Sectors

Highlights Chart 1Too Close For Comfort The Fed is in the midst of tightening policy, but with inflation still below target it wants to ensure that overall policy settings remain accommodative. In the language of central bankers, the Fed wants to keep the real fed funds rate below its equilibrium level, the level that applies neither upward nor downward pressure to price growth. The equilibrium fed funds rate cannot be calculated with precision, but one popular estimate shows that policy settings are dangerously close to turning restrictive (Chart 1). While an announcement of balance sheet reduction is almost certain to occur next month, with the real fed funds rate so close to neutral, rate hikes are probably on hold until the gap widens. Higher inflation will widen the gap by causing the real fed funds rate to fall, and we are confident that core inflation will rise in the coming months (see page 11 for further details). This will permit the Fed to deliver more than the currently discounted 28 bps of rate increases during the next 12 months. Feature Investment Grade: Overweight Chart 2Investment Grade Market Overview Investment grade corporate bonds outperformed the duration-equivalent Treasury index by 60 basis points in July, bringing year-to-date excess returns up to 209 bps. The financial press is littered with stories highlighting extremely unattractive corporate bond valuations, but we think this storyline is exaggerated. In fact, the average spread on the Bloomberg Barclays corporate bond index is somewhat wider than is typically observed in the early stages of a Fed tightening cycle (Chart 2). We calculate that in the early stages of the prior two Fed tightening cycles (February 1994 to July 1994 & June 2004 to December 2005), the index option-adjusted spread averaged 86 bps and traded in a range between 66 bps and 104 bps.1 Viewed in this context, the current spread of 102 bps looks somewhat cheap. That being said, corporate balance sheet health is worse than is typically seen during the early stages of a tightening cycle and this will limit spread compression from current levels. But all in all, excess returns to corporate bonds should be consistent with carry during the next 6-12 months, with higher inflation and tighter Fed policy being pre-conditions for material spread widening. In a recent report2 we showed that bank bonds (both senior and subordinate) still offer a spread advantage compared to other similarly risky sectors (Table 3). Banks also continue to make progress shoring up their balance sheets and the outlook for bank profits is starting to brighten. Table 3ACorporate Sector Relative Valuation And Recommended Allocation* Table 3BCorporate Sector Risk Vs. Reward* High-Yield: Overweight Chart 3High-Yield Market Overview High-Yield outperformed the duration-equivalent Treasury index by 83 basis points in July, bringing year-to-date excess returns up to 448 bps. The index option-adjusted spread tightened 12 bps to end the month at 352 bps, 8 bps above the 2017 low. We calculate that in the early stages of the prior two Fed tightening cycles (February 1994 to July 1994 & June 2004 to December 2005), the index option-adjusted spread averaged 342 bps and traded in a range between 259 bps and 394 bps. This puts the current junk spread almost in line with the average witnessed during other similar monetary environments. In contrast, the VIX index, which co-moves with junk spreads (Chart 3), is well below levels seen during the early stages of the prior two tightening cycles. The VIX currently sits at 10, and its historical range in similar monetary environments is between 11 and 17, with an average of 13.3 In this way, there would appear to be more room for investment grade corporate bond spreads to tighten than junk spreads, especially on a volatility-adjusted basis. Despite somewhat more stretched valuations than in investment grade, high-yield still offers reasonable compensation relative to expected defaults. At present, our estimated default-adjusted spread is 206 bps, only slightly below its historical average (panel 3). This is based on an expected default rate of 2.8% during the next 12 months and an expected recovery rate of 48% (bottom panel). MBS: Underweight Chart 4MBS Market Overview Mortgage-Backed Securities outperformed the duration-equivalent Treasury index by 24 basis points in July, bringing year-to-date excess returns up to 4 bps. The conventional 30-year MBS yield declined 3 bps in July, as a small 1 bp increase in the rate component was offset by a 4 bps tightening of the option-adjusted spread (OAS). The compensation for prepayment risk (option cost) held flat. Index OAS has been in a widening trend since bottoming at 15 bps last September (Chart 4). Since then, MBS have returned 43 bps less than duration-equivalent Treasury securities. The Bloomberg Barclays Aaa-rated Credit index has outperformed Treasuries by 71 bps during that same timeframe. The back-up in OAS reflects, in large part, the market pricing in the upcoming wind-down of the Fed's balance sheet, set to be announced next month. However, we think OAS still have further to widen to catch up with the rising trend in net issuance. According to Flow of Funds data, net MBS issuance totaled $83 billion in the first quarter. If that pace continues for the rest of the year, then 2017 will be the strongest year for MBS issuance since 2009. While higher mortgage rates since the end of 2016 present a drag, at least so far, home sales have not shown much weakness (bottom panel). This is unlike the 2013 taper tantrum when home sales fell sharply following the surge in rates. We are underweight MBS on the expectation that the housing market will remain resilient in the face of higher rates, allowing issuance to continue its uptrend. However, we are closely tracking the spread advantage in MBS compared to Aaa-rated credit which is finally starting to look attractive (panel 3). Government-Related: Underweight Chart 5Government-Related Market Overview The Government-Related index outperformed the duration-equivalent Treasury index by 42 basis points in July, bringing year-to-date excess returns up to 149 bps. Sovereigns and Local Authorities outperformed the Treasury benchmark by 81 bps and 112 bps, respectively. The low-beta Supranational and Domestic Agency sectors each outperformed by 5 bps. The Foreign Agency sector outperformed the duration-matched Treasury index by 56 bps. USD-denominated sovereign bonds have underperformed the Baa-rated U.S. Corporate index (their closest comparable in terms of risk) during the past three months even though the U.S. dollar has continued its trend lower (Chart 5). But despite this recent underperformance, the Sovereign index still does not offer a spread advantage over the Baa-rated U.S. Corporate index (panel 3). Further, while our Emerging Markets Strategy service still looks favorably upon the Mexican peso relative to other emerging market currencies, it does not expect the peso to continue its recent appreciation versus the U.S. dollar.4 We share this opinion, and expect the broad trade-weighted dollar to appreciate as U.S. growth rebounds in the back-half of the year.5 In our cross-sectional model, which adjusts spreads for credit rating and duration. Local Authorities and Foreign Agencies continue to look attractive compared to most U.S. corporate sectors. In contrast, the Sovereign and Supranational sectors appear expensive. Municipal Bonds: Underweight Chart 6Municipal Market Overview Municipal bonds outperformed the duration-equivalent Treasury index by 38 basis points in July (before adjusting for the tax advantage). Munis have outperformed the Treasury benchmark by 186 bps year-to-date. The average Municipal / Treasury (M/T) yield ratio fell 2% in July, breaking below 85%. The average yield ratio remains extremely tight relative to its post-crisis trading range (Chart 6). There is more compensation available at the long-end of the muni curve than at the short-end (panel 2), and investors should continue to favor long maturities over short maturities on the Aaa Muni curve. Our early estimate, based on the recently released second quarter National Accounts data, shows that state & local government net borrowing probably moved higher in Q2 (panel 3), making the recent decline in yield ratios appear even more tenuous. The increase in net borrowing stems largely from a $21 billion drop in income tax revenues and a $20 billion decline in transfer receipts from the federal government. Income tax revenue should recover in the next two quarters,6 and we expect net borrowing will also start to decline. However, it is unlikely that net borrowing will fall by enough to justify current muni valuations. On July 6, the state House of Illinois overrode Governor Bruce Rauner's veto to finally pass a $36 billion budget. The move was sufficient for Moody's and S&P to both subsequently affirm the state's investment grade rating. The 10-year Illinois General Obligation bond yield declined 102 bps on the month, despite only a 1 bp drop in the 10-year Treasury yield. Treasury Curve: Favor 5-Year Bullet Over 2/10 Barbell Chart 7Treasury Yield Curve Overview The Treasury curve bull steepened in July. The 2/10 slope steepened 3 bps and the 5/30 slope steepened 10 bps. We currently recommend two tactical trades designed to profit from movements in the Treasury curve. First, we have been recommending a short position in the July 2018 fed funds futures contract since July 11.7 From current levels, we calculate this trade will deliver an un-levered return of 28 bps if there are two hikes between now and then, and 53 bps if there are three hikes. Our second recommendation is a long position in the 5-year bullet versus a short position in a duration-matched 2/10 barbell, a trade designed to profit from a steepening of the 2/10 yield curve. It remains our view that inflation and inflation expectations, and not Fed tightening, are the main determinants of the slope of the yield curve. We expect the 2/10 slope to steepen as inflation rebounds during the next few months. Two weeks ago we published a Special Report 8 that explained our rationale for taking views on the slope of the curve using butterfly trades. It also explained our butterfly spread valuation model, and how we use that model to determine how much steepening/flattening is currently discounted in the yield curve. According to our model, the curve is priced for 9 bps of 2/10 steepening during the next six months (Chart 7). Our recommended butterfly trade will earn positive returns if the curve steepens by more than that. TIPS: Overweight Chart 8TIPS Market Overview TIPS outperformed the duration-equivalent nominal Treasury index by 39 basis points in July. The 10-year TIPS breakeven inflation rate rose 9 bps on the month and, at 1.8%, it remains well below its pre-crisis trading range of 2.4% to 2.5%. Core inflation has moved sharply lower since February, but the fact that our Phillips Curve model of core inflation has not rolled over makes us inclined to view the downtrend as transitory. Also, during the past few weeks we have seen some preliminary signs that inflation is on the cusp of rebounding. Year-over-year core PCE inflation ticked higher in June for the first time since January. The PCE diffusion index, which has a good track record capturing near-term swings in core PCE, moved sharply higher (Chart 8). The prices paid components of the ISM manufacturing and non-manufacturing surveys increased from 55 to 62 and from 52.1 to 52.7, respectively, in July. We expect stronger realized