Sectors

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

Highlights A thorough audit of our trade book highlights that our country and sector allocation recommendations have been quite profitable for investors. Of the 12 active trades in our book, 11 have generated a positive return, including one with a 32% annualized rate of return. A review of the original basis and subsequent performance of our trades suggests that investors should close 6 out of 12 of our active positions, predominantly related to resource & construction and domestic stock market themes. We will be looking for opportunities to add new trades to our book over the coming weeks and months that have broad, "big-picture" relevance. Watch this space. Feature In this week's report we conduct a thorough audit of our trade book, by revisiting the original basis and subsequent performance of all 12 of our active trades. While these trades have been initiated at different points over the past five years, they can be broadly grouped into five different themes: Core Equity Allocation & General Pro-Risk Trades (4 Trades) Reform-Oriented Trades (2 Trades) Resource & Construction Plays (2 Trades) Domestic Stock Market Trades (2 Trades) Trades Linked To Hong Kong (2 Trades) Overall, our trade book performance has been excellent. Of the 12 active trades in our book, 11 have generated a positive return, including one with a 32% annualized rate of return (since December 2015). As a result of our trade book review, we recommend that investors close six trades and maintain six over the coming 6-12 months. The closed trades predominantly fall into the resource & construction and domestic stock market categories, although we also recommend closing our long China H-share / short industrial commodity trade as well as our long Hong Kong REITs / short Hong Kong broad market trade. We present our rationale for retaining or closing each trade below. Over the coming weeks and months we will be looking for opportunities to add new trades to our book. Stay tuned. Core Equity Allocation & General Pro-Risk Trades We have four open core equity allocation and pro-risk trades: Overweight MSCI China Investable stocks versus the emerging markets benchmark, initiated on May 2, 2012 Long China H-shares / short industrial commodities, initiated on March 16, 2016 Short MSCI Taiwan / Long MSCI China Investable, initiated on February 2, 2017 and Long China onshore corporate bonds, initiated on June 22, 2017 We recommend that investors stick with three of these trades, but close the long China H-shares / short industrial commodities position for the following reasons: Chart 1Be Overweight China Vs EM In This Environment Be Overweight China Vs EM In This Environment Be Overweight China Vs EM In This Environment Overweight MSCI China Investable Stocks Versus The EM Benchmark (Maintain) This trade represents one of the most important equity allocation calls for Chinese stocks, and is one of the ways that BCA expresses a view on the Chinese economy in our House View Matrix.1 While it hasn't always been the case, we noted in a recent Special Report that Chinese stocks have become a high-beta equity market versus both the global aggregate and the emerging market benchmark, even when excluding the technology sector.2 China's high-beta nature, the fact that EM equities remain in an uptrend (Chart 1), and our view that China's ongoing slowdown is likely to be benign and controlled all suggest that investors should continue to overweight Chinese stocks vs their emerging market peers. Long China H-Shares / Short Industrial Commodities (Close) We initiated this trade in March 2016, one month after Chinese stock prices bottomed following the significant economic slowdown in 2015. At that time it was not clear to global investors that a mini-cycle upswing in the Chinese economy had begun, and this pair trade was a way of taking a limited pro-risk bet. Given our view of a benign, controlled economic slowdown in China, this hedged trade is no longer needed, especially given the uncertain impact of ongoing supply side constraints in China on global commodity prices. As such, we recommend that investors close the trade, locking in an annualized return of 15.7%. Short MSCI Taiwan / Long MSCI China Investable (Maintain) Chart 2If The TWD Declines Materially, ##br##Upgrade Taiwan (From Short) If The TWD Declines Materially, Upgrade Taiwan (From Short) If The TWD Declines Materially, Upgrade Taiwan (From Short) We initiated our short MSCI Taiwan / long MSCI China investable trade last February, when the risk of protectionist action from the Trump administration loomed large. While there have been no negative trade actions levied against Taiwan this year, macro factors, particularly the strength of the currency, continue to argue for an underweight stance within the greater China bourses (China, Hong Kong, and Taiwan). We reviewed the basis of this trade in a report last month,3 and recommended that investors stick with the call despite significantly oversold conditions (Chart 2). A material easing in pressure on Taiwan's trade-weighted exchange rate appears to be the most likely catalyst to close the trade and to upgrade Taiwan within a portfolio of greater China equities. Long China Onshore Corporate Bonds (Maintain) Chinese corporate bond yields have risen materially since late-2016, largely in response to expectations of tighter monetary policy. These expectations have been validated, with 3-month interbank rates having risen over 200bps since late-2016. We argued last summer that the phase of maximum liquidity tightening was likely over, and that quality spreads and government bond yields would probably drop over the coming three to six months. While this clearly did not occur (yields and spreads rose), the total return from this trade has remained in the black owing to the significant yield advantage of these bonds versus similarly-rated bonds in the developed world. Chart 3 highlights that Chinese 5-year corporate bond spreads are also considerably less correlated with equity prices than their investment-grade peers in the U.S. This underscores that the rise in yields and spreads over the past year has reflected expectations of tighter monetary policy, not rising default risk. Our sense is that barring a significant improvement in China's growth momentum, significant further monetary policy tightening is improbable, meaning that corporate bond yields are not likely to rise much further. As a final point, as of today's report we are changing the benchmark for this trade from a BCA calculation based on a basket of 5-year AAA and AA-rated corporate bonds to the ChinaBond Corporate Credit Bond Total Return Index. Chart 3Chinese Corporate Spreads Aren't A Risk ##br##Barometer Like In The U.S. Chinese Corporate Spreads Aren't A Risk Barometer Like In The U.S. Chinese Corporate Spreads Aren't A Risk Barometer Like In The U.S. Reform-Oriented Trades We have two open trades related to China's rebooted reform initiative, both of which were initiated on November 16, 2017: Long China investable consumer staples / short consumer discretionary stocks and Long China investable environmental and social governance (ESG) leaders / short investable broad market These trades were recently opened, and we continue to recommend that investors maintain both positions: Long China Investable Consumer Staples / Short Consumer Discretionary Stocks (Maintain) The basis for the first trade stems from the current limitations of China's investable consumer discretionary index as a clear-cut play on retail-oriented consumer spending. We argued in our November 16 Weekly Report that Chinese investable consumer staples would be a better play on Chinese consumer spending owing to the material weight of the automobiles & components industry group in the discretionary sector, which may fare poorly over the coming year due to the environmental mandate of President Xi's proposed reforms. We argued in the report that this trade would likely be driven by alpha rather than beta, and indeed Chart 4 illustrates that staples continue to rise relative to discretionary against a backdrop of a rising broad market. Long China Investable ESG leaders / Short Investable Broad Market (Maintain) In the same report we recommended that investors overweight the China investable ESG leaders index, based on the goal of favoring firms that are best positioned to deliver "sustainable" growth in an era of heightened environmental reforms. The index overweights firms with the highest MSCI ESG ratings in each sector (using a proprietary MSCI ranking scheme), and maintains similar sector weights as the investable benchmark, which limits the beta risk of the trade. Chart 5 highlights that the trade is progressing in line with our expectations, suggesting that investors stick with the position over the coming 6-12 months. Chart 4Staples Vs Discretionary Isn't A Low Beta Trade Staples Vs Discretionary Isn't A Low Beta Trade Staples Vs Discretionary Isn't A Low Beta Trade Chart 5Likely To Continue To Outperform Likely To Continue To Outperform Likely To Continue To Outperform Resource & Construction Plays We have two open trades related to the resource sector: Long China investable oil & gas stocks / short global oil & gas stocks, initiated on April 26, 2014 and Long China