exports of goods & services accounting for nearly 65% for its GDP, and a recent acceleration in real export volume has positively contributed to overall growth. Over 50% of Taiwan's exports are tech-based, and Chart 1 panel 2 highlights the close link between global semiconductor sales (which have risen sharply over the past year) and Taiwanese nominal exports. But as Chart 1 panel 3 shows, growth in real domestic demand has fallen back into contractionary territory, driven largely by a sharp decline in gross fixed capital formation. This decline in investment is somewhat surprising, given the close historical relationship between Taiwan's real exports and investment (Chart 2, panel 1). But the sharp drop may have been a lagged response to the export shock that occurred during the synchronized global growth slowdown in 2015, as it led to a non-trivial accumulation of inventory (Chart 2, panel 2). The recent acceleration of export growth and a renewed draw in inventories suggests that the severe pullback in investment is likely to reverse in the coming year. Chart 1A Divergence Between Domestic Demand##br## And Exports Chart 2Investment Likely To Rebound Over ##br##The Coming Year The evolution of Taiwanese capital goods imports is likely to provide an important confirming signal about the trend in real investment, given the close historical correlation between the two series. For now, the growth in capital goods imports is rebounding from negative territory (Chart 3), which is consistent with the view that investment is set to recover. Finally, while real consumer spending growth also decelerated in the first half of the year, the acceleration in Q3 has brought consumption back to its 5-year moving average. More importantly, Chart 4 highlights that the consumer confidence index in Taiwan is closely correlated with real spending, with the former heralding a rise in the latter over the coming months. Chart 3Capital Goods Signal An Investment Recovery Chart 4Consumption Also Set To Improve Bottom Line: Growth in the Taiwanese economy has trended sideways this year, but a budding turnaround in weak domestic demand suggests that growth should improve in 2018. The Taiwanese Dollar: Driven By Flows, Not Fundamentals Taiwanese stock prices have underperformed Greater China bourses since the beginning of the year (Chart 5), despite the recent improvement in real export growth and signs of an impending improvement in domestic demand. To us, this underperformance has been largely caused by the strength in the Taiwanese currency. The Taiwanese dollar has appreciated since early-2016, both against the U.S. dollar and in trade-weighted terms (Chart 6). Although the currency retreated from May to August of this year, it has since resumed its uptrend and currently stands between 8-9% higher than last year's low in trade-weighted terms. Chart 5Significant Underperformance Of ##br##Taiwan Vs Greater China Chart 6Material Currency Appreciation##br## Since Early-2016 Crucially, Chart 7 highlights that the rise in the TWD cannot be explained by relative monetary policy or by an improvement in the terms of trade. The chart shows how the USD/TWD began to decouple from the relative 2-year swap rate spread in early-2016, and how the trend in Taiwan's export price index has been negatively correlated with the trade-weighted exchange rate. The best explanation for the recent strength in Taiwan's currency appears to be a surge in capital inflows oriented towards Taiwan's equity market (Chart 8). Foreign ownership of Taiwanese stocks has increased significantly over the past few years and is currently at a record high of 43%. Given that Taiwan's equity market is enormously tech-focused, it appears that global investors have been attracted to Taiwanese stocks as part of a play on the global tech rally. As we will discuss below, this has become somewhat of a self-defeating strategy, at least in terms of Taiwan's relative performance vs Greater China bourses. While it is possible that monetary authorities will attempt to combat the appreciation of the Taiwanese dollar, Chart 9 highlights that there is little room to maneuver. First, Taiwan's policy rate of 1.375% is already extremely low, and is only 12.5 bps above the level that prevailed during the worst of the global financial crisis. Second, panels 2 and 3 suggests that while past central bank intervention was successful at depreciating the TWD, monetary authorities also seem reluctant to allow Taiwan to be labeled as a currency manipulator. Our proxy for central bank intervention is the rolling 3-month average daily depreciation in TWD/USD in the first 30 minutes of aftermarket trading, a period that the central bank has historically used to intervene in the foreign exchange market. The chart shows that periods of intervention have been associated with a