Health Care

In lieu of the next weekly report I will be presenting the quarterly webcast ‘The Japanification Of Europe: Should We Fear It, Or Celebrate It?’ on Monday 4 November at 10.00AM EST, 3.00PM GMT, 4.00PM CET, 11.00PM HKT. As usual, the webcast will take a TED talk format lasting 18 minutes, after which I will take live questions. Be sure to tune in. Regards, Dhaval Joshi Highlights Global and European growth is experiencing a welcome rebound. Favour a cyclical investment stance, albeit tactical – as there is no visibility in the growth rebound beyond early 2020. Close the overweight to healthcare versus industrials at a small profit. Upgrade Sweden and Spain to overweight, and Norway to neutral. Downgrade Denmark to underweight, and Ireland to neutral. Expect heightened volatility in sterling in the build up to a highly ‘non-linear’ UK election. Fractal trades: 1. long oil and gas versus telecom; 2. long tin. Feature Global and European growth is experiencing a welcome rebound. This we can see from the best real-time indicators of activity, such as the ZEW sentiment, IFO expectations and of course the equity and bond markets (Chart of the Week). Nevertheless, investors make three very common mistakes in interpreting, predicting, and implementing such rebounds. This week’s report describes these three mistakes and the underlying realities. Chart of the WeekGrowth Is Experiencing A Welcome Rebound Mistake #1: Real-Time Indicators Do Not Lead The Market Reality #1: In the short term, markets move in lockstep with indicators such as the ZEW sentiment, IFO expectations, and PMIs (Chart I-2). Chart I-2Economic Indicators Do Not Lead The Markets... Having said that, the evolution of economic indicators can still provide a useful long-term investment signal. If an indicator – like IFO expectations – tends to revert to its mean, and is now near its historical lower bound, the scope for an eventual move up is greater than the scope for a further move down.1 Based on such a reversion to the mean, we are maintaining a structural overweight to the DAX versus the German long bund (Chart I-3). Chart I-3...But Depressed Performances Have Scope For Long-Term Upside But to reiterate, in the short term, the market moves in lockstep with the real-time economic indicators. Hence, to get a useful short-term investment signal, we need to predict where these indicators will be in the coming months – in other words, to predict whether growth will continue to accelerate. In the short term, the market moves in lockstep with real-time economic indicators.  Which brings us neatly to the second mistake. Mistake #2: When Financial Conditions Ease, Growth Does Not Necessarily Accelerate Reality #2: It is not the change of financial conditions but rather its impulse – the change of the change – that causes growth to accelerate or decelerate. For example, a 0.5 percent decline in the bond yield decline will trigger new borrowing through, inter alia, an increase in the number of mortgage applications. The new borrowing will add to demand, meaning it will generate growth. But in the following period, a further 0.5 percent decline in the bond yield will generate the same additional new borrowing and thereby the same growth rate. The crucial point being that if the decline in the bond yield is the same in the two periods, growth will not accelerate. Growth will accelerate only if the first 0.5 percent bond yield decline is followed by a bigger, say 0.6 percent, decline – meaning a tailwind impulse. But growth will decelerate if the first 0.5 percent decline is followed by a smaller, say 0.4 percent, decline – meaning a headwind impulse. To repeat, the counterintuitive thing is that for a growth acceleration it is not the change in the bond yield that is important but rather its impulse. There are four impulses that matter for short-term growth: The bond yield 6-month impulse. The credit 6-month impulse. The oil price 6-month impulse (for oil importing economies like Germany). The geopolitical risk impulse. To be clear the geopolitical risk impulse is not an impulse in the technical sense, but it is a similar concept: is the number of potential geopolitical tail-events going up or down? In the fourth quarter, our subjective answer is down. The Brexit deadline has been pushed back to January 31 2020; the new coalition government in Italy has removed Italian politics as an imminent tail-event; and the US/China trade war and Middle East tensions are most likely to be in stasis. Turning to the other impulses, the credit 6-month impulse should briefly rebound in the fourth quarter following the rebound in the global bond yield 6-month impulse (Chart I-4). All of this favours a cyclical investment stance – albeit tactical, because there is no visibility in this growth rebound beyond early 2020. Chart I-4The Credit 6-Month Impulse Should Briefly Rebound Meanwhile, the recent evolution of the oil price 6-month impulse should provide an additional short-term tailwind for oil importing economies (Chart I-5). Justifying a near-term overweight stance to the cyclical heavy German stock market within a European or global equity portfolio. Chart I-5The Oil Price 6-Month Impulse Should Help Oil Importing Economies Which brings us to the third mistake. Mistake #3: Major Stock Markets Are Not Plays On Their Economies Of Domicile Reality #3: Major stock markets are dominated by multinational corporations, and such companies are plays on their global sectors, rather than the country in which they have a stock market listing. Hence, a stock market’s relative performance is predominantly a play on its distinguishing overweight and underweight ‘sector fingerprint’. What confuses matters is that sometimes the sector fingerprint happens to align with the tilt of the domicile economy. Germany has an exporter heavy stock market and an exporter heavy economy while Norway has an oil heavy stock market and an oil heavy economy, so in these cases there is a connection between the stock market and the economy. But in most instances, there is no alignment: the