investable construction materials sector / short investable broad market, initiated on December 9, 2015 We recommend that investors close both of these positions, based on the following rationale: Chart 6Similar Earnings Profile, ##br##But Weaker Dividend Payouts Similar Earnings Profile, But Weaker Dividend Payouts Similar Earnings Profile, But Weaker Dividend Payouts Long China Investable Oil & Gas Stocks / Short Global Oil & Gas Stocks (Close) This trade was initiated based on the view that the valuation gap between Chinese and global oil & gas companies is unjustifiable given that the earnings off both sectors are globally driven. Indeed, Chart 6 shows that the trailing EPS profiles of both sectors in US$ terms have been broadly similar over the past few years, and yet China's oil & gas sector trades at a 40% price-to-book discount relative to its global peers. However, panel 2 of Chart 6 highlights that this discount may represent investor concerns about earnings quality and/or state-owned corporate governance. The chart shows that while the earnings ROE for Chinese oil & gas companies is higher than that of the global average, the dividend ROE (dividends per share as a percent of shareholders equity) is considerably lower. While China's oil & gas dividend ROE has recently been rising, the gap remains wide relative to global oil & gas companies, suggesting that there is no significant re-rating catalyst that is likely to emerge over the coming 6-12 months. Close for an annualized return of 1.4%. Long China Investable Construction Material Stocks / Short China Investable Broad Market (Close) The relative performance of Chinese investable construction material stocks has been positive over the past two years, with the trade having generated an 8.1% annualized return since initiation. There are two factors contributing to our view that it is time for investors to book profits on this trade. The first is that China's investable construction materials are dominated by cement companies, which may suffer in relative terms from China's rebooted reform initiative this year.4 The second is that the relative performance of construction materials stocks is closely correlated with, and led by, the growth in total real estate investment (Chart 7). Residential investment makes up a significant component of total real estate investment, and Chart 8 highlights that a significant gap between floor space sold and completed has narrowed the inventory to sales ratio over the past three years. But the ratio remains somewhat elevated relative to its history which, when coupled with the ongoing growth slowdown in China and the deceleration in total real estate investment growth, implies a poor risk/reward ratio over the coming 6-12 months. Chart 7Cement Producers Trade Off Of Real Estate Investment Cement Producers Trade Off Of Real Estate Investment Cement Producers Trade Off Of Real Estate Investment Chart 8No Clear Construction Boom Is Imminent No Clear Construction Boom Is Imminent No Clear Construction Boom Is Imminent Domestic Stock Market Trades We have two open trades related to China's domestic stock market: Long China domestic utility sector / short domestic broad market, initiated on January 22, 2014 and Long China domestic food & beverage sector / short domestic broad market, initiated on December 9, 2015 Similar to our resource & construction plays, we recommend that investors close both of our recommended domestic stock market trades: Long China Domestic Utility Sector / Short Domestic Broad Market (Close) We initiated this trade in early-2014, following a comprehensive reform plan released in late-2013 by the Chinese government. The plan called for allowing market forces to play a decisive role in allocating resources, which we argued would grant utilities more pricing power, reduce their earnings volatility associated with policy risks, and lead to a structural positive re-rating. Chart 9 illustrates that this trade gained significant ground in 2014 and early-2015, even prior to the significant melt-up in domestic stock prices that began in Q2 2015. However, the trade has underperformed significantly since the middle of last year, which has been driven by a sharp deterioration in ROE. This decline in ROE appears to have been cost-driven, as coal is an important feedstock for Chinese utility companies and has risen substantially in price over the past two years. While domestic utilities are now significantly oversold in relative terms, we recommend that investors close this trade because the original reform-oriented basis has shifted significantly. The priorities that emanated from October's Party Congress were decidedly environmental in nature, meaning that coal prices may very well remain elevated over the coming 6-12 months (due to restricted supply). This means that a recovery in ROE would rest on the need to raise utility prices, which is a low-visibility event that will be difficult to predict. Close for an annualized return of 3%. Long China Domestic Food & Beverage Sector / Short Domestic Broad Market (Close) We initiated this trade in December 2015, based on this sector's superior corporate fundamentals and undemanding valuation levels. We argued that the anti-corruption campaign since late-2012 was likely the cause of prior underperformance, given that the group is dominated by a few high-end alcohol producers. The market overacted to the high-profile crackdown, and ultimately the fundamentals of the sector did not deteriorate materially. Our view has panned out spectacularly, with the trade having earned a 32% annualized return since inception5 (Chart 10 panel 1). While the group's ROE remains significantly above that of the domestic benchmark, valuation measures suggest that investors have more than priced this in (Chart 10 panel 2). The trade has mostly played out and we would not like to overstay our welcome. In addition, panel 3 illustrates that technical conditions are extremely overbought, suggesting that investors are being presented with an excellent opportunity to exit the position. Chart 9Sidelined By A Major Hit To ROE Sidelined By A Major Hit To ROE Sidelined By A Major Hit To ROE Chart 10Time To Book Profits Time To Book Profits Time To Book Profits Trades Linked To Hong Kong We have two open trades related to Hong Kong: Long U.S. / short Hong Kong 10-Year government bonds, initiated on January 15, 2014 and Short Hong Kong property investors / long Hong Kong broad market, initiated on January 21, 2015 We recommend that investors stick with the first and close the second, based on the following perspectives: Long U.S. / Short Hong Kong 10-Year Government Bonds (Maintain) Hong Kong has an open capital account and an exchange rate pegged to the U.S. dollar, meaning that its monetary policy is directly tied to that of the U.S. Yet, Hong Kong's 10-year government bond yield is non-trivially below that of the U.S., which argues for a short stance versus similar maturity U.S. Treasurys. While it is true that the Hong Kong - U.S. 10-year yield spread does vary and can widen over a 6-12 month horizon, Chart 11 highlights that the relative total return profile of the trade (in unhedged terms) trends higher over time due to the carry advantage. Short Hong Kong REITs / Long Hong Kong Broad Market (Close) There are cross-currents facing the outlook for Hong Kong REITs vs the broad market, arguing for a neutral rather than an underweight stance. Close this trade for an annualized return of 3.6%. While the relative performance of global REITs is typically negatively correlated with bond yields, Chart 12 shows that the relationship with Hong Kong property yields has been positive and lagging (i.e. falling yields lead declining relative performance, and vice versa). Under this regime, a rise in U.S. government bond yields, as we expect, would suggest an improvement in the relative performance of Hong Kong REITs. Chart 11A Straightforward Carry Pick Up Trade A Straightforward Carry Pick Up Trade A Straightforward Carry Pick Up Trade Chart 12Rising Bond Yields Implies ##br##Positive HK REIT Performance Rising Bond Yields Implies Positive HK REIT Performance Rising Bond Yields Implies Positive HK REIT Performance Chart 13 highlights that periods of positive yield / REIT performance correlation have tended to occur when Hong Kong property prices are rising significantly relative to income, as they have been for the past several years. One interpretation of this dynamic is that when house prices are overvalued and potentially vulnerable, REIT investors react positively to an improvement in economic fundamentals (which tends to push yields up due to higher interest rate expectations). The risk of an eventual collapse of Hong Kong property prices is clear, but we cannot identify an obvious catalyst for this to occur over the coming 6-12 months. Importantly, the fact that property prices have continued to rise during a period of tighter mainland capital controls suggests that only a significant economic shock will be enough to derail the uptrend in prices, circumstances that we do not expect over the coming year. Finally, Chart 14 highlights that Hong Kong REITs are deeply discounted relative to book value when compared against the broad market. This suggests that at least some of the risks associated with the property market have already been priced in by investors. Chart 13Yields & REITs Positively Correlated ##br##When House Prices Are Overvalued Yields & REITs Positively Correlated When House Prices Are Overvalued Yields & REITs Positively Correlated When House Prices Are Overvalued Chart 14Hong Kong REITs Are Cheap Hong Kong REITs Are Cheap Hong Kong REITs Are Cheap Jonathan LaBerge, CFA, Vice President Special Reports jonathanl@bcaresearch.com Lin Xiang, Research Analyst linx@bcaresearch.com 1 https://www.bcaresearch.com/trades 2 Please see China Investment Strategy Weekly Report, "China: No Longer A Low-Beta Market", dated January 11, 2018, available at cis.bcaresearch.com. 3 Please see China Investment Strategy Weekly Report "Taiwan: Awaiting A Re-Rating Catalyst", dated December 14, 2017, available at cis.bcaresearch.com. 4 Please see China Investment Strategy Weekly Report, "Messages From The Market, Post-Party Congress", dated November 16, 2017, available at cis.bcaresearch.com. 5 Please note that the total return from this trade had been erroneously reported for some time due a data processing error on BCA's part. The return since inception now properly sources the China CSI SWS Food & Beverage index from CHOICE. We sincerely regret the error and any confusion it may have caused. Cyclical Investment Stance Equity Sector Recommendations