subsequent decline in TWD/USD, but that intervention durably ended once Taiwan was added to the U.S. Treasury's watch list of potential currency manipulators (first vertical line). Taiwan was removed from the watch list in October of this year (second vertical line), after central bank intervention ceased. Chart 7Currency Strength Not Supported ##br##By Fundamentals Chart 8Equity-Oriented Capital Inflows##br## Are Pushing Up The TWD Chart 9Little Room For Policy ##br##To Push Down The Exchange Rate Bottom Line: The appreciation of the TWD from its 2016 low reflects investor inflows rather than bullish fundamentals. While there is scope for further central bank intervention to help depreciate the currency, the risk of a protectionist backlash means that monetary authorities are reluctant to act. The Relative Outlook For Taiwanese Equities Table 1 presents a simple performance attribution analysis for Taiwan's year-to-date stock returns relative to Greater China bourses,2 in an attempt to answer the following question: Has Taiwan underperformed because it is underweight sectors that have outperformed, or because its highly-weighted sectors underperformed? To test this question we calculate a "hypothetical" return for the Taiwanese stock market, which shows what would have occurred if Taiwan's tech and ex-tech sectors had earned the benchmark return instead of their own. Table 1Taiwan's Poor Performance This Year Is Due To Its Tech Sector The table clearly shows that Taiwan would have substantially outperformed Greater China in this hypothetical scenario, underscoring that its sector weighting is not the source of the underperformance. While both Taiwan's tech and ex-tech indexes underperformed those of Greater China, it is apparent that most of the gap in performance can be linked to Taiwan's tech sector. Tech accounts for roughly 60% of Taiwan's equity market capitalization, and the sector significantly underperformed Greater China tech this year. Chart 10 highlights that Taiwan's tech sector underperformance is significantly explained by the rise in Taiwan's trade-weighted currency. Panels 2 & 3 of the chart shows Taiwan's rolling 1-year tech sector beta and alpha vs Greater China tech, both compared with the (inverted) year-over-year percent change in the trade-weighted exchange rate. Here, we define alpha using Jensen's measure, which is the difference between Taiwan's tech sector price return and what would have been expected given its beta and Greater China's tech sector performance. The chart clearly shows that the sharp rise in Taiwan's trade-weighted exchange rate caused both a decline in Taiwan's tech sector beta (from a historical average of about 1) as well as a significantly negative alpha over the past year. Chart 10, in combination with the currency-driven downtrend in Taiwan's export prices shown in Chart 7, suggests that Taiwan's equity market has suffered in relative terms due to the outsized appreciation in its currency. This is somewhat ironic, as we noted above that the currency appreciation itself appears to be caused by capital inflow oriented towards Taiwan's tech sector, meaning that global investors have inadvertently contributed to Taiwan's equity market underperformance relative to Greater China bourses. Looking forward, there are cross-currents affecting the outlook for Taiwanese stock prices. Chart 11 shows that technical conditions and relative valuation argue against maintaining an underweight stance; Taiwanese stocks are heavily oversold vs Greater China, and have de-rated in relative terms since the beginning of the year. Taiwanese tech in particular is quite cheap in relative terms. In addition, panel 1 of Chart 10 suggests that Taiwanese tech (in relative terms) may have undershot the appreciation in the currency. Chart 10Taiwan's Tech Underperformance Is Explained By Currency Appreciation Chart 11Taiwan Vs China: Oversold, And Cheaper Than Usual However, Taiwan's tech sector is mostly made up of the semiconductors & semiconductor equipment industry group, and there are signs that the growth rate in global semiconductor sales is in the process of peaking. Chart 12 illustrates the close correlation between the growth of global semi sales and Taiwan's absolute 12-month forward earnings per share, with the recent gap likely having occurred due to the currency impact noted above. The chart suggests that earnings expectations for Taiwan are highly unlikely to accelerate if semi sales growth slows, meaning that Taiwanese stocks, particularly the tech sector, currently lack a catalyst to re-rate. Chart12Taiwan Is Lacking A Re-Rating Catalyst From our perspective, a lasting depreciation in the currency appears to be the most likely catalyst for a re-rating, as it would increase the odds that the relationship shown in Chart 10 would durably recouple. Until