inflation will lead TIPS breakevens higher during the next few months. However, even in a scenario where core inflation fails to rebound, the downside in breakevens from current levels is limited. The reason is that if inflation remains very low, the Fed will most likely refrain from hiking rates in December. Such a dovish capitulation from the Fed would put upward pressure on breakevens at the long-end of the curve. We discussed this possible scenario in more detail in a recent report.9 ABS: Overweight Chart 9ABS Market Overview Asset-Backed Securities outperformed the duration-equivalent Treasury index by 5 basis points in July, bringing year-to-date excess returns up to 59 bps. The index option-adjusted spread for Aaa-rated ABS held flat on the month, and remains well below its average pre-crisis level. The Federal Reserve released its Q2 Senior Loan Officer Survey last week. It showed that credit card lending standards moved back into "net tightening" territory after having eased the previous quarter (Chart 9). Auto loan lending standards tightened on net for the fifth consecutive quarter. Tightening lending standards are usually a response to deteriorating credit quality, and thus tend to correlate with higher losses and wider spreads. In that regard, net loss rates for auto loans continue to trend higher, and Moody's data show that the cumulative loss rate for prime auto loans originated in 2017 is worse than for any vintage since 2009, for loans with the same age. Conversely, the mild tightening in credit card lending standards has so far not translated into rising charge-offs (Chart 9), but the situation bears close monitoring. For now, we are content to remain overweight ABS given the attractive spread pick-up compared to other similarly risky sectors. However, we also recommend investors favor Aaa-rated credit cards over Aaa-rated auto loans, even though auto loans now once again offer an attractive spread differential, after adjusting for differences in duration and spread volatility (panel 3). Non-Agency CMBS: Underweight Chart 10CMBS Market Overview Non-agency Commercial Mortgage-Backed Securities outperformed the duration-equivalent Treasury index by 39 basis points in July, bringing year-to-date excess returns up to 96 bps. The index option-adjusted spread for non-agency Aaa-rated CMBS tightened 4 bps on the month, and remains below its average pre-crisis level. The Fed's Q2 Senior Loan Officer Survey showed that lending standards for all classes of commercial real estate (CRE) loans tightened, on net, for the eighth consecutive quarter. The survey also reported that demand for CRE loans is on the decline (Chart 10). The combination of tighter lending standards and weak loan demand suggests that credit concerns continue to mount in the private CMBS space. Agency CMBS: Overweight Agency CMBS outperformed the duration-equivalent Treasury index by 11 basis points in July, bringing year-to-date excess returns up to 65 bps. The average option-adjusted spread for the Agency CMBS index held flat on the month but, at 49 bps, the sector continues to look attractive compared to other similarly risky alternatives.10 Not only does the sector offer attractive spreads, but the agency guarantee and the lower delinquency rate in multi-family loans compared to other CRE loans (panel 5) makes its risk/reward profile particularly appealing. Treasury Valuation Chart 11Treasury Fair Value Models The current reading from our 2-factor Treasury model (which is based on Global PMI and dollar sentiment) places fair value for the 10-year Treasury yield at 2.62% (Chart 11). Our 3-factor version of the model, which also includes the Global Economic Policy Uncertainty Index, places fair value at 2.63%. The U.S. PMI bounced back in July, after having trended lower for most of this year. The Chinese PMI also increased last month, while the Eurozone reading moderated somewhat from a very high level (panel 4). Overall, the Global PMI came in at 52.7 in July, up from 52.6 in June. Bullish sentiment toward the U.S. dollar has also fallen sharply in recent weeks (bottom panel). Bearish dollar sentiment in an environment of expanding global growth sends a very bond-bearish signal. It means that the entire world is participating in the global expansion and any increase in Treasury yields is less likely to be met with an influx of foreign buying. For further details on our Treasury models please refer to the U.S. Bond Strategy Weekly Report, "The Message From Our Treasury Models", dated October 11, 2016, available at usbs.bcaresearch.com At the time of publication the 10-year Treasury yield was 2.26%. Ryan Swift, Vice President U.S. Bond Strategy rswift@bcaresearch.com Alex Wang, Research Analyst alexw@bcaresearch.com 1 Range calculated using monthly data, specifically the final day of each month. 2 Please see U.S. Bond Strategy Weekly Report, "Summer Snapback", dated July 11, 2017, available at usbs.bcaresearch.com 3 Ranges for junk spread and VIX calculated using monthly data, specifically the final day of each month. 4 Please see Emerging Markets Strategy Weekly Report, "The Case For A Major Top In EM", dated July 12, 2017, available at ems.bcaresearch.com 5 Mexico carries the largest weight in the Sovereign index, accounting for 23% of market cap. 6 Please see U.S. Bond Strategy Weekly Report, "Will The Fed Stick To Its Guns?", dated May 16, 2017, available at usbs.bcaresearch.com 7 Please see U.S. Bond Strategy Weekly Report, "Summer Snapback", dated July 11, 2017, available at usbs.bcaresearch.com 8 Please see U.S. Bond Strategy Special Report, "Bullets, Barbells And Butterflies", dated July 25, 2017, available at usbs.bcaresearch.com 9 Please see U.S. Bond Strategy Weekly Report, "Three Scenarios For Treasury Yields In 2017", dated June 20, 2017, available at usbs.bcaresearch.com 10 Please see U.S. Bond Strategy Weekly Report, "Risk Rally Extended", dated June 27, 2017, available at usbs.bcaresearch.com Fixed Income Sector Performance Recommended Portfolio Specification Corporate Sector Relative Valuation And Recommended Allocation Total Return Comparison: 7-Year Bullet Versus 2-20 Barbell (6-Month Investment Horizon)

Highlights July jobs report friendly for risk assets. Q2 earnings and July ISM confirm bullish profit environment. The Fed acknowledges softer inflation, but remains determined to tighten policy. 1H economic growth is just enough for the Fed. Housing weakness in Q2 is not a concern. Feature Chart 1Labor Market Conditions Favor Risk Assets The July jobs report suggests that the environment of solid economic growth and still muted wage pressures remains in place, a positive backdrop for equity markets. The report showed that the economy added 209,000 jobs in July, well above the consensus forecast of 178,000. Prior months were also revised higher by 2,000 pushing the 3-month moving average up to 195,000 jobs per month. Monthly job gains thus far in 2017 are nearly identical to the 187,000 jobs per month averaged in 2016. Despite an uptick in the participation rate to 62.9% from 62.8%, the unemployment rate dipped by 0.1% to 4.3%. At two decimal points, the dip in the jobless rate was from 4.36% to 4.35%. Although the monthly increase ticked up to 0.3%, the annual increase in average hourly earnings was flat at 2.5% for the fourth consecutive month (Chart 1). Nonetheless, the reacceleration in the 3-month change in average hourly earnings from 1.9% in January 2017 to 2.8% in July supports the Fed's view on inflation. Bottom Line: The July employment report paints a fairly stable picture of the U.S. economy. Job gains are continuing at a pace consistent with the 2% GDP growth rate of recent years. Meanwhile, wage gains remain modest and consistent with muted inflation. We still expect the Fed to announce the process of running down its balance sheet at the September FOMC meeting. The next rate hike will likely come at the December FOMC meeting, if inflation rebounds in the second half of the year. Steady growth, low inflation and a gentle Fed should continue to underpin U.S. risk assets. Q2 Earnings Update: Margin Expansion In Place EPS and sales growth in Q2 are running well ahead of consensus expectations as forecasted in our July 3 preview. Moreover, the counter trend rally in profit margins is still in place. More than 80% of companies have reported results so far with 73% of companies beating consensus EPS projections, just above the long-term average of 70% (Chart 2). Furthermore, 68% have posted Q2 revenues that exceeded expectations. The surprise factor for Q2 stands at 6% for EPS and 1% for sales. We anticipate the secular mean-reversion of margins to ultimately re-assert itself in the S&P data, perhaps beginning early in 2018. Nonetheless, over the nearer term, results thus far imply that Q2 will see another quarter of margin expansion. Average earnings growth (Q2 2017 versus Q2 2016) is strong at 12% with revenue growth at just 5%. The BCA Earnings model predicts EPS growth to hit roughly 24% later this year on a 4-quarter moving total basis, before moderating in 2018 (Chart 3). Measured on this basis, S&P 500 EPS growth in Q2 would be 20%, compared with 13% in Q1. Chart 2Positive Earnings Surprises Continue Chart 3Strong EPS Growth Ahead Importantly, the strength in earnings and revenues is broadly based (Table 1). Earnings per share are higher in Q2 2017 versus Q2 2016 in all 11 sectors. Results are particularly strong in energy, technology and financials. Energy revenues surged by 15.7% in Q2 versus a year ago. Sales gains in technology (8.2%), materials (7.2%) and utilities (5.7%) are notable. Since the start of 2017, the trajectory of EPS estimates for 2017 and 2018 (Chart 4) has been encouraging. The forecast for 2017 is 12%, up from 11% at the outset of the Q2 reporting season and unchanged from the start of the year. The 2018 estimate (11%) is also little changed from estimates made in January 2017. In a typical year, earnings estimates tend to move lower as the year progresses. Table 1S&P 500:##BR##Q2 2017 Results* Chart 4Stability In '17 & '18 EPS##BR##Estimates Supports U.S. Equities BCA's U.S. Equity Strategy service noted1 that the lagged effect from a softening U.S. dollar will also likely underpin EPS in the back half of the year. We are surprised that mentions of the greenback are absent from Q2 conference calls; the domestic market appears front of mind for both investors and management teams. We are inclined to see fading concerns about the dollar from the next Beige Book (due in early September) as evidence in favor of our colleagues' view. The July reading of the ISM manufacturing Index supports our case for accelerating profits in the second half of 2017. From the perspective of risks to our stance, industrial production (IP) has historically been a good proxy for sales of S&P 500 companies (Chart 5); and a rollover in the 12-month change in IP would challenge our constructive view towards earnings. However, strong readings on the ISM, which tracks IP, suggest that IP should accelerate in the next six months (Chart 5, panel 1). Chart 5Favorable Macro Backdrop For Earnings And Sales At 56.3 in July, the ISM has rebounded from its recent low of 47.9 in 2015, but ticked down from the 57.8 reading in June. For many investors, the risk is that the index has peaked and will soon roll over. While a decline is certainly possible given that the index is already elevated, the leading components of the ISM, including the new orders index and the new orders-to-inventory ratio, indicate that the ISM will remain above 50 in the months ahead (Chart 