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

Overweight A key beneficiary of a tight job market are managed health care providers who see lifts in both employer-sponsored health plans and newly-affordable individual and family health plans. With the unemployment rate touching new lows and small-business hiring plans hitting new highs (unemployment rate shown inverted, second panel), the direction for premium revenue for this niche health care sub-index is clearly higher. At the same time as the top line is moving higher, cost inflation has dramatically decelerated, driven by collapsing pharma price inflation (third panel). The implication is outsized earnings growth this year. The market has clearly taken notice, rewarding the S&P managed health care index with a premium valuation (bottom panel). While this is an improvement from the discount multiple of much of the past decade, it remains a far cry from previous cyclical highs. We think an exceptional earnings growth phase should make this valuation expansion durable; stay overweight. The ticker symbols for the stocks in this index are: BLBG: S5MANH - UNH, AET, ANTM, CI, HUM, CNC. Managed Health Care Looks Healthy As Ever Managed Health Care Looks Healthy As Ever

Highlights The Beige Book released on January 17 keeps the Fed on track to raise rates at least three times this year and highlights the impact of the tax bill on the economy. BCA's Big 5 Bank Lending Beige Book highlights several of the positive trends supporting our view of the economy, the tax bill and the Fed. The Tax Cut and Jobs Act of 2017 has the potential to generate significant supply-side benefits for consumers, shareholders and the broad economy. We decided to stay long the dollar after a lengthy internal debate, although we have revised down our view on the upside potential. Feature U.S. risk assets continued to outperform last week outside of the dollar, as S&P 500 firms started to report Q4 2017 results and provide guidance for Q1 2018 and beyond. BCA's Bank Lending Beige Book summarizes the most optimistic comments from the Big 5 banks. The Fed's Beige Book captured comments on the broad economy in December and early January that were equally ebullient. Both Beige books suggested that firms were planning to return their tax savings to shareholders in the New Year, and to continue to boost capex, which was stout even before the law was passed. Yet, despite the upbeat news, the dollar broke down last week, as the ECB sounded a hawkish note and the Japanese economy continued to improve. On balance, the Beige Book, the Q4 earnings season, the health of the U.S. economy (notably capital spending), all support BCA's stance on the U.S. stock-to-bond ratio, the Fed, duration and the dollar. However, the dollar has not behaved as we would have expected. Beige Book Barometer Bounces The Beige Book released on January 17 keeps the Fed on track to raise rates at least three times this year and highlights the impact of the tax bill on the economy. BCA's quantitative approach1 to the Beige Book's qualitative data points to underlying strength in GDP and a tighter labor market, but there is still a disconnect between the Beige Book's view of inflation and the market's stance. Moreover, references to the stronger dollar have disappeared from the Beige Book and business uncertainty is significantly reduced, reflecting the tax cut bill and President Trump's assault on regulation. Chart 1Latest Beige Book Supports##BR##The Fed's View On Rates, Economy Latest Beige Book Supports The Fed's View On Rates, Economy Latest Beige Book Supports The Fed's View On Rates, Economy Chart 1, panel 1 shows that at 66%, BCA's Beige Book Monitor stayed near its cycle highs in January, re-confirmation that the underlying economy was still upbeat in Q4 and early 2018. (The latest Beige Book covered the period from mid-November 2017 to January 8, 2018). The number of 'weak' words in the Beige Book returned to near four-year lows after ticking higher in the wake of last summer's hurricanes. Moreover, there were 12 mentions of the tax bill in the January Beige Book, up from only 3 in November (not shown). The tax bill was cast in a positive light in 75% of the remarks. In November, the references to either the tax bill (or tax reform) cited the consequent uncertainty as a constraint on growth. Based on the minimal references to a robust dollar in the past five Beige Books, the greenback should not be an issue in Q4 2017 or Q1 2018, which is in sharp contrast with 2015 and early 2016 when there was a surge in Beige Book mentions (Chart 1, panel 4). The last time that five consecutive Beige Books had so few remarks about a strong dollar was in late 2014. Business uncertainty over government policy (fiscal, regulatory and health) ticked up in the past few Beige Books as Congress debated the particulars of the tax bill. Nonetheless, comments of uncertainty in the Beige Book have dropped since Trump took office in early 2017. The implication is that the business community is correctly focused on policy and not politics in D.C. (Chart 1, panel 5). The disconnect with the Fed on inflation is evident in the Beige Book's number of inflation words (Chart 1, panel 3). Expressions regarding inflation rose to a four-month high in January and the disconnect persists between the still-elevated mentions of inflation and the soft readings on CPI and PCE. In the past, increased references to inflation have led measured inflation by a few months, suggesting that the CPI and core PCE may soon turn up. Bottom Line: The recent Beige Book backs BCA's view that the U.S. economy is poised to grow above its long-term potential in the first half of 2018. However, the Beige Book has done little to resolve the debate around why an economy growing above potential and a tightening labor market have not boosted inflation. Likewise, the latest Beige Book confirmed that at least initially, businesses and bankers across the U.S. welcomed the Tax Cut and Jobs Act. Bankers' Beige Book Returns Chart 2Banking System Shipshape Banking System Shipshape Banking System Shipshape BCA's Big 5 Bank Lending Beige Book highlights several of the positive trends supporting our view: Pristine credit quality, a positive U.S. credit impulse, loosening U.S. banking regulatory requirements, and pent up demand for shareholder friendly activities. We introduced the Big 5 Bank Lending Beige Book2 in early 2014 to interpret the health of the banking system based on comments from leaders of the Big Five banks during earnings season. Managements were upbeat on loan demand and credit quality as they unveiled Q4 results in the past two weeks, and most expressed optimism that the positive credit trends would continue to improve in 2018. Several bank executives shared their Fed rate hike expectations for this year, with most forecasting three or four increases. One institution planned for a flatter curve, while another noted that rising rates on both the short and long ends will benefit their operations. Chart 2 shows key banking related variables cited in the Bank Lending Beige Book. Appendix Table 1 shows the Big 5 Bank Lending Beige Book for Q4 2017. All five banks were uniformly upbeat in their assessments of the tax bill's impact on their operations, their customers' businesses or the overall economy. One bank noted that it took a repatriation charge in Q4, and another said it would return capital to shareholders via buybacks and dividends. A third said the bill will provide "immediate and ongoing benefit to our employees, customers, communities and our shareholders, as we invest a portion of our tax savings in each of these important constituencies." Bottom Line: The banking system is shipshape as 2018 begins and lenders are ready to extend credit to businesses and consumers to boost the economy despite higher rates. BCA's U.S. Equity strategists recommend an overweight position in the S&P 500's financial sector, with a high conviction overweight on