then, any exogenous rebound in relative tech sector performance is likely to be met with a self-limiting TWD appreciation. Bottom Line: We recommend that investors, for now, stick with our existing long MSCI China / short Taiwan trade. However, a breakout in relative Taiwanese tech sector performance coupled with a weakening TWD would likely cause us to close the trade, and upgrade Taiwanese stocks to at least neutral within a greater China equity portfolio. Stay tuned. Jonathan LaBerge, CFA, Vice President Special Reports jonathanl@bcaresearch.com Lin Xiang, Research Assistant linx@bcaresearch.com 1 Pease see China Investment Strategy Weekly Report "Taiwan's 'Trump' Risk", dated February 2, 2017, available at cis.bcaresearch.com. 2 We use MSCI's Golden Dragon index to represent Greater China, which includes China investable, Hong Kong, and Taiwanese stocks. Cyclical Investment Stance Equity Sector Recommendations
Highlights The growth momentum of China's recent mini-cycle has peaked, but the ongoing slowdown is likely to continue to remain benign in nature. A return to 2015-like conditions is not the most likely outcome over the coming year. Chinese policymakers are likely to increase their focus on reform efforts next year, but the pace will have to be modulated to avoid a repeat of the significant slowdown that occurred in 2014/2015. The risk of a policy mistake is a key theme to watch for 2018. Chinese ex-tech stocks have room to re-rate next year in a benign slowdown scenario. Investors should stay overweight Chinese investable equities vs EM and global stocks. Feature BCA recently published its special year end Outlook report for 2018,1 which described the macro themes that are likely to drive global financial markets over the coming year. In this week's China Investment Strategy report we expand on the Outlook, by reviewing our three key themes for China over the coming year. Key Theme # 1: A Benign End To China's Recent Mini-Cycle We presented our case that the cyclical slowdown of the Chinese economy will likely be benign in our October 12 Weekly Report. Chart 1 presents a stylized view of the Chinese economy over the past three years that was published in that report, which illustrated our framework of how cyclical growth conditions have evolved over this "mini-cycle". It also highlighted three possible scenarios for the coming 6-12 months, and noted that our bet was on scenario 2: A re-acceleration of the economy and a continuation of the V-shaped rebound profile A benign, controlled deceleration and settling of growth into the "stable" growth range, and An uncontrolled and sharp deceleration in the economy that threatens a return to the conditions that prevailed in early-2015 (or worse) Chart 1A Stylized View Of China's Recent "Mini-Cycle" Since we presented this framework, incoming evidence has been consistent with our call. Chart 2 shows that the Li Keqiang index has now decisively rolled over, but that economic conditions remain well away from their mid-2015 lows. We sketched out the basis for our benign slowdown view in our October 12 piece, but we followed up more formally in a two-part report that addressed the main factors arguing against a return to 2015-like conditions.2 Our view is grounded in the perspective that economic conditions in 2015 were not "normal", and we showed in these reports how a sharp slowdown in the economy was caused by an extremely weak external demand environment and overly tight monetary policy. On the trade front, Chart 3 highlights how Chinese export growth is likely to moderate over the coming several months, which argues against the re-acceleration scenario described above. Since mid-2011, Chinese export growth has lagged what most economic indicators would have predicted, and we noted in part I of our 2015 vs today comparison that this can be traced largely to two factors: a decline in global import intensity and, to a lesser extent, a decline in China's export "market share". Chart 2An Economic Slowdown In China##br## Is Now Underway Chart 3Chinese Export Growth Likely To##br## Converge To Global IP Growth Our analysis in that report suggested that China's 2018 export growth will converge to that of global industrial production, which implies a modest deceleration in the months ahead. Still, export growth of +4% would be a far cry from the significant contraction of exports that occurred in late-2015 / early-2016, which is consistent with a benign growth slowdown. On the monetary policy front, we showed how a monetary conditions approach captured the tightness of China's policy stance from 2012 to early-2015, which led to a material decline in China's industrial sector (Chart 4). Our Special Report last week further supported the view that monetary conditions matter enormously for China's economy; out of 40 macro data series that we