6). Moreover, the new export orders component of the ISM has also surged. The implication is that foreign demand (rather than domestic consumer or business spending) is leading the U.S. manufacturing sector. Consistent with this perspective, the 3- and 12-month changes in the industrial production indices in advanced economies outside the U.S. have outpaced domestic growth (Chart 7). Chart 6IP Poised To Accelerate##BR##And Support EPS Growth Chart 7U.S. IP Growth Still##BR##Other Developed Markets Bottom Line: EPS growth will continue to accelerate through the end of 2017 and into early 2018, aided by a period of margin expansion and decent top-line growth. The elevated level of ISM sets the stage for EPS growth to gather momentum in the second half of 2017. Firm readings on ISM indicate that our bullish profit story for 2017 is still intact, supporting an overweight stance towards stocks versus bonds. Fed Still On Track The July FOMC statement supports our view that the Fed will announce plans to shrink its balance sheet at the September FOMC meeting and hold off until December for the next rate hike. Policymakers upgraded their views of the labor market and downgraded their assessments of inflation. The reference to job gains moderating was dropped; instead, the Fed noted that employment growth has been robust. On inflation, the Fed stated that it is "running below" 2%, as opposed to "somewhat below" 2% in the June statement. These are only small tweaks and do not suggest any deviation from the Fed's plan to raise rates one more time this year as per its latest "dot plot" published in June. We still see the next rate hike in December if inflation begins to turn higher and shows signs of heading towards the 2% target. While the Fed is on the sidelines regarding rate hikes until the final meeting of 2017, it is creeping closer to begin shrinking its balance sheet. The July FOMC statement announced that the balance sheet normalization process will begin "relatively soon." The Fed had previously stated that the process would commence "this year." We view this shift in language as a signal that the balance sheet announcement will be made at the September meeting. Hesitation on tapering by the ECB, persistently weak readings on U.S. inflation or a tightening of U.S. financial conditions, would also give the Fed reason to reassess its plan. Bottom Line: Slight variations in the FOMC's statement indicate that rates are on hold at least until December. This will give the Fed time to determine whether inflation is moving back to its target and to assess the market impact of shrinking its balance sheet. 1H GDP: Just Enough U.S. GDP grew by 2.6% in Q2, following a revised 1.2% advance in Q1 (Chart 8). Given the potential distortions to the quarterly data from residual seasonality issues, an average of the first two quarters gives a better reading on the underlying trend in the economy. In the first half of this year, growth averaged 1.9%. On a year-over-year basis, the economy grew by 2.1%, and while that is only in line with the Fed's 2.1% forecast for 2017, it is above the central bank's view of 1.8% GDP growth in the "longer run." In addition, the NY Fed's Nowcast for Q3 is 2.0% and the Atlanta Fed's GDP now reading for Q3 is 3.7%. Moreover, in years when Q1 GDP is weak, 2H growth is faster than 1H growth 70% of the time.2 Quarterly GDP has averaged 2.2% since the current expansion started in the second half of 2009. Chart 8GDP Growth Remains Below Average, But Above Fed's Long Run Target Looking beyond the quarterly fluctuations, the U.S. economy has been relatively stable at about 2% growth for nearly 10 years. This advance has been sufficient to lower unemployment, with trend GDP growth slowing due to weak productivity gains and demographics. However, the expansion has not yet led to a material acceleration in wage growth or inflation. Inflation, a lagging indicator, warrants more attention from investors. BCA's Global Investment Strategy,3 team recently argued that both cyclical and structural forces will boost inflation in the next year and far into the next decade. In making this assessment, it was noted that inflation typically does not peak until well after a recession has begun and does not bottom until well after it has ended. The implication is that inflation could stay subdued for the next 12 months as the labor market slowly overheats, before moving higher in the second half of 2018. This also suggests that the central bank already may be behind the curve on raising rates. The implication for investors is to stay below-benchmark overall portfolio duration and favor corporate credit over government bonds over the rest of 2017. Bottom Line: Despite historically weak readings on economic growth, the U.S. economy is advancing quickly enough to reduce slack and ultimately, push up inflation. We agree with the Fed that gradual increases will forestall more aggressive hikes later in the cycle. Strong Housing Sector Dips In Q2 We expect housing to continue to add to GDP growth in 2017 and beyond. Housing - as measured by residential fixed investment - subtracted 0.27% from GDP growth in Q2 2017. However, since early 2011, the sector has contributed to growth in 20 of 25 quarters. Moreover, the Q2 decline appears to be a one off, with all of the weakness coming in "other structures," which measures broker commissions, manufactured housing and home improvement. The more economically sensitive single-family sector added 0.31% to GDP in Q2. There are few signs of the severe imbalances in housing and housing-related debt that sparked the 2007-2009 global financial crisis. Chart 9 shows that housing investment is running behind other long "slow burn" recoveries.4 These recoveries lasted well beyond the point at which the economy hit full employment, and inflationary pressures were also slower to emerge. The housing sector's lag is not surprising given the bloated inventory of vacant, unsold and foreclosed homes that needed to be absorbed in the early part of this recovery. Chart 10 shows the overhang has disappeared. Moreover, recent anecdotal reports suggest that the limited supply of homes in areas where people want to live is hurting sales. Chart 9We Are In A "Slow Burn" Expansion Chart 10Solid Housing Fundamentals In Place Other positive factors for housing include: A rise in FICO scores, which indicates that more renters now qualify for loans and could move from a rental unit to a single family house. We highlighted this factor in a recent Special Report on housing.5 Housing affordability: although off its all-time high, it remains favorable and the cost of owning remains cheap relative to renting. The rate of home ownership is now well below its long-term average (Chart 10, panel 2). If the pre-Lehman bubble in the homeownership rate has been unwound, it removes a headwind for construction activity because renting favors multi-family construction that produces less GDP per unit compared with single-family homes. The supply of foreclosed homes on the market is almost nil. While this may not directly impact home construction and GDP directly, it supports higher home prices. Lending standards have not eased much in this cycle, and accordingly, have not been a net plus for the housing market. Nonetheless, more selective mortgage lending by banks in this cycle stands in sharp contrast to the lax lending in the last cycle, with the net result being better credit quality for bank mortgage portfolios and less systemic risk in the banking sector. This is an area the Fed is paying close attention to in this cycle.6 That said, with lending standards tight, there is room for them to loosen and provide an additional boost to housing in the future. Household formation is still recovering from a period in which young adults stayed home with their parents for longer than normal for economic reasons. Although mild by historical standards, the tightening labor market and cyclical rebound in disposable incomes have allowed millennials to move out of their parents' basements, which has boosted housing demand (Chart 11). Chart 12 estimates the remaining pent up demand for housing, based on the deviation from its 1990-2007 trend in the ratio of the number of households to the total population. A closing of the remaining gap implies an extra 540,000 housing units. The equilibrium number of housing starts needed to cover underlying population growth, plus the units lost to scrappage, is estimated at about 1.4 million annually. If the household formation 'catch up' occurs during the next two years, adding another 250,000 units per year, then total demand could be 1.6 to 1.7 million in each of the next two years. This compares with the July housing starts level of 1.2 million. If starts rise smoothly from today's level to 1.7 million at the end of 2018, then the housing sector will contribute about 0.25 percentage points and 0.52 percentage point to real GDP growth in 2017 and 2018, respectively (Chart 13). Chart 11Household Formation##BR##Following Incomes Higher Chart 12A Catch Up In Housing Construction##BR##Will Occur If This Gap Narrows Chart 13Housing Catch Up##BR##Will Boost GDP Growth The implication for the economy is that this already-aged expansion phase could persist for a couple of more years as long as it is not hit by an adverse shock and inflationary pressures remain muted, which would allow the Fed to proceed slowly. Bottom Line: Housing starts remain well below the equilibrium level implied by underlying household formation and a "catch up" phase could stoke the current "slow burn" expansion in the coming years. Residential investment will continue to add to GDP growth in 2017 and beyond, and keep economic growth on track to hit the Fed's modest target. John Canally, CFA, Senior Vice President U.S. Investment Strategy johnc@bcaresearch.com 1 Please see U.S. Equity Strategy Weekly Report "Growth Trumps Liquidity", dated July 31, 2017, available at uses.bcarearch.com. 2 Please see U.S. Investment Strategy Weekly Report "Waiting For The Turn", dated June 26, 2017, available at usis.bcarearch.com. 3 Please see Global Investment Strategy Weekly Report "A Secular Bottom In Inflation", dated July 28, 2017, available at gis.bcarearch.com. 4 Please see The Bank Credit Analyst Monthly Report, dated November 24, 2016, available at bca.bcarearch.com. 5 Please see U.S. Investment Strategy Special Report "U.S. Housing: What Comes Next?", dated March 27, 2017, available at usis.bcarearch.com. 6 Please see U.S. Investment Strategy Weekly Report, "The Fed's Third Mandate", dated July 24, 2017, available at usis.bcaresearch.com.

This week's GDP report contained good news for domestic manufacturers; nonresidential fixed investment expanded at a 5.2% annualized rate in Q2, slower than the 7.2% expansion of Q1 but still well above the overall economy at 2.6%. The implication is that confidence in the U.S. economy is high enough that firms are increasingly deploying productive capital into their businesses. Loan growth cycles are typically synchronous with improved business sentiment which, in turn, coincides with firms feeling confident enough to expand the balance sheet. Accordingly, growth in capex and growth in bank loans move in lockstep (second, third and fourth panels). Pre-GFC, the financials index and capex/loan growth moved broadly together. The relationship has broken down, however, in the post-GFC world. We expect above-normal earnings growth in financials to eventually drive a renormalization of valuation multiples and the gap to close. We reiterate our overweight financials recommendation.