banks.3 A Different Lens On Earnings Chart 3Corporate Health Has Improved##BR##Since Start Of 2017 Corporate Health Has Improved Since Start Of 2017 Corporate Health Has Improved Since Start Of 2017 The early December release of the U.S. flow of funds report allows us to update BCA's Corporate Health Monitor (CHM) (Chart 3). The CHM's level improved slightly between Q2 and Q3, but the overall reading remains in 'deteriorating health' territory. The marginal improvement in Q3 was driven by rising profit margins. In addition, profit growth surged while debt moved up modestly in Q3. The CHM is a reliable indicator of the trend in corporate bond spreads which supports our corporate bond overweight. Given that corporate balance sheets are declining, the sole supports for corporate spreads are low inflation and accommodative monetary policy. We anticipate spreads will start to widen later this year when inflation climbs and policy turns more restrictive. BCA's U.S. Bond strategists remain overweight the U.S. high-yield bond market.4 Although spreads appear a bit more attractive than for investment-grade corporates, there is still not much room for spread compression in high-yields. We calculate that if the high-yield index spread tightens by another 117 bps, then junk bonds will be the most expensive since 1995. In an optimistic scenario where the index spread tightens 100 bps, bringing it close to all-time expensive levels, then we would expect junk excess returns to be in the range of 600 bps (annualized). Nonetheless, in view of the trends in corporate leverage, it is unlikely that there will be another 100 bps of spread tightening. More realistically, we expect excess returns between 200 bps and 500 bps (annualized) between now and the end of the credit cycle. Bottom Line: BCA's indicators suggest that we are moving into the late stages of the credit cycle, but we retain an overweight cyclical stance on corporate bonds. A shift to a more restrictive monetary policy, tightening C&I bank lending standards and/or a continued uptrend in gross corporate leverage are the main catalysts we will monitor to gauge the end of the cycle. An abrupt end to the positive capex or earnings cycle would also be concerns for our upbeat view on credit. Repatriation Redux The Tax Cut and Jobs Act of 2017 has the potential to generate significant supply-side benefits for consumers, shareholders and the broad economy. There are several uses for corporate cash, including capital spending, M&A, increasing compensation to employees, paying down debt and returning capital to shareholders. Chart 4 shows that through Q3 2017, share buybacks and dividends ran slightly ahead of prior cycles, while capex was about average. Investors wonder how that mix may change under the new law. Corporate behavior in the wake of the 2004 overseas tax holiday5 provides some guidance. Chart 4Comparison Of Corporate Outlays Across Four Economic Expansion Phases Variations On A Theme Variations On A Theme Corporations used cash generated from the 2004 tax break to return capital to shareholders. However, we found scant evidence that firms who benefited from the tax holiday increased capital spending, raised wages or hired more workers. A study by the National Bureau of Economic Research (NBER) noted that a dollar increase in repatriations "was associated with an increase of almost $1 in payouts to shareholders."6 Moreover, a 2008 IRS paper7 concluded that nearly half of all the cash repatriated in 2004 and 2005 came from only the tech and pharma sectors. A Congressional Research Service (CRS) found that small firms tended to benefit less than large firms from the tax holiday.8 A paper9 by the left-leaning, U.S.-based think tank, the Center For Budget and Policy Priorities (CBPP), stated that several firms that benefitted the most from the 2004 law laid off workers soon after the tax law was enacted. In 2018, BCA expects firms to return capital to shareholders, boost capex and continue to bump up wages. Chart 5 shows that buybacks will probably augment S&P 500 EPS by around 2% this year, while panel 2 shows that there was a noticeable upswing to buyback announcements as 2017 ended. Aside from the post-recession bounce in buybacks in 2010, the last big swell in buyback announcements occurred in 2004 and 2005. That said, corporate balance sheets were in much better shape in 2004/2005 than they are today (Chart 3 again). The implication is that management teams may decide to pay down debt before returning the cash windfall back to shareholders. However, with rates still low, most firms will chose to distribute the cash to shareholders, despite high corporate debt levels. The positive reading on BCA's Capital Structure Preference Indicator supports our stance on buybacks (Chart 6, third panel). This Indicator is defined as the equity risk premium minus the default-adjusted yield in high-yield corporate bonds. When the indicator is above zero, there is financial incentive for firms to issue debt and buy back shares. Conversely, firms are incentivized to issue stock and retire debt when the indicator is below zero. The Indicator is currently positive, although not as high as it was in 2015. Moreover, Chart 7 shows that the dividend payout ratio rebounded from the 2007-2009 financial crisis, but has moved above its pre-crisis level. However, dividend distributions remain below their pre-crisis peak reached in the early 1990s. Chart 5Still Some Room##BR##To Run For Buybacks Still Some Room To Run For Buybacks Still Some Room To Run For Buybacks Chart 6Buybacks Adding Almost##BR##2 Percentage Points To EPS Growth Buybacks Adding Almost 2 Percentage Points To EPS Growth Buybacks Adding Almost 2 Percentage Points To EPS Growth Capital spending was already on a tear in late 2017, even before the tax bill passed. Industrial production, the PMI diffusion index and advanced-economy capital goods imports, all confirm strong underlying momentum in investment spending (Chart 8). Chart 7Corporations Poised To Return##BR##Capital To Shareholders Corporations Poised To Return Capital To Shareholders Corporations Poised To Return Capital To Shareholders Chart 8Capital Spending Helping##BR##To Drive Growth Capital Spending Helping To Drive Growth Capital Spending Helping To Drive Growth Both BCA's real and nominal capex models, driven by surging capital goods orders along with elevated ISM data, roaring global exports and soaring sentiment on business spending, indicate strong investment in plant and equipment in the next few quarters (Chart 9). CEO confidence soared to a 13-year high in Q4, according to the latest Duke's Fuqua School of Business/CFO Magazine Global Business Outlook (Chart 10, panel 1). Duke noted that "Among CFOs who responded to the survey after the Senate passed its version of the tax reform bill, optimism spiked to 73, which is the highest U.S. optimism ever recorded in the history of the survey."10 Chart 9Bright Outlook##BR##For Capital Spending Bright Outlook For Capital Spending Bright Outlook For Capital Spending Chart 10CEO Confidence And##BR##Capex Plans Surging CEO Confidence And Capex Plans Surging CEO Confidence And Capex Plans Surging Surveys by the Conference Board and Business Roundtable show a similar pattern. (panel 1 again). Notably, the soundings on all three surveys have climbed since Trump's election, but then retreated as his pro-business agenda stalled in the summer months. The dip in sentiment reflected the lack of legislative progress in Washington in the first 10 months of the Trump administration. The dip in CEO sentiment in Q2 and Q3 was in sharp contrast to the easing of policy concerns in the Fed's Beige Book (Chart 1, bottom panel). The upbeat numbers in the regional FRBs' surveys of capital spending intentions further support escalating capex spending in the next few quarters. The average readings from the New York, Philadelphia and Richmond Feds' capex survey plans are at an all-time high (Chart 10, panel 2). Moreover, the regional Feds' capex spending plans diffusion index is close to a cycle high, despite a modest pullback last summer (panel 3). Bottom Line: Stay overweight stocks versus bonds, and underweight duration. The tax bill will boost returns to shareholders via buybacks and dividends. In addition, rising capex will drive up GDP, employment and EPS in the coming quarters. Dollar View Revisited The dollar fell by 4% between mid-December and mid-January, amid a hawkish market interpretation of the ECB minutes, persistently strong growth in Japan and a key technical breakdown in the DXY index. The decline has some investors questioning BCA's bullish stance on the currency (Chart 11). We were correct on the direction of interest rate differentials vis-à-vis the other major economies, but this has not translated into a stronger dollar so far. We decided to stay long the dollar after a lengthy internal debate, although we have revised down our view on the upside potential. A lot of good news on the European and Japanese economies is now discounted and investors are quite pessimistic on the dollar (which is bullish the dollar from a contrary perspective) (Chart 12). Given this technical backdrop, we would expect at least a 5% rise in the trade-weighted dollar as expectations of Fed rate hikes rise this year. We are likely to exit our long