tested to reliably predict the Chinese business cycle, only measures of money & credit passed our criteria.3 An aggregate indicator of these 6 series has a similar profile to the Bloomberg Monetary Conditions Index that we have shown in the past (Chart 4, panel 2), and neither suggests that a sharp further slowdown in China's economy is imminent. We will be watching these indicators closely in 2018 for signs of a more aggressive decline than we currently expect. Recently, some investors have pointed to a sharp rise in China's corporate bond yields as a sign that the monetary policy stance is, in fact, tighter than a standard monetary conditions approach would imply. Indeed, China's 5-year AA corporate bond yield has risen 230 bps since late-October 2016, from 3.6% to 5.9%, with most of this rise having occurred due to a rise in government bond yields. Corporate bond spreads have also risen, but relative to spreads on similarly-rated U.S. credit, the rise appears to reflect a rebound from extremely low levels late last year and is not (yet) symptomatic of major concerns over defaults (Chart 5). Chart 4The Ongoing Slowdown Is Likely ##br##To Be Benign Chart 5China's Corporate Bond Spreads ##br##Do Not Yet Look Onerous We are not complacent of the potential risk posed by rising corporate bond yields, and a further significant rise in 2018 could change our view that a benign economic slowdown is the most likely outcome. But for now, the fact that the stock of corporate bond issuance accounts for only 10% of ex-equity social financing suggests that the rise in yields this year is not likely to have an outsized impact on the economy in 2018, beyond the impact that monetary tightening has had on overall average interest rates (which, for now, is material but has not returned rates back to their 2015 levels). Chart 6The Rise In CPI Will Likely Soon Peak Finally, the 85 bps rise in Chinese core consumer price inflation that has occurred over the past year has also fed investor concerns that monetary policy will become even tighter next year. To us, this risk is probably overblown, given that demand-driven inflation lags growth (which has clearly peaked). Chart 6 shows the year-over-year change in Chinese core CPI vs that of the Li Keqiang index, and clearly suggests that the acceleration in core prices is likely to soon abate. Poor communication from the PBOC means that it is not clear how prominently core inflation features into the central bank's reaction function, but given that tighter monetary conditions have already caused a peak in both house prices and growth momentum, we doubt that policymakers will see the recent rise in consumer prices as a basis to aggressively tighten further. Bottom Line: The growth momentum of China's recent mini-cycle has peaked, but a return to 2015-like conditions is not the most likely outcome over the coming year. Key Theme # 2: Monitoring The Pace Of Renewed Structural Reforms We have written several reports concerning China's 19th Communist Party Congress over the past three months, both in the lead-up to the event and as a post-mortem.4 The Congress was significant because it likely heralds stepped-up reform efforts in 2018 and beyond. By "reforms", our Geopolitical Strategy team specifically means deleveraging in the financial sector accompanied by a more intense anti-corruption campaign focused on the shadow-banking sector, as well as ongoing restructuring in the industrial sector. Table 1 presents our geopolitical team's assessment of the likely reform scenarios and probabilities over the coming year. It should be clearly noted that the "reform reboot" scenario as described in Table 1 is likely negative for emerging market equities and other plays on China's industrial sector (such as industrial metals). Table 1Post-Party Congress Scenarios And Probabilities We agree that the "status quo" scenario of no significant reforms is highly unlikely given that President Xi has succeeded in amassing tremendous political capital and that he has an agenda for reform. But the intensity of reforms pursued over the coming year will have to be closely monitored by policymakers, to avoid a repeat of the significant slowdown that occurred in 2014/2015. As such, the view of BCA's China Investment Strategy service is that the reform efforts over the coming year will be structured at a pace that is sufficient to avoid a meaningful deceleration in China's industrial sector and is conducive to the outperformance of Chinese ex-technology stocks. However, the potential for a brisk pace of reforms to cause a more acute decline in industrial activity in 2018 is a risk to our view that China's ongoing economic slowdown is likely to be benign and controlled. We presented our framework for monitoring this risk in our November 16 Weekly Report,5 specifically our BCA China Reform Monitor (Chart 7). The monitor is calculated as an equally-weighted average of four "winner" sectors that outperformed the investable benchmark in the month following the Party Congress relative to an equally-weighted average of the remaining seven sectors. Significant underperformance of "loser" sectors could become a headwind for broad MSCI China outperformance (especially ex-tech), and we will be watching in 2018 for signs that our monitor is rising largely due to outright declines in the denominator. Chart 7Our Reform Monitor Will Help Us Judge ##br##Whether The Pace Of Reforms Becomes Too Burdensome For now, there is no indication that reform risk is affecting the performance of the MSCI China index. Panel 2 of Chart 7 highlights that recent movements in our Reform Monitor have been driven by the "winner" sectors, with the recent selloff largely reflecting a modest correction in global technology stocks sparked by the passage of the U.S. Senate's tax reform plan.6 But we will be watching the monitor closely in 2018, and will adjust it as needed in reaction to additional reform announcements over the coming months. Finally, next year's reform announcements will be highly significant not just because of the "what", but also the "how". It is difficult to see how China's leadership can aggressively pare back heavy-polluting industry and deleverage the financial sector without destabilizing the economy in the near term, but their goal to significantly raise China's per capita GDP and escape the "middle income trap" over the long-term is equally nebulous. We have noted in previous reports that a country's income level is fundamentally determined by its productivity, which is in turn determined by the level and sophistication of its capital stock. Chart 8 shows a clear positive correlation between a country's per capita output, a measure of productivity, and its per capita capital stock. In general, industrialized countries enjoy much higher levels of per capita capital stock than developing economies, leading to much higher productivity, income, and living standards. Therefore, the process of industrialization is fundamentally a process of accumulation of capital stock through investment. As shown in Chart 9, despite some remarkable achievements, the productivity level of the average Chinese worker is still just a fraction of the level in more advanced countries. Conventional economics would suggest that if China wishes to keep progressing on the productivity and income ladder, that it should remain on the path of growing the capital stock through savings and investment. If, however, it abandons its current growth model and "rebalances" towards a consumption-driven one, the risk that the country will stagnate and fail to advance beyond the "middle income trap" looms large. Chart 8Productivity Is Positively Correlated ##br##With Capital Stock Chart 9China's Catchup Process ##br## Has A Lot Further To Run Chart 10 makes this point from a different perspective. At root, China's leadership is describing the desire to rapidly transition towards an economy with a much higher level of tertiary industry (services) as a share of GDP, but the U.S. experience suggests that this is a long process that is not investment-oriented. The chart shows the evolution of U.S. investment in private services excluding real estate as a share of total private fixed assets since 1947, when the U.S. had only a slightly higher level of real per capita GDP than China today. It has taken almost 70 years for the share of private services ex real estate to rise by 16 percentage points in the U.S., and it has yet to account for the majority of private fixed investment.7 Services activity/investment also typically requires a highly educated workforce as an input, and rate of China's post-secondary educational attainment appears to be too low to fit the bill (Chart 11). In short, crucial details about China's reform plan should hopefully emerge in 2018, which are likely to have both near-term and multi-year implications. Bottom Line: Chinese policymakers are likely to increase their focus on reform efforts next year, but the pace will have to be modulated to avoid a repeat of the significant slowdown that occurred in 2014/2015. The risk of a policy mistake is a key theme to watch for 2018. Chart 10China Cannot Easily Replace 'Hard' Investment Chart 11China's Workforce Is Not Well Equipped To Transition To Services Key Theme # 3: The Relative Re-Rating Of Chinese Investable Ex-Tech Stocks Over the past several years, this publication argued strongly that the valuation discount applied to Chinese equities was unjustified. For the investable benchmark, the past two years of material outperformance vs emerging market and global stocks has removed a significant portion of this discount, and we noted in our August 31 Weekly