Special Report

Feature This is the first of two Special Reports on Electric Vehicles. In this report, we will look at the current costs of ownership of a typical mass-market EV, including and excluding subsidies, versus a similar Internal Combustion Engine Vehicle (ICEV). Based on current manufacturing costs and battery capabilities, EVs carry a significantly higher total cost per mile, even including current subsidies. Electric Vehicles have galvanized the interest of consumers, investors, and governments for several years now. We touched on the subject in our Special Report "Electric Vehicle Batteries", published September 20, 2016, where we noted that there were many misconceptions regarding batteries in general and EV batteries in particular. Despite the current cost and utility disadvantages of EVs, we expect governments (especially Europe and China) will continue to provide subsidies (carrots) and mandates (sticks) to further the adoption of EVs for the purposes of reducing CO2 emissions and tailpipe particulate pollution. The longer-term hope is that by forcing the EV market to expand, meaningful technological breakthroughs on batteries will eventually enable EVs to exceed ICEVs on a cost and utility basis. In our second report, we will look at the potential issues associated with adoption of EVs and the investment implications for the auto industry and energy markets. Cost Comparison: EV Vs. ICEV We estimated the difference in cost of ownership of a Chevy Bolt EV (known as the Opel Ampera-e in Europe) and two equivalent Internal Combustion Engine Vehicles (ICEVs), the Chevy Sonic and the Opel Astra, over 160,000 km or 100,000 miles (Table 1). Depreciation is an important consideration in cost of ownership, and we expect EVs to depreciate much more rapidly than ICEVs, a cost that many consumers either ignore or simply fail to incorporate into their purchase decisions. Table 1Comparison Of Costs Of Ownership Between EV And ICEV Automobiles There are many unknowns, such as actual selling price, actual manufacturing cost, etc., in this exercise which may add or subtract a thousand dollars or more to the net results. Under realistic assumptions, those probably cancel out. In summary, EVs are more expensive than ICEVs: Excluding subsidies, the net difference is about $16,100 in the U.S., $18,500 in Germany, and $13,200 in France. After subsidies, the difference is about $6,600 in New York State, $13,900 in Germany, and $6,000 in France. Even if electricity were free, after subsidies, the difference in cost of ownership in the U.S. (NY) would be $3,400, $3,200 in Germany, and $600 in France. The U.S. Federal subsidy of $7,500 is designed to be phased out once a manufacturer sells 200,000 vehicles, which would happen quickly if EVs are to become main stream. Therefore, the total premium cost of ownership of an EV over a comparable ICEV in the U.S. should be assumed to be $16,100 less state subsidy, if any. European subsidies are probably more politically acceptable, even though they will become quite costly if EV sales accelerate as many predict. GM is believed to be losing $9,000 with every Bolt it sells. If so, and if GM changed its pricing to deliver the company's average Gross Margin of around 13%, assuming it currently allows a 10% markup by dealers and discounts the vehicle by 10%, the price of the car would need to be raised to around $48,300 from its current MSRP of $37,500. This would increase the cost of ownership by nearly $11,000 (Table 2), or $0.11 per mile. To make the Bolt's ownership costs - after subsidies - competitive with GM's Opel Astra in France, the Bolt's manufacturing costs would need to be cut by about $14,750 or 34%. Table 2Comparison Of Costs Of Ownership Between EV And ICEV Automobiles, ##br##If GM Sold Bolt At Average Corporate Profitability Note that although we have focused on the Bolt, the common denominator for all EVs is the cost of batteries, which are a commodity. As such, our estimates probably hold for similarly sized vehicles and the differential costs of ownership are likely larger for larger EVs. As we will show in Part 2, integrated auto manufacturers probably have a significant cost advantage over "pure play" EV vendors such as Tesla, because outside of the drive train, they are able to use many of the same components they manufacture for ICEVs. Batteries: A Review All assumptions regarding EV technology are predicated on continued improvements in the cost, durability, and performance of batteries. The leading battery technology for EVs is a Lithium Ion technology (Illustration 1), and there really are no proven near-term alternatives worth discussing. Illustration 1Lithium Ion Technology In our Special Report "Electric Vehicle Batteries", we concluded that: Although the consensus view is that EV battery prices have experienced rapid (8 - 14% per annum) price declines over the past few years, we found no evidence to support that position; Battery durability is at least as important as price, and batteries will not likely last much more than 100,000 miles (160,000 km); Planned expansion of EV battery manufacturing capacity may significantly exceed demand by 2020, resulting in the collapse of EV battery prices and heavy losses for battery manufacturers. We continue to stand by those conclusions, and would like to stress that recent stories such as "China Is About to Bury Elon Musk in Batteries"1 and "10 Battery Gigafactories Are Now in the Works and Elon Musk May Add 4 More"2 are more or less consistent with our comment that "even though there is no reason to expect significant price improvements due to technological shifts, battery prices might drop due to oversupply - at least as long as manufacturers are willing to sell batteries at a loss."3 It seems likely now that China may follow the path it took to the solar industry and mass produce batteries, likely at a loss. The exact motivation for them to do so is uncertain, but this would be moot from the perspective of a western auto manufacturer or consumer. Finally A Reliable Battery Price Data Point! As we will demonstrate in Part 2 of our EV report, excluding the cost of the battery, it should be slightly cheaper to manufacture an EV than a similar ICEV. The EV drive train is much simpler and should be less expensive than that of an ICEV (Illustration 2), offset slightly by the need for a somewhat more robust chassis and suspension due to the weight of the battery, the requirement for electric powered air conditioning, and regenerative braking. Illustration 2Key Components Of A Bolt EV Drive Unit The battery is the most expensive part of an EV and responsible for the higher vehicle prices, and that is likely to remain the case even as manufacturing efficiencies allow EV prices to decline. Unfortunately, the cost of EV batteries is subject to much more speculation than should be the case: many articles cite speculative forecasts, projections, anecdotes, and so on, but without hard data backing them up. Fortunately, we finally have a data point: GM lists the cost of the Bolt EV battery pack as $15,734 for a 60 kWh unit, or $262/kWh.4 Some reports claim the battery cells cost $145/kWh,5 however, battery cells are not the same thing as a battery pack, which is a fully assembled unit complete with wiring, electronics, and a cooling system. Peer reviewed research suggests the cost of the battery pack is about 50% greater than the cost of the battery cells,6 however, we note the same article suggests that ratio will remain the same as battery prices drop. This is unlikely as there is no reason to believe the largely mechanical battery pack will decline proportionately any more than the cost of an engine or transmission will decline. Most likely, the battery pack assembly, excluding the cells, will decline only slightly. EV vendors likely oversize their battery pack in order to limit stress on the batteries (Illustration 3). In other words, the actual capacity of the battery is likely somewhat larger than the rated or useable capacity. If GM is indeed paying $145/kWh for its cells and its pack costs are 50% more than its cell costs and it is oversizing its pack by 20%, the cost of the pack works out to $261/kWh. Illustration 3Oversizing Battery To Account For Capacity Fade The reports which cite a $145/kWh cell price further suggest GM believes cells will cost $100/kWh in 2022, which implies a potential battery cost reduction of $2,700 (assuming the packs are not oversized) over the next 5 years (Table 3). The aforementioned research paper states: "The pure material costs for the VDA-type batteries are estimated to be currently about 50 EUR/kWh ($67.50), which seems to be the lower possible limit at long term." Even if the difference between materials cost and selling price is only 20%, that implies a lower limit of $81/kWh for the cells, meaning savings of $64/kWh are possible. This has not prevented some commentators from suggesting batteries will decline in price by 77% (or $112, implying $33/kWh pricing) by 2030.7 Regardless, savings of $64/kWh work out to $3,840 assuming a 60 kWh pack, or $4,680 assuming the pack is 20% oversized. Even if the pack cost were to decline a similar amount, the cost savings (assuming 50% for the pack, 20% oversized) would only be $7,000. Table 3GM Aims To Cut The Battery Cost By $2,700 By 2022 According to press reports, at the onset GM will lose $9,000 for every Bolt it sells.8 Since the major difference in costs between an EV and an ICEV is the battery pack, the $262 price cited above is probably not representative of the true cost. It may be that part of GM's commercial strategy is to show EV buyers that a replacement battery pack is not overwhelmingly expensive, and it is therefore willing to offer them at a loss. After all, the vehicle comes with a 100,000-mile, 8-year warranty on the battery, and we doubt many consumers would spend $15,734 (plus labor) to replace the battery on an 8-year-old EV. Therefore, GM is probably not going to sell that many replacements, so they won't suffer many losses by offering a replacement battery below its cost. The price differential between a Bolt and a Chevy Sonic, which is a similar vehicle manufactured in the same factory, is about $22,300. If we include the reported $9,000 expected loss, the "true" difference in price is $31,300. We believe that most likely the actual cost of the battery pack of the Bolt is much higher than $15,734. GM Confirms That Batteries Get Used Up Although the Bolt battery pack is covered by an 8-year 100,000-mile warranty, that warranty considers the potential for degradation of up to 40%: "Like all batteries, the amount of energy that the high voltage 'propulsion' battery can store will decrease with time and miles driven. Depending on use, the battery may degrade as little as 10% to as much as 40% of capacity over the warranty period."9 We highlight "all batteries" because this is the fate of all existing battery technologies. We further note that the amount of degradation will depend on the driving habits of the user: if the car is "lightly used" (i.e. traveled much less than 12,000 miles/year), chances are the battery degradation will be at the low end of the scale, whereas if the car is used a lot, chances are it will be at the high end of the scale. The average U.S. driver travels ~13,500 miles (22,000 km) per year,10 meaning the average driver with a single car would exceed the warranty on the Bolt in less than 8 years and, most likely, battery degradation would be closer to 40% than to 10%. Assuming a normal distribution, half of drivers would likely exceed the