dollar position if we get such an appreciation. Chart 11We Are Sticking With##BR##Our Long Dollar View We Are Sticking With Our Long Dollar View We Are Sticking With Our Long Dollar View Chart 12The Case For Crisis Era Monetary Stimulus##BR##In Europe And Japan Is Weakening The Case For Crisis Era Monetary Stimulus In Europe And Japan Is Weakening The Case For Crisis Era Monetary Stimulus In Europe And Japan Is Weakening Bottom Line: BCA's bullish dollar trade was initiated in October 2014 and although the DXY index is up 4% since that time, we are maintaining the trade. While downside risks remain, a unilateral decision by the Trump Administration to leave NAFTA will boost the U.S. dollar versus the Canadian dollar and the peso. Italy's upcoming spring Presidential election could prompt a rally in the dollar if the Eurosceptic parties outperform expectations. John Canally, CFA, Senior Vice President U.S. Investment Strategy johnc@bcaresearch.com 1 Please see BCA Research's U.S. Investment Strategy Weekly Report, "The Great Debate Continues", published on April 17, 2017. Available at usis.bcaresearch.com. 2 Please see BCA Research's U.S. Investment Strategy Weekly Report, "Commitments", published January 20, 2014. Available at usis.bcaresearch.com. 3 Please see BCA Research's U.S. Investment Strategy Weekly Report, "High Conviction Calls", published November 27, 2017. Available at usis.bcaresearch.com. 4 Please see BCA Research's U.S. Bond Strategy Weekly Report, "January Effect", published January 9, 2018. Available at usbs.bcaresearch.com. 5 https://www.congress.gov/bill/108th-congress/house-bill/4520 6 http://www.nber.org/papers/w15023 7 https://www.irs.gov/pub/irs-soi/08codivdeductbul.pdf 8 https://fas.org/sgp/crs/misc/R40178.pdf 9 https://www.cbpp.org/research/tax-holiday-for-overseas-corporate-profits-would-increase-deficits-fail-to-boost-the 10 http://www.cfosurvey.org/2017q4/press-release.html Appendix: Bankers Beige Book Variations On A Theme Variations On A Theme Variations On A Theme Variations On A Theme

Highlights Trade #1: Go Short The December 2018 Fed Funds Futures Contract. The trade has gained 64 bps since we initiated it. We are lifting the stop to 60 bps and targeting a profit of 75 bps. Trade #2: Go Long Global Industrial Stocks Versus Utilities. The trade is up 13.1%. We are targeting a profit of 15%, and are tightening the stop further to 12%. Trade #3: Go Short 20-Year JGBs Relative To Their 5-Year Counterparts. The trade is up 0.7%. We see this as a multi-year trade with significant upside potential. The unwinding of heavy short positions could cause the yen to strengthen temporarily. The euro is vulnerable to negative growth surprises. A retracement of some of its recent gains is likely. Feature Looking Back, Thinking Forward I had the pleasure of speaking at BCA's Annual Investment Conference held in New York on September 27th of last year where I offered three "tantalizing" trade ideas. Chart 1 reviews their performance. They were the following: Trade #1: Go Short The December 2018 Fed Funds Futures Contract We argued last summer that U.S. growth was likely to accelerate, taking rate expectations higher. That has indeed happened. Aggregate hours worked rose by 2.5% in Q4 over the previous quarter. Assuming that productivity increased by 1.5% in Q4 - equal to the pace recorded in Q3 - real GDP probably increased by nearly 4%. A variety of leading indicators point to continued above-trend growth in the months ahead (Chart 2). Chart 1Three Tantalizing Trades: ##br##An Update Three Tantalizing Trades: An Update Three Tantalizing Trades: An Update Chart 2Leading Indicators Pointing ##br##To Above-Trend U.S. Growth Leading Indicators Pointing To Above-Trend U.S. Growth Leading Indicators Pointing To Above-Trend U.S. Growth We think the Fed will raise rates four times this year, one more hike than projected by the dots and roughly 35 bps more in tightening than implied by current market expectations. The median Fed dot calls for an unemployment rate of 3.9% by end-2018, only marginally lower than today's rate of 4.1%. We have been saying for a while that above-trend growth will take the unemployment rate down to a 49-year low of 3.5% by the end of this year. If the unemployment rate falls this much, the Fed will probably turn more hawkish. Stronger inflation numbers should also give the Fed confidence to keep raising rates once per quarter. Core inflation surprised on the upside in December. We expect this trend to continue in the coming months, as the ISM manufacturing index, the New York Fed's Inflation Gauge, and our own proprietary pipeline inflation index are already foreshadowing (Chart 3). Chart 3U.S. Inflation ##br##Should Accelerate U.S. Inflation Should Accelerate U.S. Inflation Should Accelerate Chart 4A Pick-Up In Wage Growth ##br##Would Put Upward Pressure On Service Inflation A Pick-Up In Wage Growth Would Put Upward Pressure On Service Inflation A Pick-Up In Wage Growth Would Put Upward Pressure On Service Inflation As we noted two weeks ago,1 service sector inflation should get a lift from faster wage growth this year (Chart 4). Goods inflation should also rise on the back of higher oil prices and the lagged effects of a weaker dollar (Chart 5). In addition, health care inflation is likely to pick up from its current depressed level, especially if the Congressional Budget Office is correct that insurance premiums will rise due to the elimination of the individual mandate (Chart 6). Housing inflation will moderate, but this is unlikely to stymie the Fed's tightening plans since excessively low interest rates could lead to even more overbuilding in the increasingly vulnerable commercial real estate sector. Chart 5Higher Oil Prices And A Weaker Dollar ##br##Are A Tailwind For Inflation Higher Oil Prices And A Weaker Dollar Are A Tailwind For Inflation Higher Oil Prices And A Weaker Dollar Are A Tailwind For Inflation Chart 6Health Care Inflation ##br##Should Move Higher Health Care Inflation Should Move Higher Health Care Inflation Should Move Higher Granted, four rate hikes equal four opportunities to defer raising rates. It is easy to imagine scenarios where the Fed stands pat, but hard to conjure scenarios where the Fed has to raise rates five times or more this year. Thus, the risk to our four-hike view is to the downside. As such, we will be looking to take profits of 75 bps on the trade, and are putting in a stop of 60 bps. Trade #2: Go Long Global Industrial Stocks Versus Utilities Capital spending tends to accelerate in the late innings of business-cycle expansions. We are in such a phase now, as evidenced by capital goods orders, capex intention surveys, and our global capex model (Chart 7). Increased capital spending will benefit industrial companies. Conversely, rising bond yields will hurt rate-sensitive utilities. Valuations in the industrial sector have gotten stretched, but are not at extreme levels (Chart 8). Based on enterprise value-to-EBITDA, industrials are still only slightly more expensive than utilities compared to their post-1990 average. Chart 7Capex Is Shifting Into ##br##Higher Gear Capex Is Shifting Into Higher Gear Capex Is Shifting Into Higher Gear Chart 8Industrial Stocks: Valuations Are Stretched, ##br## But Not Yet Extreme Industrial Stocks: Valuations Are Stretched, But Not Yet Extreme Industrial Stocks: Valuations Are Stretched, But Not Yet Extreme While we do think global growth will slow this year from the heady pace of 2017, it should remain firmly above-trend. A bigger-than-expected slowdown - especially if it is concentrated in China - would undoubtedly hurt industrials. A stronger dollar could also be a headwind. Thus, we are keeping this trade on a short leash, with a target of 15% and a stop of 12%. Trade #3: Go Short 20-Year JGBs Relative To Their 5-Year Counterparts The Japanese economy is on fire. Growth almost reached 2% in 2017 and leading indicators suggest a solid start to 2018 (Chart 9). The unemployment rate has fallen to 2.7%, a full point below 2007 levels. The ratio of job openings-to-applicants has surpassed its bubble peak. The Tankan Employment Conditions Index is pointing to an exceptionally tight labor market. Wages excluding overtime pay are rising at the fastest pace in twenty years (Chart 10). Chart 9Japanese Growth Momentum Is Positive Japanese Growth Momentum Is Positive Japanese Growth Momentum Is Positive Chart 10Signs Of A Tight Labor Market Signs Of A Tight Labor Market Signs Of A Tight Labor Market Inflation is low but is starting to edge up. The most recent release surprised on the upside. Inflation expectations moved higher on the news, benefiting our long Japanese 10-year CPI swap trade recommendation (Chart 11). A simple scatterplot between the unemployment rate and core inflation suggests the Phillips curve remains intact in Japan -- amazingly, it even looks like Japan (Chart 12)! Chart 11Inflation Expectations Have Edged Higher Inflation Expectations Have Edged Higher Inflation Expectations Have Edged Higher Chart 12The Phillips Curve In Japan Looks Like Japan Three Tantalizing Trades - Four Months On Three Tantalizing Trades - Four Months On Still, with core inflation excluding food and energy running at only 0.3%, there is a long way to go before inflation reaches the BoJ's target -- and even longer if the BoJ honours its promise to generate a meaningful overshoot to compensate for the below-target inflation of prior years. This suggests the BoJ will not meaningfully water down its Yield Curve Control regime anytime soon. As such, five-year yields are likely to stay put while yields with maturities in excess of ten years should move higher. Our "tantalizing trade" being short 20-year JGBs versus their 5-year counterparts still has a long way to run. Too Risky To Short The Yen The exceptionally strong correlation between USD/JPY and U.S. Treasury yields has broken down this year (Chart 13). Had the relationship held, the yen would have actually weakened against the dollar. Still, we are reluctant to get too bearish on the yen (Chart 14). The yen real effective exchange rate is close to multi-decade lows. Positioning on the currency is heavily short. The current account surplus has mushroomed from close to zero in 2014 to 4% of GDP at present. And even if the BoJ keeps the Yield Curve Control regime in place, investors may still anticipate its demise, leading to a temporary bout of yen strength. Chart 13Strong Correlation Is Broken Strong Correlation Is Broken Strong Correlation Is Broken Chart 14Too Risky To Short The Yen Too Risky To Short The Yen Too Risky To Short The Yen What's Propping Up The Euro? The euro has been on a tear since last week, egged on by the ECB minutes, which hinted at a faster pace of monetary normalization. Growing confidence that Angela Merkel will be able to form a grand coalition also helped the common currency, along with hopes that the new government will loosen the fiscal purse strings. The euro is often thought of as the "anti-dollar." And sure enough, the euro's strength has been reflected in a broad-based decline in the dollar index in recent days. BCA's Global Investment Strategy service went long the dollar on October 31, 2014. We "doubled up" on this call in the fall of 2016, controversially arguing that "Trump will win and the dollar will rally." Obviously, in retrospect, I should have rung the register and declared victory on our long dollar view when I had the chance. EUR/USD fell to 1.04 on December 2016, within striking distance of our parity target. Bullish dollar sentiment had reached unsustainably lofty levels. That was the time to sell the greenback. But hubris got the best of me. While our other currency trade recommendations have delivered net gains of 11% since the start of 2017, the long DXY trade has stuck out like a sore thumb. Hindsight is 20/20. The key question is what to do today. EUR/USD is still trading below the level it was at when we went long the DXY. Relative to the IMF's Purchasing Power Parity exchange rate of 1.32, the euro is 7% undervalued. That said, PPP exchange rates may not be a reliable benchmark in this case. Given current market expectations, EUR/USD would need to strengthen to 1.41 over the next ten years just to cover the carry cost of being short the dollar. Even assuming lower inflation in the euro area, that would still leave the euro trading above its long-term fair value. It is possible, of course, that rate differentials will narrow further, but the scope for this is more limited than it might appear. The market currently expects policy rates ten years out to be 95 basis points higher in the U.S., down from a spread of nearly 180 basis points in late December (Chart 15). Given that euro area inflation expectations are 40-to-50 bps lower than in the U.S., this implies a real spread of about 50 bps - broadly in line with our estimate of the real neutral rate gap between the two regions. Ultimately, the fate of the euro in 2018 will rest on the same question that drove the currency in 2017: Will euro area growth surprise on the upside, prompting investors to price in a faster pace of monetary normalization? The bar for success is certainly higher at present. Chart 16 shows that euro area consensus growth estimates have risen significantly since the start of last year. The expected lift-off date for policy rates has also shifted in by more than a year to mid-2019. Considering that Jens Weidmann stated earlier this week that he thinks current market pricing is broadly consistent with when the ECB expects to hike rates, there is little scope for the lift-off date to move forward. Chart 15Little Scope For Rate Differentials ##br## To Narrow Further Little Scope For Rate Differentials To Narrow Further Little Scope For Rate Differentials To Narrow Further Chart 16Euro Area Growth Estimates Have Been Revised Up ##br##Since The Start Of 2017 Euro Area Growth Estimates Have Been Revised Up Since The Start Of 2017 Euro Area Growth Estimates Have Been Revised Up Since The Start Of 2017 Meanwhile, financial conditions have tightened significantly in the euro area relative to the U.S., the euro area credit impulse has turned negative, and the U.S. economic surprise index has jumped above that of the euro area (Chart 17). Euro area inflation has also dipped. Especially worrying is that core inflation in Italy has fallen back to a near record-low of 0.4% (Chart 18). How is Italy supposed to navigate its way out of its debt trap if nominal growth stays this weak? On top of all that, long speculative euro positions have soared to record-high levels (Chart 19). Given the choice of betting whether EUR/USD will first hit 1.30 or 1.15, we would go with the latter. If our bet turns out to be correct, we will use that opportunity to shift to neutral on the dollar. Chart 17The Euro Is Vulnerable ##br##To Negative Growth Surprises The Euro Is Vulnerable To Negative Growth Surprises The Euro Is Vulnerable To Negative Growth Surprises Chart 18Euro Area Core Inflation ##br##Has Dipped Euro Area Core Inflation Has Dipped Euro Area Core Inflation Has Dipped Chart 19Euro Positioning: From Deeply Short ##br##To Record Long Euro Positioning: From Deeply Short To Record Long Euro Positioning: From Deeply Short To Record Long Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com 1 Please see Global Investment Strategy Weekly Report, "Four Key Questions On The 2018 Global Growth Outlook," dated January 5, 2018. Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Neutral The recently released National Restaurant Association's Restaurant Performance Index turned up solidly in November, building on momentum earned in the early parts of 2017 (second panel). Further, the Expectations Index, a reflection of restaurant operators' six-month outlook, rose to its highest level since 2014 (third panel). We are much less sanguine. Consumers have been spending fewer of their dollars in restaurants for the last two years and the trend is now accelerating to the downside at the fastest rate since the GFC (bottom panel). With this deflationary backdrop, rapid sales growth seems overly optimistic. We continue to remain on the fence and reiterate our neutral recommendation. The ticker symbols for the stocks in this index are: BLBG: S5REST - MCD, SBUX, YUM, DRI, CMG. Diners Are Still Pushing Back From The Table Diners Are Still Pushing Back From The Table

Underweight Presenters at this week's Detroit Auto Show have reason to celebrate; December light vehicle sales numbers showed the industry had sold more than 17 million vehicles for a third consecutive year, marking the best winning streak ever for auto makers. Even better, falling pricing appears to be staging a much needed comeback (third panel). The picture is somewhat murkier beneath the surface. J.D. Power reported that average manufacturer incentive spending per unit set a new record in December, exceeding 10% of MSRP for the 17th time in 18 months. At the same time, lenders have continued to clamp down sharply on auto lending (bottom panel), implying that ongoing incentives are required to maintain even the status quo. This is negative to component makers from both a pricing and potentially volume basis. Better growth can be found elsewhere; stay underweight. The ticker symbols for the stocks in the S&P auto components index are: BLBG: S5AUTC - DLPH, BWA, GT. Signs Of Life In Auto Pricing But Beware The Head Fake Signs Of Life In Auto Pricing But Beware The Head Fake