Report that Chinese equities are no longer "exceptionally cheap".8 However, a good portion of this revaluation has been isolated to the tech sector. Chart 12 shows that while the 12-month forward P/E ratio for Chinese tech stocks is 70% higher than the global average, ex-tech shares still trade at a 37% relative discount. Chart 13 echoes this conclusion by showing the ex-tech price-to-book ratio for every country in MSCI's All Country World index; by this metric China's ex-tech cheapness currently ranks in the 85th percentile, behind only Israel, Colombia, Italy, Jordan, Korea, Russia, and Greece. Chart 12China: Expensive Tech, Extremely Cheap Ex-Tech Chart 13China's Ex-Tech P/B Ratio Among The Lowest In The World Charts 12 and 13 are weighted simply by the remaining market capitalization in each country's market after excluding the technology sector, meaning that the deep discount applied to Chinese banks wields a disproportionate influence (financials would make up 40% of China's MSCI ex-tech "index", if one officially existed). Although we agree that the magnitude of the rise in debt over the past several years warrants somewhat of a P/B discount, we would argue that the risk is more earnings and dilution-related rather than solvency-related. It is highly unlikely that the Chinese government would allow large banks to fail outright in the event of a serious financial crisis, but the potential for a rise in provisioning and significant new capital raising suggests that the risk premium for these stocks should be somewhat higher than what would otherwise be normal. Chart 14China's Banks Can Re-Rate ##br##In A Benign Slowdown Scenario Still, either the Chinese bank risk premium is excessive, or the banking sectors of several major DM countries are significantly overvalued. For example, Chinese investable banks trade at a P/B ratio of 0.8, but Canadian, Australian, and Swedish banks trade at an average P/B ratio of 1.7. If the concern over credit excesses is the source of the higher risk premium applied to Chinese banks, Chart 14 suggests that there is a major inconsistency in pricing; an equally-weighted average of Canadian, Australian, and Swedish private sector debt-to-GDP is higher than that of China's, at 214% vs 211% as of Q2 this year. Our bet is the former: In a world where outsized returns are scarce and U.S. equities are overvalued, a benign growth deceleration and a modulated pace of reforms favor a lessening of the substantial valuation discount currently applied to China's investable ex-tech stocks. Barring a more pronounced slowdown in China's economy than we currently expect, investors should stay overweight the MSCI China investable index in 2018, within both an emerging markets and global equity portfolio. Bottom Line: Chinese ex-tech stocks have room to re-rate in a benign slowdown scenario. Investors should stay overweight Chinese investable stocks in 2018. Jonathan LaBerge, CFA, Vice President Special Reports jonathanl@bcaresearch.com 1 Please see BCA Special Report, "2018 Outlook - Policy And The Markets: On A Collision Course," dated November 20, 2017, available at cis.bcaresearch.com. 2 Please see China Investment Strategy Weekly Reports "China's Economy - 2015 Vs Today (Part I): Trade", dated October 26, 2017, and "China's Economy - 2015 Vs Today (Part II): Monetary Policy", dated November 9, 2017, available at cis.bcaresearch.com. 3 Please see China Investment Strategy Special Report, "The Data Lab: Testing The Predictability Of China's Business Cycle", dated November 30, 2017, available at cis.bcaresearch.com. 4 Please see China Investment Strategy and Geopolitical Strategy Special Reports, "China's Nineteenth Party Congress: A Primer", dated September 14, 2017, "How To Read Xi Jinping's Party Congress Speech", dated October 18, 2017, and BCA Special Report "China: Party Congress Ends ... So What?", dated November 2, 2017, available at cis.bcaresearch.com. 5 Please see China Investment Strategy Weekly Report, "Messages From The Market, Post-Party Congress", dated November 16, 2017, available at cis.bcaresearch.com. 6 The Senate bill that was passed this week unexpectedly retained 20% alternative minimum tax (AMT) for corporations, which would disproportionately impact U.S. technology companies. Indications currently suggest that the final tax cut bill to be approved by both houses of Congress will repeal the AMT. 7 In 2016, real estate investment accounted for roughly 29% of total private investment in fixed assets, and the sum of primary and secondary industry (agriculture, mining, utilities, construction, and manufacturing) accounted for about 28%. 8 Please see China Investment Strategy Weekly Report, "A Closer Look At Chinese Equity Valuations", dated August 31, 2017, available at cis.bcaresearch.com. Cyclical Investment Stance Equity Sector Recommendations