average annual miles driven, and as a result, their battery degradation would be even greater and happen even sooner, since they would be stressing the battery system through deeper and more frequent charging. Of course, if you were to travel 100,000 miles in 5 years, your battery warranty would expire. A major motivation for buying an EV is the expectation that it will save money on gasoline, which is true as shown in Table 1. However, the more you drive, the faster you use up the battery, and the sooner you would be faced with buying an expensive replacement battery. As such, drivers who drive a lot would be best to be cautious about purchasing an EV, as their costs of ownership due to battery degradation/replacement would be even higher. The Bolt has a purported range of 238 miles, but that range is achieved only when the battery is new and likely measured under ideal circumstances. Use of air conditioning, extreme temperatures (i.e. winter), etc., would probably trim the range significantly, likely to well below 200 miles. Assuming a reasonable usage for the vehicle, an 8-year-old Bolt would probably have a range closer to 100 miles than to 200 miles. This would significantly affect resale value as a vehicle with a range of 100 miles has much less utility than one with 200 miles. Difference In Cost Of Ownership: Chevy Bolt Vs. ICEV Calculating costs of ownership is subject to numerous assumptions, and this is especially the case with respect to an emerging technology such as EVs. Because we have a significant amount of information from GM on the cost and operating characteristics of the Bolt, and because GM makes "mass market" ICEVs which are roughly comparable to the Bolt, we thought it would be a uniquely useful benchmark for a cost of ownership analysis. We are neither making a claim that the Bolt or any EV will be commercially successful, nor are we endorsing it in any way; we are simply identifying the Bolt as representative of a typical mass-market EV. In our analysis we assume: The Chevy Bolt is a typical mass market EV; The sales price of the Bolt is roughly the same in the U.S.11 and Europe12 at $37,495; The Bolt is comparable to the Sonic in North America and the Opel Astra in Europe (Table 4); There are no direct financial subsidies associated with EVs; and After 100,000 miles, both the EV and the comparable ICEV have a similar residual value. Table 4The Bolt Is Much More Expensive Than Similarly-Sized GM ICEVs As we noted above, GM is believed to be taking a $9,000 loss associated with each Bolt sold. This is not sustainable if the firm expects to sell a lot of them. Most likely, either the company sees a path to significant cost reduction over the life of the product, or the company will artificially limit supply and use profits from its other products to subsidize the sales of Bolts. For the purpose of this analysis, we will assume the company and its rivals believe they can sell such vehicles at a reasonable profit in the future. The difference in the cost of ownership for similar vehicles is mainly associated with purchase cost, fuel costs, repair costs, and resale value. Insurance, parking, and so on would be a wash and annual repair and maintenance bills on most new cars are quite modest, so it would not significantly tilt the balance. Although EV enthusiasts tend to highlight the fact EVs do not require oil changes, the significantly increased weight of the battery means EVs require more frequent tire replacement than an equivalent ICEV.13 For example, modern ICEVs require an oil change every 10,000 miles. At $70/oil change this works out to $700, similar in price to a set of tires. Furthermore, the repair experience with EVs is extremely limited, and if we are to take Tesla as an example, they do not fare as well as many had hoped.14 We address the likely higher depreciation rates of EVs below. Estimating Electric Power Costs For An EV Charging a battery is not 100% efficient as losses occur in the charger and at the battery. Batteries get warm as they are charged, and that is a sign of inefficiencies in the charging process. As smartphone and notebook owners are aware, aged batteries produce a lot more heat when they are charged because the charging becomes less efficient as the batteries age. A new EV with a "slow" charger (see below) is about 85% efficient,15,16 while the figure is almost certainly lower for an aged battery. Assuming the system were 100% efficient, the Bolt vehicle goes 238 miles on 60 kWh, averaging about 0.25 kWh/mile, or approximately 25,000 kWh for 100,000 miles. Assuming lifetime average efficiency of 80% (85% when new, 75% when old), lifetime power consumption would be about 31,250 kWh. EV advocates note there are numerous "free" public charging stations. This is true, but there are far fewer public charging stations than there are EVs, which means the average EV owner pays for her electricity (Chart 1). Regardless, somebody has to pay for the electricity, and it is unreasonable to assume that "free charging" will persist if EVs gain significant market share, which apparently they have been doing in the past few years, especially in the U.S. and the EU (Chart 2). Chart 1Globally, EVs Outnumber Charging Stations By 6 To 1 Chart 2EV Market Share Is Increasing, Especially In Europe Furthermore, although many utilities have "time of use" utility rates which are lower in the evening when an EV is being charged, there is reason to question whether those can coexist with significant EV market penetration, a subject we will address in Part 2. Regardless, average power rates incorporate discounted time of use power to some extent, so that is the figure we use. Net Operating Costs: U.S. The Bolt17 is roughly comparable to a Chevy Sonic18 in terms of size, and the vehicles are made in the same factory. The difference in price is about $22,300. At 25/33 mpg, fuel use of the Sonic over 100,000 miles would be about 3,600 gallons (13,627 liters), costing about $9,000, assuming a gasoline price of $2.50 per gallon ($0.66/liter), which is slightly higher than the current nationwide average of ~$2.30/gallon. Assuming lifetime power consumption of 31,250 kWh and an average electricity price in the U.S. of $0.104/kWh,19 electric power costs for the Bolt would be around $3,250, for a net "fuel costs savings" of $5,700 in favor of the Bolt. However, the substantially higher initial purchase price and faster depreciation still results in the Sonic costing about $16,100 less over the duration of the vehicles' 100,000 miles (160,000 km). Put another way, the Bolt's total operating costs would average about $0.38 per mile, 73% higher than the $0.22/mile cost of the Sonic. Net Operating Costs: Europe In Europe, both fuel and electricity costs are typically much higher than in the U.S., but ICEVs also tend to be more fuel efficient. The Bolt is roughly equivalent to an Opel Astra, which costs €16,700 ($19,160) in France and consumes 4.4 litres/100 km20 (53 MPG). The difference in price between the Bolt and the Astra is about $18,300, a smaller premium than in the U.S. comparison. However, even though gasoline prices are more than twice as expensive in Europe than in the U.S., fuel costs for the Astra are moderated by the car's higher fuel efficiency, approximating $10,500 for the first 100,000 miles. Energy costs and EV subsidies vary widely across the EU. Because the economic impact of EVs would be roughly proportional to GDP, we decided to look at the largest EU economies excluding the UK. It happens that EV sales in Italy are negligible, with total market share less than 0.1%,21 and EV subsidies in the country are somewhat opaque. Therefore, we confined our analysis to Germany and France. Assuming lifetime power consumption of 31,250 kWh, the electric power costs of the Bolt would be around $5,350 in France, which has low power prices, for net energy savings of $5,100. In Germany, where power prices of $0.34/kWh are considerably higher, the Bolt and the Astra would have energy costs that are roughly equal. In France, EVs' ownership costs would be $13,200 (49%) higher than the ICEV; in Germany, EV ownership costs would be $18,500 (68%) higher. Bolt Vs Sonic Cost Of Ownership: Impact Of Subsidies In the U.S., there is a federal subsidy of $7,500 and some states also have an EV incentive. In New York State, the subsidy is $2,000, meaning the net increased cost of owning the Bolt instead of a Sonic drops to around $6,600. Note that the federal subsidy is designed to "phase out" once a manufacturer sells 200,000 vehicles. GM hopes to sell 30,000 EVs in 2017 despite only launching U.S.-wide in summer 2017. Combined with prior Volt sales of over 150,000 units, GM should exhaust its federal subsidies in early 2018. Subsidies vary considerably across the EU.22 In France, there is a subsidy of €6,300 ($7,200)23 associated with the purchase of an EV, while Germany24 has a €4,000 ($4,600) incentive. Besides subsidies, there are other benefits of owning an EV including reserved or even free parking spaces, often including free charging. These are offset to some extent by the limited range of EVs which may disqualify them from purchase by some. It remains to be seen how long EV subsidies will persist. They may be affordable to governments as long as the number of vehicles sold remains small, but they would become very costly if EV sales accelerate. For example, about 2 million new passenger cars are registered in France every year. If only half of those were EVs, subsides would total $7.2B. Money for roads, infrastructure maintenance, policing, and so on have to come from somewhere, and if ICEV sales decline substantially, European governments' huge gasoline tax revenues would also deteriorate; in such an environment, it is reasonable to assume that EV subsidies would eventually disappear and be replaced by taxes. It seems highly unlikely to us that a massive subsidy program would be a politically acceptable solution in the U.S. auto market; however, it may very well be that over the near term subsidies persist in the EU where concerns over climate change have greater political weight. Cost Of Ownership: Depreciation Depreciation of the EV is almost certainly going to be much higher than the ICEV, which accounts for some of the higher cost of ownership. We believe that most EV batteries will be substantially degraded after 160,000 km (100,000 miles), and we doubt there will be many EVs on the road past about 200,000 km or 15 years of operation. In contrast, the average age of a vehicle in the EU is over 10.5 years,25 while the average age of a vehicle in the U.S. is 11.6 years.26 The overwhelming majority of EVs on the road today are still under warranty and, in either event, relatively new, which means consumers lack the information to understand the inherent issues of battery degradation. As more consumers have experience with EVs, the problems of degradation and replacement cost (i.e. the high cost of depreciation) will likely temper demand. This would be the case even if battery costs drop significantly: few consumers would invest even $5,000 into repairing a 10-year-old vehicle, and an EV with a 100 mile (160 km) range is significantly less useful than one with a 200 mile (320 km) range. Rapid depreciation has been the experience of Nissan Leaf owners who are discovering their vehicles have lost 80% of their value after only 3 years.27 EV advocates suggest that degradation is not an issue and that, in any event, batteries are getting better and better. This flies in the face of what essentially every consumer has experienced with mobile