Highlights We are upgrading our allocation to Indian stocks from neutral to overweight within EM equity portfolios. India's public banks are much further along in their necessary adjustment process, and the credit cycle downturn is much more advanced relative to China's. To capitalize on this theme, we recommend going long Indian banks and shorting Chinese bank stocks. India's public bank recapitalization program will allow them to slowly augment credit origination, assisting the economic recovery. Feature Chart I-1Favor Indian Banks Versus Chinese Ones Favor Indian Banks Versus Chinese Ones Favor Indian Banks Versus Chinese Ones Our report this week highlights the results from stress tests we conducted on Indian and Chinese public banks, and also compares their respective equity valuations. Based on our findings, we are initiating a new relative equity trade: long Indian / short Chinese bank stocks (Chart I-1). The health of the banking system, the credit cycle outlook as well as the performance of bank share prices hold the key to relative performance of any bourse in the EM universe. Provided our positive bias toward Indian banks relative to their EM peers on all the above parameters, we are upgrading our allocation to India from neutral to overweight within EM equity portfolios. Indian Versus Chinese Public Banks From 2003 to 2012, India went through a large credit binge and capital misallocation cycle in its industrial and infrastructure sectors. During this period, banks' loans to companies and bank assets rose from 12% to 23% and 63% to 85% of GDP, respectively (Chart I-2A). By comparison, Chinese (ex-policy) commercial banks' claims on companies and their total assets have surged from 85% to 110% and from under 180% to 230% of GDP, respectively, since 2009 (Chart I-2B). In both countries, the banking sector remains dominated by public banks that hold more than 50% of banking system assets. Chart I-2ACredit Boom In Perspective: India Credit Boom In Perspective: India Credit Boom In Perspective: India Chart I-2BCredit Boom In Perspective: China Credit Boom In Perspective: China Credit Boom In Perspective: China Today, Indian public banks - who were the main lenders to industrial companies during the corporate credit binge in the 2003-12 period - have been experiencing mushrooming bad loans. Total public banks' NPLs and distressed asset ratios have reached 13.5% and 2.7% of total loans, respectively (Chart I-3). By contrast, for all Chinese banks, the current NPL ratio is at a mere 1.7%, while the distressed loan ratio stands at only 3.6% of total loans. Chart I-3NPL Ratios In Perspective: India & China NPL Ratios In Perspective: India & China NPL Ratios In Perspective: India & China Further, under pressure from the central bank, Indian public banks have been raising provisioning levels for bad assets very aggressively. On the flip side, Chinese regulators have been following tolerant policies toward their own commercial banks. As such, the provisions-to-loans ratio at all public banks now stands at 3% in China, compared with 5.6% in India. In addition, Chinese banks have bought a lot of corporate bonds that are not provisioned for at all. Does this higher NPL ratio in India relative to China mean that credit allocation is much worse in India? Not quite. The thesis that Indian public banks are more poorly managed than Chinese public banks is not accurate. These banks are managed by public sector executives who often allocate credit to support government growth policies. This is why it is reasonable to assume that the quality of credit allocation among Chinese and Indian public banks is probably similar. As such, we presume that Chinese banks' current NPL ratio is severely understated, and has the potential to rise to levels currently being reported by Indian public banks. The basis is that the Chinese credit boom has dramatically exceeded that of India (see Chart I-2A and I-2B on page 2). Typically, the resulting NPL ratio is proportional to the magnitude of the preceding credit frenzy. Finally, India's central government announced a major recapitalization plan in October 2017 to assist the country's public banks in cleaning up their balance sheets and to also support them in expanding credit. It is likely, therefore, that these banks are now approaching the final stages of their balance sheet repair and deleveraging process. Bottom Line: India's public banks are much further along in their necessary adjustment, and their credit cycle downturn is also much more advanced relative to Chinese banks. The latter have been postponing the inevitable balance sheet clean-up process. To capitalize on this theme, we recommend going long Indian banks and shorting Chinese bank stocks. Banking Stress Test For India And China We have conducted stress tests for India's top seven and China's top five listed public banks. We used the following assumptions for the three scenarios we considered: Non-performing risk-weighted assets (NPA) ratios to rise to 14% (pessimistic), 12% (baseline) and 10% (optimistic scenario) of risk-weighted assets for both Indian and Chinese public banks. Risk-weighted assets adjust banks' various types of assets based on their degree of riskiness. In that way, the risk-weighted asset values are comparable between the two banking systems. We assume a 30% recovery rate in all three NPA scenarios for both countries. The recovery rate on Chinese banks' NPAs in the 2001-2005 period was 20% amid a booming economy. The assumed recovery rate of 30% is therefore not low. The outcome of the stress tests is as follows: In the baseline scenario of 12% NPA, the losses post recovery and provisions would amount to 1.3 trillion rupees in India (0.9% of GDP) and RMB 3.4 trillion in China (4.2% of GDP). This would translate into a 33% equity impairment for India's seven public banks, and 48% for China's five public banks (Table I-1 and I-2, column 7). Table I-1Stress Test For Top 7 Indian Public Banks Long Indian / Short Chinese Banks Long Indian / Short Chinese Banks Table I-2Stress Test For Top 5 Chinese Public Banks Long Indian / Short Chinese Banks Long Indian / Short Chinese Banks From a valuation standpoint, the post-impairment price-to-book value (PBV) ratio would jump to 1.44 and 1.62 for Indian- and Chinese-listed public banks, respectively. Assuming a fair PBV ratio of 1.3 - which is the average PBV ratio for all EM banks since 2011 - Indian public banks are 11% overvalued and Chinese ones are about 25% overvalued. In other words, if one were to calculate the true PBV ratio of these banks after a comprehensive "clean-up" has been done, then Indian public bank stocks would be cheaper than Chinese ones. It is important to note that the above valuation exercise does not take into consideration banks' future profits. As such, we account for their recurring profits in the following manner: Table I-3 calculates the ratio of NPA losses to banks' recurring net profits before provisioning. Losses are the amount to be written-off post provisioning and recovery. In the baseline scenario of a 12% of NPA, this ratio is 2.5 for India and 3.4 for China. In other words, it will take 2.5 and 3.4 years of net profits before provisions close the "black hole" of NPA losses (post provisions and recovery) in India and China, respectively. Hence, on this measure as well, India's listed public banks appear more appealing than those in China. Table I-3Profit Coverage Of Loan Losses Long Indian / Short Chinese Banks Long Indian / Short Chinese Banks There is a caveat regarding Chinese banks' stress and their post-impairment book value. Our analysis is performed based on risk-weighted assets, and does not include off-balance-sheet assets. Therefore, any losses from off-balance-sheet assets will make losses for Chinese public banks greater than our analysis captures. Further, the Chinese financial authorities are currently tightening regulations, which will likely curtail banks' off-balance-sheet activities and by extension their profitability. These risks are not present in India, where banks have less off-balance-sheet assets. Bottom Line: Public bank stocks are currently overvalued by about 11% and 25% in absolute terms in both India and China, respectively. This favors Indian bank share prices outperforming their Chinese peers. The fact that the "clean-up" has not yet begun in China reinforces this trade. Banks' Recapitalization In India Saddled with NPLs, Indian public banks have not been willing to lend in recent years. Chart I-4 demonstrates that their loan growth has stalled. Credit to large industrial companies has in particular suffered (Chart I-4, bottom panel), as most of this type of credit is typically extended by public banks. Chart I-4India: Public Bank Loan Growth Has Slumped India: Public Bank Loan Growth Has Slumped India: Public Bank Loan Growth Has Slumped Consequently, India's capital expenditures have languished in recent years, weighing not only on cyclical growth but also depressing long-term productivity and potential growth. In October, the Indian government announced an estimated 2.11 trillion rupees public bank recapitalization program that will be implemented over the next two years. The program is for all public banks, while the above stress test was performed for only the top seven listed public banks. The latter account for around 60% of all public banks' assets, so we assume they will get around 60% of the stated recapitalization amount. The recapitalization program is designed as follows: The central government plans to inject 180 billion rupees of equity capital into all public banks via budgetary allocations. The public banks will in turn raise 580 billion rupees from the market. The remaining 1,350 billion rupees will come from government-issued Bank Recapitalization Bonds. The government will issue bonds to banks and then use the funds to buy more shares from public banks. It is important to note that in the stress test above and for the calculation of post-impairment PBV ratios, we assume the government will not subsidize existing shareholders when it injects money into public banks. This means the government will provide equity capital to public banks at post-impairment equity value - i.e., at a fair market price. It will be difficult for the Indian government to bail out its public banks without making current shareholders bear losses. If the government bails out public banks' private and foreign shareholders, the opposition parties will use the bank recapitalization program against Prime Minister Narendra Modi's government in the general elections scheduled to be held in 2019. Many investors and commentators assume that India's bank recapitalization program is automatically bullish for bank share prices. While it is positive for banks' ability to lend and drive growth in the medium and long term, the program is not necessarily bullish for share prices, particularly at their current high levels. The same is true for potential recapitalization programs in China. Overall, odds are that current shareholders of public banks will likely shoulder meaningful losses in India and possibly in China as well. How well off will capitalized public banks in India be after implementation of the recapitalization program? In the case of the seven Indian public banks we performed the stress test on, Table I-4 estimates that post-impairment and recovery, the total equity capital-to-risk-weighted assets ratio will be 8% in our baseline scenario. This is lower than the regulatory minimum of 9%. Table I-4Capital Ratios For India's Top 7 Public Banks Long Indian / Short Chinese Banks Long Indian / Short Chinese Banks The recapitalization will bring this equity capital adequacy ratio to 11.3%, which exceeds the regulatory minimum of 9%. Hence, after the program is completed, Indian public banks will likely become well capitalized and will be able to resume their lending and expand their assets. This in turn will facilitate the economic recovery. Bottom Line: The Indian government's recapitalization program is sufficient to raise public banks' capital adequacy ratio above the regulatory minimum. This will allow public banks to resume their lending. India's Cyclical Growth Outlook India's cyclical outlook will be one of muted recovery. Yet it is superior to other EMs, where we expect meaningful deceleration due to a potential slowdown in China and a rollover in commodities prices. Public banks' recap program will be slow in India - to be conducted over the next two years - and banks' ability to boost lending will improve only gradually. Meanwhile, private banks have and will probably continue to concentrate their lending efforts on consumers rather than on industrial companies and infrastructure. In the next 12-18 months, a slow improvement in public banks' ability to originate credit will allow only moderate improvement in capital spending growth. The latter is required to resolve bottlenecks and unleash the nation's productivity potential. Several indicators of capital spending are lukewarm (Chart I-5, top panel). However, new capex project announcements and the number of investment proposals have been dropping (Chart I-5, middle panel). Surprisingly, companies' foreign external borrowing is still contracting, despite booming capital inflows into EM (Chart I-5, bottom panel). On the consumer side, the outlook remains bright. Motorcycle sales have recovered sharply and commercial vehicle sales are beginning to pick up (Chart I-6). Chart I-5India's Capital Spending Is Sluggish India's Capital Spending Is Sluggish India's Capital Spending Is Sluggish Chart I-6Indian Consumer Health Is Strong Indian Consumer Health Is Strong Indian Consumer Health Is Strong Consumer/personal loans are accelerating from an already strong growth rate, largely thanks to the aggressiveness of private sector banks (Chart I-6, bottom panel). In turn, the employment outlook is finally beginning to show signs of improvement (Chart I-7). The manufacturing PMI has also risen substantially, and is currently in expansion territory (Chart I-8). Likewise, the service sector PMI has bounced above 50. Chart I-7India's Employment Is Turning The Corner India's Employment Is Turning The Corner India's Employment Is Turning The Corner Chart I-8India: PMIs Are Positive India: PMIs Are Positive India: PMIs Are Positive Finally, India is less exposed to China's growth and a retracement in commodities prices than many other emerging economies. This makes us upbeat on India's cyclical economic dynamics and relative equity and currency performance versus other EMs. Bottom Line: India's cyclical outlook is better than that of many other EMs. Structural Tailwinds And Impediments India holds huge promise for investors as it is a much-underinvested economy, and potential return on capital is considerably higher in those countries than in relatively overinvested ones. In addition, its population and labor force growth are among the highest in mainstream developing countries. On the other hand, for such potential to be realized, the country needs to be able to boost its productivity. On this count, the outlook is less positive. India's share of global goods and services exports has declined substantially since 2011 (Chart I-9). This should not be surprising, given weak investment spending has led to stagnation in trade competitiveness. Chart I-10 reveals that based on the UNCTAD1 dataset, India has been losing market share in both low- and high-skilled labor sectors export markets worldwide. Chart I-9India's Share In Global Trade India's Share In Global Trade India's Share In Global Trade Chart I-10India Has Been Losing Export Market Share India Has Been Losing Export Market Share India Has Been Losing Export Market Share While certain reforms such as the introduction of a sales tax will have a positive impact on the economy, other much-needed changes, such as land and labor market reforms, have so far remained unattainable. Moreover, the agriculture sector still faces material challenges. Without these vital reforms, it will be difficult to boost efficiency and productivity and build global competitiveness. Finally, in terms of education enrollment, India lags other EMs, especially China, in tertiary education (Chart I-11). This makes it even more difficult to boost productivity and growth potential. Bottom Line: India has great secular potential, but the structural advance has stalled since 2011. The jury is still out on whether it can implement additional reforms to realize this potential. Investment Conclusions India's banking sector outlook is brighter, and the deleveraging cycle is much more advanced, compared with many other EMs in general and China in particular. Therefore, we recommend a new relative equity trade: long Indian banks / short Chinese banks. Investors could buy Indian public banks or all banks with the understanding that private banks are typically in better shape than their state-owned peers, but are also much more expensive. We will be tracking this trade's performance using the Bankex index for India and the MSCI bank index for China. The Bankex index has a larger share of market cap of public banks than the MSCI India bank index. Within China, we are maintaining our short small and medium / long large banks position initiated on October 26th 2016. We are also recommending EM equity investors upgrade the Indian bourse from neutral to overweight. We shifted Indian stocks from overweight to neutral on August 23rd 2017, but the risk-reward has improved since then (Chart I-12). Chart I-11India's Education Improvement Is Lagging India's Education Improvement Has Stalled India's Education Improvement Has Stalled Chart I-12Upgrade Indian Bourse Within EM Universe Upgrade Indian Bourse Within EM Universe Upgrade Indian Bourse Within EM Universe Our primary concerns with EM stocks are a China slowdown, a rollover in commodities prices and a rebound in the U.S. dollar. Associated strains in countries with large foreign debt levels or wide current account deficits as well as lack of credit deleveraging and bank recapitalization will define EM financial markets' performance in the next 12-18 months. On all of these counts, India scores better than many EMs, justifying this equity upgrade. The absolute outlook for Indian stocks, however, is not inspiring. This equity market is rather expensive and overbought in absolute terms. If EM risk assets experience a setback in 2018, as we expect, Indian equities will also relapse in absolute terms. Ayman Kawtharani, Associate Editor ayman@bcaresearch.com Arthur Budaghyan, Senior Vice President Emerging Markets Strategy arthurb@bcaresearch.com   1 United Nations Conference on Trade and Development.   Equity Recommendations Fixed-Income, Credit And Currency Recommendations

America's banks appear to have finished off 2017 with stellar core earnings as some of the largest lenders, including JPM, WFC and C, have all reported strengthening net interest income and loan growth while delivering EPS ahead of estimates. These earnings reports serve as early validation of our high-conviction investment thesis for banks, namely that bank profits should exceed expectations as the price of credit, loan growth and credit quality move steadily higher in the year to come. Rising inflation expectations (second panel) should keep a tailwind behind the 10-year yield, driving improving net interest margins (third panel). Combined with record low unemployment and the associated low default rates, margins should widen; EPS should soar as a result. We reiterate our high conviction overweight recommendation. The ticker symbols for the stocks in this index are: BLBG: S5BANKX - WFC, JPM, BAC, C, USB, PNC, BBT, STI, MTB, FITB, CFG, RF, KEY, HBAN, CMA, ZION, PBCT. Banks Start Q4 Earnings With A Bang Banks Start Q4 Earnings With A Bang