phones, notebook computers, or any other cordless device. We believe GM has better insights into the issue than EV advocates do and, in any event, we see no evidence for significant improvements in battery life. If, indeed, significant improvements are made to batteries, prior-generation EVs (including today's Bolt) will plummet in value. That said, consumer understanding of battery degradation is not likely to be a factor for EV adoption over the near term. Conclusion: Costs Of Ownership Assuming similar depreciation and excluding subsidies, the net difference in cost of ownership over 160,000 km (100,000 miles) between a Bolt and an equivalent ICEV is about $16,100 in the U.S., $13,200 in France, and $18,500 in Germany, in favor of the ICEV. After subsidies, an optimistic analysis suggests the difference in cost of ownership to travel 100,000 miles (160,000 km) between a Bolt EV and a roughly similar ICEV is about $6,600 in the U.S. (New York), $6,000 in France, and $13,900 in Germany, in favor of the ICEV. Electric power costs for the Bolt are around $3,250 in the U.S., $10,600 in Germany, and around $5,350 in France. Even if electricity were free, after subsidies, the difference in cost of ownership would be $3,400 in the U.S. (NY), $3,200 in Germany, and $600 in France. GM is believed to be losing $9,000 with every Bolt it sells. If so, and it wanted to sell the vehicle at its average Gross Margin of around 13%, it would sell for closer to $48,300, which would increase cost of ownership by about $11,000. In other words it would take a cost reduction of around $14,750 (about 34%) of likely manufacturing cost before the cost of ownership would favor the Bolt in France after subsidies. As noted above in our discussion of battery costs, GM expects a $2,700 cost saving associated with battery cells by 2022. Given that it is losing money on the vehicle, it is hard to believe they will immediately pass these savings on to the consumer. Even if they did, cost of ownership would still favor the ICEVs. Brian Piccioni, Vice President Technology Sector Strategy brianp@bcaresearch.com Matt Conlan, Senior Vice President Energy Sector Strategy mattconlan@bcaresearchny.com Robert P. Ryan, Senior Vice President Commodity & Energy Strategy rryan@bcaresearch.com Johanna El-Hayek, Research Assistant johannah@bcaresearch.com 1 https://www.bloomberg.com/news/articles/2017-06-28/china-is-about-to-bury-elon-musk-in-batteries 2 https://www.greentechmedia.com/articles/read/10-battery-gigafactories-are-now-in-progress-and-musk-may-add-4-more 3 Please see Technology Sector Strategy Special Report "Electric Vehicle Batteries", dated September 20, 2016. 4 http://insideevs.com/heres-how-much-a-chevrolet-bolt-replacement-battery-costs/ 5 http://insideevs.com/gm-chevrolet-bolt-for-2016-145kwh-cell-cost-volt-margin-improves-3500/ 6 https://www.researchgate.net/publication/260339436_An_Overview_of_Costs_for_Vehicle_Components_Fuels_and_Greenhouse_Gas_Emissions 7 https://www.bloomberg.com/news/articles/2017-05-26/electric-cars-seen-cheaper-than-gasoline-models-within-a-decade 8 https://www.bloomberg.com/news/articles/2016-11-30/gm-s-ready-to-lose-9-000-a-pop-and-chase-the-electric-car-boom 9 https://electrek.co/2016/12/07/gm-chevy-bolt-ev-battery-degradation-up-to-40-warranty/ 10 http://www.carinsurance.com/Articles/average-miles-driven-per-year-by-state.aspx 11 http://www.chevrolet.com/byo-vc/client/en/US/chevrolet/bolt-ev/2017/bolt-ev/features/trims/?section=Highlights§ion=Fuel%20Efficiency§ion=Dimensions&styleOne=388584 12 https://electrek.co/2016/12/15/chevy-bolt-ev-europe-june-2017-opel-ampera-e-gm/ 13 The Bolt weighs almost 800 pounds (360 kg) more than a similar sized Chevrolet Sonic. 14 http://www.consumerreports.org/cars-tesla-reliability-doesnt-match-its-high-performance/ 15 https://www.veic.org/docs/Transportation/20130320-EVT-NRA-Final-Report.pdf 16 http://teslaliving.net/2014/07/07/measuring-ev-charging-efficiency/ 17 http://www.chevrolet.com/bolt-ev-electric-vehicle 18 http://www.chevrolet.com/sonic-small-car 19 https://www.eia.gov/electricity/state/ 20 http://www.opel.fr/vehicules/gamme-astra/astra-5-portes/points-forts.html#trim-edition 21 http://www.eafo.eu/content/italy 22 https://www.iea.org/publications/freepublications/publication/GlobalEVOutlook2017.pdf pages 53-55 23 http://insideevs.com/overview-incentives-buying-electric-vehicles-eu/ 24 https://electrek.co/2016/04/27/germany-electric-vehicle-incentive-4000/ 25 http://www.acea.be/statistics/tag/category/average-vehicle-age 26 http://www.autonews.com/article/20161122/RETAIL05/161129973/average-age-of-vehicles-on-road-hits-11.6-years 27 http://blog.caranddriver.com/tesla-aside-resale-values-for-electric-cars-are-still-tanking/ Investment Views and Themes Recommendations Strategic Recommendations Tactical Trades Commodity Prices and Plays Reference Table Trades Closed in 2017 Summary of Trades Closed in 2016

Overweight The cable & satellite index heavyweights Comcast and Charter Communications both reported their results last week, announcing that they had churned 34,000 and 90,000 of the traditional video customers, respectively. Still, neither company saw a decline in video revenue, reflecting still-strong sector pricing (second panel) and an unabated willingness of the consumer to purchase their content (third panel). The dominant theme from cable & satellite earnings was a transition to high-speed internet (unchanged from the past number of years), a lower revenue but higher margin business. This drove both of the aforementioned companies to each grow their customer relationships by mid-single digits in the quarter. Importantly, the customer additions were made without significantly increasing capital outlays (bottom panel) that, when combined with an overall higher margin business, implies more efficient returns on capital. This should ultimately drive more free cash flow, higher valuation multiples and ongoing share price increases. We reiterate our overweight recommendation for cable & satellite. The ticker symbols for the stocks in the S&P cable & satellite index are: BLBG: S5CBST - CMCSA, CHTR, DISH.

Special Report

Dear Client, Over the next three weeks, much of BCA’s Geopolitical Strategy team will be traveling in Australia, New Zealand, and Asia. As such, we are taking this week off from publication and will return to our regular schedule next week. In lieu of our regular missive, we are sending you the following Special Report, penned by our colleagues in the BCA Technology Sector Strategy. The report, originally published on May 16, tackles “The Coming Robotics Revolution” in an innovative way that aligns with our own views. Clients often ask us what will be the political consequences of the revolution in artificial intelligence and robotics. Our answers are controversial because we strongly disagree with the conventional, Terminator-inspired, doom and gloom. Brian Piccioni and Paul Kantorovich agree with us, which is reassuring given that they understand the technology behind robotics far better than we do. I hope you enjoy the enclosed report and encourage you to seek out the insights of our Technology Sector Strategy. Kindest Regards, Marko Papic, Senior Vice President Chief Geopolitical Strategist Feature "The amount of technology coming at us in the next five years is probably more than we've seen in the last 50" Mark Franks, Director Of Global Automation at General Motors, Bloomberg News, April 2017 There is good reason to believe we are at the cusp of a Robot Revolution which will have a dramatic impact on our economy. Robots have been around for decades or centuries, depending on the definition. Past robots were either fixed in place, as in the case of factory robots, or supervised by operators that are near the robot, or connected through telemetry. In contrast, the robots that are coming will not be fixed in place, and will be able to perform their functions without a human operator. This opens up massive markets for robots in industry (cutting lawns, cleaning windows, delivering parcels, etc.) and, most significantly, consumer applications. Part 1: Robots - Industrial Revolution To Early 21st Century The term "robot" can have different meanings. The most basic definition is "a device that automatically performs complicated and often repetitive tasks,"1 a definition which encompasses a broad range of machines: from the Jacquard Loom,2 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. For much of history, most of the labor force was involved with the production of food: over 50% of the U.S. labor force was involved in agriculture until the late 1800s (Chart 1). Agriculture has benefitted immensely from automation as inventions such as the McCormick Reaper (a wheat cutting machine pulled by horses), the cotton gin, and other mechanical systems displaced human effort. Steam and then internal combustion-powered tractors, which can be viewed as "robotic horses," accelerated the process, as engines delivered much more power more cost effectively than mechanical devices (Chart 2). This massively improved productivity: within 20 years from 1830 to 1850, the labor to produce 100 bushels of wheat dropped from 250-300 to 75-90 hours, and by 1955 it only took 6 ½ hours of labor for a net reduction of 97.5% in 125 years.3 Chart 1Farm Workers Were Disrupted In The Late 19th Century Chart 2...And So Were Horses In other words there is nothing new about automation displacing workers while improving productivity, nor is a rapid displacement unprecedented. The industrial revolution was about replacing human craft labor with capital (i.e. 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. Automation Frightens People Although automation is nothing new, it has always engendered anxiety among workers. The anxiety boils down to concern for continued employment as well as fear of the technology itself. We discuss below why Artificial Intelligence (AI) does not present the sort of threat to humanity or even employment that seems to be the consensus view at the moment. Will Robots Become Self-Aware? We have covered the topic of Artificial Intelligence/Deep Learning as it relates to sentient/self-aware machines in some detail in our October 18, 2016 Special Report on Artificial Intelligence. In summary, most of the discussion surrounding AI is misinformation. Although AI uses algorithms called "artificial neural networks," which are extremely useful for solving certain classes of problems, these are nothing like biological neural networks. There is no reason whatsoever to believe AI technology in its current form can become sentient, or even meaningfully intelligent, and that will not change with increased computing power. Furthermore, whether or not AI can arise to the level of a threat, there is no current or imagined power source which could keep a rampaging robot active for more than a few hours. The Terminator would have been much less threatening if he required frequent recharging. Will Robots Make Human Workers Irrelevant? Automation in agriculture occurred rapidly enough to be felt by workers at the time - and yet there were no marauding hordes of unemployed hay cutters or cowboys. Improved productivity meant markets were opened which did not previously exist, and unemployed agricultural workers moved to factory work. Media coverage of automation tends to focus on the potential job losses without mentioning the fact that the economy and its workers adapt, and overall living standards generally improve (Chart 3). Technology has displaced entire classes of jobs very rapidly in the recent past, and many products such as smartphones would be extremely difficult to assemble if the work was done by hand. Box 1 provides several other examples. Yet as is usual for many things that have happened multiple times in the past, we are told "this time is different." Chart 3The Industrial Revolution Led To A Vast Improvement In Living Standards Box 1 Automation Displaced Entire Classes Of Jobs In The Recent Past, But Brought Enormous Benefits Before calculators and word processors were available, writing and mathematical calculations were done manually. Machines such as calculators and type writers enhanced productivity, eliminating many such jobs. Software applications such as Microsoft Word and Excel further accelerated this process. Not that long ago, welding was entirely a manual job but now most welding in factories is done by robots: you can usually tell a human weld on a mass produced product by its poor quality. Robots in the modern factory have freed up workers for other roles in the economy just as the massive loss of agricultural jobs in the 20th century did. Many modern electronic products such as smartphones would be extremely difficult to assemble if the work was done by hand, as the components are so small they require microscopes to manipulate. Even if it were possible to hand assemble a smartphone, it would take hours of manual labor to produce, and the quality would be very poor. The use of automation means that smartphones cost a few hundred dollars instead of a few thousand dollars and are affordable enough to be a mass market item. Some of the anxiety around automation-related job losses centers on the possibility that this time, robots will displace workers from the service and white-collar sectors. BCA's European Investment Strategy service has written about the potential for AI to replace jobs involving tasks that require specialized education and training, such as calculating credit scores or insurance premiums, or managing stock portfolios.4 Recent developments in AI (specifically deep learning algorithms) have allowed computers to solve pattern recognition problems that they could not previously solve. However, we do not believe AI in its current form poses a widespread risk to white collar employment for the following reasons: Both service-sector and white collar employees have been subject to replacement through automation already, and the economy has adapted: ATMs are robot bank tellers, self-checkout lanes are robot checkout kiosks, and "smart" gas and electric meters that can be read remotely replace human meter readers. The legal profession has been transformed by Google searches and the accounting business by accounting software. These tools allow certain clients to avoid the use of a lawyer or accountant altogether (for example in setting up a corporation or doing bookkeeping), or allow a firm to employ less skilled workers for the task. We can offer numerous other examples of white collar jobs which have been fully or partially automated over the past couple decades. In addition, recall that AI produces high probability answers which turn out to be wrong, and it requires a lot of subject specific training. Both of these are intrinsic to the implementation of the algorithm. In contrast, humans generally are much better at assigning confidence to decisions and train very rapidly because they have cross-expertise AI lacks. An implementation of AI has to meet BOTH of the following conditions to be successful: There has to be a lot of subject-specific data available A high probability assigned to a wrong answer is either inconsequential or can be easily overruled by a human It is also important to note that although AI may reduce the demand for accountants, insurance agents, credit analysts and other skilled professionals, these are exactly the sort of people that can handle retraining. Part 2: What Makes Upcoming Robots Revolutionary Upcoming robots will be different because they will not be confined to the factory floor. We believe this is a key transition point, and that the next 20 years or so will see as dramatic a change from robotics as was caused by the Internet. Factory robots have improved immensely due to cheaper and more capable control and vision systems. Early robots performed very specific operations under carefully controlled conditions -an assembly robot which encountered a misaligned component would simply install it that way, resulting in a defective product. Eventually vision systems were developed which allowed robots to adjust to varying conditions. As camera and computing costs continue to decline, vision systems are becoming more elaborate and useful, as they gather and process more information to make increasingly complex decisions. 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. Mobile robots will likely rely on AI to make many decisions. In order to be cost effective, for many years AI will likely be hosted in cloud data centers. This is especially the case for consumer robots, which will have to be highly capable and yet cost effective. We discuss the implications for cloud services providers in more detail in Part 3: Investment Implications. We May Be Entering A 'Virtuous Cycle' In Robotics Improvements to one domain of robotic applications can be generally applied to others. Robotics technology is concurrently moving forward on many fronts ranging from the aforementioned vacuum cleaners, lawnmowers, and logistics robots, to medical orderlies,5 farm tractors,6 mining equipment,7 transport trucks,8 and cargo ships.9 Despite enormous differences in cost and value added, all of these applications are solving essentially the same problem. As with any other technological revolution, advances between different fields in robotics will be adapted, borrowed, extended and enhanced. This, in turn, creates opportunities for ever more applications, creating a virtuous cycle (Diagram 1). Diagram 1Robotics Will Enter Into A Virtuous Cycle There are few tasks which cannot be automated, but there is a definite cost-benefit tradeoff for each one. For example, a golf course may consider spending $25,000 for a robotic lawnmower, however costs were closer to $70 - $90,000 in 2015,10 and installed cost is even higher.11 Because the incremental cost of the machines is comprised of electronics, which will drop in price rapidly, it is probably a matter of another 2 or 3 years before the price moves to the point where mass adoption by groundskeepers begins. The same improvements to industrial lawnmowers will lead to more useable, albeit still pricy, consumer models which will probably enter mass market adoption 5 to 10 years from now. The same argument can be made for almost any manual chore ranging from cleaning the carpet to delivering parcels. We predict the virtuous cycle for robots will span several decades. As the cost of automation drops, better solutions will be developed, resulting in 'early retirement' of dated but otherwise fully functional robotic systems. This is the opposite of the Feature Saturation phenomenon currently present in the smartphone and PC industries - though feature saturation will eventually hit robots as well. A Self-Driving Car Is A Robot The most important robotics technology, from a macroeconomic perspective, is the rapidly advancing field of Autonomous Vehicles (AVs). The automobile industry is a significant part of the global economy, so changes in this industry will have profound implications. We covered AVs in detail in our April 8, 2016 Special Report. Due to technical and legal obstacles that must be overcome, a vehicle which can safely travel from point to point on major roads and city streets without driver intervention is probably 20 years away, +/- 5 years. The macro impact, however, will occur much sooner than that, due to the technologies developed on the way to full AVs. Vehicles are already offering features such as forward collision warning, autobrake, lane departure warning, lane departure prevention, adaptive headlights, and blind spot detection.12 Although we have only touched the surface, robotics are being applied across many industries, making even seemingly modest advances significant when measured in aggregate, as small changes in one industry are quickly adapted by other industries. It is noteworthy that this transition will likely occur during a period where demographic shifts, in particular in the most developed economies, signal the potential for labor shortages, or at least increasing cost of labor (Chart 4).13, 14 Robots may be showing up in the nick of time to improve both the economy and quality of life in the developed world. Chart 4Advances In Robotics Will Counter Adverse##br## Demographic Trends Part 3: Investment Implications The semiconductor industry has stagnated as the PC and smartphone markets entered a largely replacement-driven era (Chart 5). Although it may not be evident until the virtuous cycle is fully engaged, robotics represents another up-leg in demand for semiconductors and therefore should result in a significant improvement to industry growth rates. There is little opportunity for startup semiconductor companies nowadays due to the high costs of developing a new chip. Well positioned, established, semiconductor companies will be the primary beneficiaries of the robotics revolution. Large firms that attempt to fit their existing product offering into the industry (e.g. by remaining PC or mobile-phone centric) will fall behind. Winners System on a Chip (SoC) Vendors: Robotics hardware will more likely be implemented as "System on a Chip" (SoC) as this provides the greatest functionality with lowest cost and power consumption. SoCs generally consist of a variety of Intellectual Property (IP) "cores" which may be licensed from third parties. Typically, IP cores consist of a microprocessor and various specialized subsystems, depending on the application. Robotics SoCs are likely to include Digital Signal Processing (DSP) or Image Processing cores to process sensor data. SoC vendors who target or encourage robot development, such as Overweight-rated Texas Instruments, are likely to be favored by early movers in the space.15 We believe it is a matter of time before Graphics Processors (GPUs) currently used in AI/Deep Learning are replaced by processors specifically designed for AI, which will be cheaper and more power efficient.16 This is one of the reasons for our Underweight rating on Nvidia. Semiconductor Foundries, Mixed Signal and Automotive Semiconductor Vendors: This environment will favor the merchant semiconductor foundries which manufacture most SoCs. In addition, firms with "mixed signal" expertise will experience increased demand for motor controls, sensor interfaces, etc. As robotics features are added to automobiles, demand for automotive semiconductors should outpace that in other sectors. A significant degree of commonality in the parts and systems used in advanced automobiles will be used in other mobile robots, so "automotive" semiconductor demand should significantly outpace automobile sales. Sensor Vendors: Robots need a variety of sensors, depending on the application. Unlike factory floor robots which can make do with cameras, mobile robots will require advanced radar, ultrasound, laser scanning and other sensor types in order to provide redundancy and cope with weather and other related issues. Important sensors on prototype AVs are currently made in low volumes and are extremely expensive. Due to the number of sensors involved, we believe there is significant opportunity for companies offering aggressive cost reduction in sensor technology. Wireless Equipment and Service Providers: Most robotic systems will include some degree of wireless connectivity and participate in the "Internet of Things" (IoT). This will present challenges and opportunities for wireless equipment and service providers,17, 18 as networks will have to adapt to increased upload bandwidth (from robot to carrier) as well as novel billing schemes. Coverage will also have to be expanded to accommodate AVs as it is non-existent or spotty in large stretches of North American roadways. Not being able to check Facebook between two cities is one thing, losing your robot driver is much more serious. Our recent downgrade of Cisco to Underweight19 may appear inconsistent with the analysis above. However, the company's valuation is extremely elevated and revenues are declining (Chart 6). Any benefit Cisco will derive from investment into wireless infrastructure is several years out, and open-source hardware initiatives are gaining momentum.20 For that reason, we see the risks as outweighing the opportunities at the moment for the company. Chart 5Long Replacement Cycles Mean Slower ##br##Semiconductor Sales Chart 6Cisco's Stock Price Is Close To Tech Bubble##br## Levels Despite Declining Revenue Cloud Service Providers: Most robots will be on line and some will likely use cloud services to offload computational effort and minimize cost. A relatively "dumb" robotic lawnmower which offloads control to a shared computational resource in the cloud would probably be cheaper than a much more capable fully autonomous system. This will increase demand for cloud services, however the challenge of declining margins (due to increased competition in the space) will offset cloud services revenue growth somewhat in the long term. On balance, Overweight-rated Microsoft and Alphabet/Google, as well as Amazon, stand to benefit. Chart 7Eastman Kodak Tried To Ignore The Shift ##br##To Digital Cameras Losers We believe companies who ignore the robotics revolution will find themselves at a significant competitive disadvantage. This is not unprecedented in the technology sector: Digital Equipment Corporation (DEC) and Kodak vanished because their business models could not accommodate an obvious shift in their core markets (Chart 7). Similarly Intel and Microsoft completely missed the smartphone revolution. As we noted in our April 8, 2016 Special Report on AVs, the frequency and severity of crashes will decrease dramatically which will lead to reduced insurance rates, fewer repairs, and less money spent on accident related healthcare and rehabilitation. The economic losses of automobile crashes were estimated $871 billion in the US in 201021 and even a modest reduction in the frequency and severity of collisions due to partial automation would have a significant economic impact. "Dumb" Auto Parts Manufacturers: Fewer collisions will result in fewer repairs to people or vehicles. Auto parts manufacturers will fall into two camps: those with significant expertise in robotics will prosper, while those without such expertise will fall behind as the demand for replacement components (fenders, bumpers, doors, windshields, etc.) will decline. AVs are also likely to include advanced diagnostic and service reminder systems which will result in more timely service, reducing wear and tear on internal components as well. The Auto Insurance Industry: While it is doubtful robotics will ever eliminate auto accidents, the rate might be reduced to such a level that the auto-insurance industry, worth $157 billion in the US alone,22 will be much smaller in 20 years than it is today. This will be offset to a degree by greater demands for product liability insurance for AVs and robots in general. Brian Piccioni, Vice President Technology Sector Strategy brianp@bcaresearch.com Paul Kantorovich, Research Analyst paulk@bcaresearch.com 1 http://www.merriam-webster.com/dictionary/robot 2 http://www.computersciencelab.com/ComputerHistory/HistoryPt2.htm 3 https://www.agclassroom.org/gan/timeline/farm_tech.htm 4 Please see European Investment Strategy Special Report, "Female Participation: Another Mega-Trend," dated April 6, 2017, available at eis.bcaresearch.com. 5 http://www.tomsguide.com/us/Forth-Valley-Royal-Robots-Serco-Medicine,news-7124.html 6 http://modernfarmer.com/2013/04/this-tractor-drives-itself/ 7 http://www.asirobots.com/mining/ 8 http://www.theaustralian.com.au/business/powering-australia/rio-rolls-out-the-robot-trucks/story-fnnnpqpy-1227090421535 9 http://www.bloomberg.com/news/articles/2014-02-25/rolls-royce-drone-ships-challenge-375-billion-industry-freight 10 http://techon.nikkeibp.co.jp/english/NEWS_EN/20141210/393619/ 11 http://www.golfcourseindustry.com/article/do-robotic-mowers-dream-of-electric-turf/ 12 http://www.iihs.org/iihs/topics/t/crash-avoidance-technologies/topicoverview 13 http://gbr.pepperdine.edu/2010/08/preparing-for-a-future-labor-shortage/ 14 http://www.imf.org/external/pubs/ft/fandd/2013/06/das.htm 15 http://www.ti.com/corp/docs/engineeringChange/robotics.html 16 Please see Technology Sector Strategy Weekly Report, "Google - AI And Cloud Strategy," dated April 25, 2017, available at tech.bcaresearch.com. 17 http://www.fiercemobileit.com/press-releases/gartner-says-internet-things-will-transform-data-center 18 http://www.computerworld.com/article/2886316/mobile-networks-prep-for-the-internet-of-things.html 19 Please see Technology Sector Strategy Weekly Report, "Networking Equipment Update ," dated March 28, 2017, available at tech.bcaresearch.com. 20 http://www.businessinsider.com/att-white-box-test-should-scare-cisco-juniper-2017-4 21 http://www.nhtsa.gov/About+NHTSA/Press+Releases/2014/NHTSA-study-shows-vehicle-crashes-have-$871-billion-impact-on-U.S.-economy,-society 22 http://www.bloomberg.c/bw/articles/2014-09-10/why-self-driving-cars-could-doom-the-auto-insurance-industry

Negative relative sales growth at retail drug stores has caused the S&P retail drug store index to underperform (top and second panels). However, the second derivative of the decline has turned positive, troughing early this year, but the sector's share of the consumer's wallet has barely changed since the share price slide began in 2015. Analysts' top line estimates have largely captured the modest improvements in the sales outlook; these pulled out of deflation last month for the first time since late-2016 (bottom panel). However, valuations have not followed suit, which appears to be the market assigning a too-high risk premium to the operating recovery. If, as we expect, sales at drug retailers have turned a corner, margins and multiples should expand, particularly since the industry has consolidated substantially since 2015. This should allow investors to recoup some of their losses. Stay overweight The ticker symbols for the stocks in this index are: BLBG: S5DRUG - CVS, WBA.

The GAA DM Equity Country Allocation model is updated as of July 31st, 2017. The model has continued to reduce its allocation to the U.S. and now the U.S. allocation is the largest underweight. The funds from the U.S. are largely used to reduce the large underweight in the U.K. such that now the U.K. is in slight overweight. Other changes in the non-U.S. universe are the downgrade of Spain in favor of Germany, Italy and Netherland. These adjustments are mainly due to changes in liquidity indicators, as shown in Table 1. As shown in Table 2 and Charts 1, 2 and 3, the overall model outperformed its benchmark by 88 bps in July, entirely due to the 213 bps outperformance of Level 2 model where the overweight in Italy, Spain , Australia and Netherland vs the underweight in Japan, Germany, Sweden and Switzerland worked very well. Since going live, the overall model has outperformed its benchmark by 257 bps. Table 1Model Allocation Vs. Benchmark Weights Table 2Performance (Total Returns In USD) Chart 1GAA DM Model Vs. MSCI World Chart 2GAA U.S. Vs. Non U.S. Model (Level 1) Chart 3GAA Non U.S. Model (Level 2) Please see also on the website http://gaa.bcaresearch.com/trades/allocation_performance. For more details on the models, please see the January 29th, 2016 Special Report, "Global Equity Allocation: Introducing the Developed Markets Country Allocation Model." http://gaa.bcaresearch.com/articles/view_report/18850. GAA Equity Sector Selection Model The GAA Equity Sector Selection Model (Chart 4) is updated as of July 31, 2017. Chart 4Overall Model Performance Table 3Allocations Table 4Performance Since Going Live The model continue to be bullish on global growth and hence the cyclical tilt. However, consumer discretionary is the only cyclical sector to have an underweight. This recommendation is mainly driven by the unfavorable liquidity and technical backdrop. For more details on the model, please see the Special Report "Introducing The GAA Equity Sector Selection Model," July 27, 2016 available at https://gaa.bcaresearch.com.

Investors have shunned telecom services stocks vehemently year-to-date (YTD) on the back of an abysmal profit showing. Telecom services stocks are down 9%, while the S&P is up 10% YTD. In fact, in Q1 telecom services stocks were the sole sector to register negative year-over-year EPS growth on trough Q1/2016 earnings comparisons. Nevertheless, we do not want to overstay our welcome and are booking profits of 12% and lifting the S&P telecom services sector to the neutral column. Our Cyclical Macro Indicator (CMI) has arrested its fall giving us comfort that at least a lateral move in relative share prices is likely in coming months (top panel). The steep recalibration of cost structures to the new pricing reality is buttressing our CMI, offsetting the sector's plummeting share of the consumer's wallet (second panel). Encouragingly, selling prices cannot contract at 10% per annum indefinitely, and on a three month-rate of change basis, pricing power has staged a V-shaped recovery (third panel). Impressive labor cost discipline along with even a modest pricing power rebound signal that a grinding higher margin backdrop is likely in the coming months, in line with our margin proxy reading (bottom panel) Bottom Line: Lock in gains of 12% in the S&P telecom services sector and lift exposure to neutral. For additional details, please see yesterday's Weekly Report. The ticker symbols for the stocks in this index are: T, VZ, LVLT, CTL.

Pharma stock profits have moved in lockstep with consumer spending on pharmaceuticals and both have roughly doubled over the past decade. However, relative pharma consumer outlays have crested recently, causing a significant pharma profit underperformance (third panel). If our cautious drug pricing power thesis pans out as we portrayed in this week's Weekly Report, then pharma earnings will suffer and exert downward pressure on relative share prices (top panel). Industry balance sheet deterioration represents another warning signal. Net debt/EBITDA is skyrocketing at a time when the broad non-financial corporate (NFC) sector has been in balance sheet rebuilding mode (bottom panel). While this metric does not suggest that pharma stocks are in deep financial trouble, the deterioration in finances is undeniable, and, at the margin, a rising interest rate backdrop will likely slow down debt issuance for equity retirement and dividend payout purposes. Bottom Line: Trim the S&P pharmaceuticals index to underweight, which takes the S&P health care index to underweight. For additional details, please see yesterday's Weekly Report. The ticker symbols for the stocks in the S&P pharmaceuticals index are: BLBG: S5PHAR - JNJ, PFE, MRK, BMY, AGN, LLY, ZTS, MYL, PRGO.