connection between the UK stock market and the UK economy is minimal, and the same is true in Spain, Denmark, Ireland, and most other countries. When bond yields were declining most sharply, and growth was decelerating, it weighed on cyclical sectors such as industrials and banks versus the more defensive sectors such as healthcare. Banks suffered doubly because the flattening (or inverting) yield curve also ate into their margins. But if the sharpest decline in bond yields has already happened, it suggests that cyclicals could experience a burst of outperformance, at least for a few months (Chart I-6). Hence, today we are closing our four month overweight to healthcare versus industrials at a small profit. Chart I-6If The Sharpest Decline In Bond Yields Is Over, Cyclicals Could Outperform Based on sector fingerprints, this also necessitates the following changes to our country allocation: Overweight banks versus healthcare means overweight Sweden versus Denmark (Chart I-7). Chart I-7Long Sweden Versus Denmark = Long Financials And Industrials Versus Biotech Overweight banks means overweight Spain (Chart I-8). Chart I-8Long Spain = Long Banks Meanwhile, removing our underweight to the cyclical oil sector means removing the successful underweight to Norway (Chart I-9). And indirectly, it means removing the equally successful overweight to Ireland, given its high weighting to Airlines (Chart I-10).  Chart I-9Long Norway = Long Oil And Gas Chart I-10Long Ireland = Long Airlines   Bonus Mistake: You Can Not Hit A Point Target In A Non-Linear System Boris Johnson said that he “would rather be dead in a ditch” than miss the October 31 deadline for delivering Brexit. Well Johnson had to ditch his ditch. Why? Because the UK’s parliamentary arithmetic has made Brexit an inherently non-linear system, and you cannot hit a point target in a non-linear system. Boris Johnson had to ditch his ditch. In a non-linear system a tiny change in an input might have no impact on the output, or it might have a huge impact on the output. The Brexit process is inherently non-linear because a tiny shift in parliamentary votes one way or another, or a tiny shift in the tabled amendments to laws one way or another has had a huge impact on the outcome. That’s why it proved impossible for Johnson to hit his point target of delivering Brexit by October 31. Attention now shifts to another non-linear system – the upcoming UK general election. The UK’s first past the post electoral system is designed for a head-to-head between two dominant parties. But right now, there are five parties in play – Labour, Liberal Democrat, Conservative, Brexit, plus the SNP in Scotland. Mathematically, this creates the possibility of ten types of swings, compared with the usual single swing between Labour and Conservative. Making the outcome of the election highly sensitive to a tiny shift in votes either way in ten different directions. The UK general election is a non-linear system. In The Pound Is A Long Term Buy (And So Are Homebuilders) we initiated a structural long position in the undervalued pound.2 Given that our overweight to the international focused FTSE100 versus the domestic focussed FTSE250 is effectively an inverse play on the pound, it is inconsistent with our long-term view on the currency (Chart I-11). Nevertheless, over the course of the election campaign we expect heightened volatility in sterling as the non-linearity of the election outcome becomes clear. Hence, we await an upcoming better opportunity to remove our overweight FTSE100 versus FTSE250 position. Chart I-11Long FTSE250 Versus FTSE100 = Long Pound Fractal Trading System* There are two recommended trades this week. The underperformance of US oil and gas versus telecom is ripe for a technical rebound based on its broken 130-day fractal structure. Go long US oil and gas versus telecom, setting a profit target and symmetrical stop-loss at 8 percent. The recent sell-off in tin is undergoing a similar technical bottoming process. Go long tin, setting a profit target and symmetrical stop-loss at 5 percent. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment’s fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-12US: Oil & Gas Vs. Telecom Chart I-13Tin The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions. * For more details please see the European Investment Strategy Special Report “Fractals, Liquidity & A Trading Model,” dated December 11, 2014, available at eis.bcaresearch.com.   Dhaval Joshi Chief European  Investment Strategist dhaval@bcaresearch.com Footnotes 1 In technical terms, if the time-series is ‘stationary’, it must eventually rebound from its lower bound. 2 Please see the European Investment Strategy Weekly Report, "The Pound Is A Long-Term Buy (And So Are Homebuilders)," dated October 17, 2019 available at eis.bcaresearch.com Fractal Trading System Cyclical Recommendations Structural Recommendations Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields   Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Chart II_8Indicators To Watch - Interest Rate Expectations  

Special Report

Highlights In this report, we build and present models designed to predict the odds of Chinese investable equity sector outperformance, based on a set of macroeconomic and equity market factors. BCA Research's China Investment Strategy service will aim to use our newly developed sector outperformance probability models to help investors to better understand the drivers of performance at any given moment, and to make more active equity sector recommendations in the future. Among the top six factors explaining historical periods of sector performance, three were macroeconomic in orientation, and two were directly related to the broad Chinese equity market. We see this as strongly supportive of the potential returns to be earned from active top-down sector rotation within China’s investable market. Cyclical stocks are very depressed relative to defensives, and we would favor them versus defensives over the coming year if China strikes a trade deal with the US and the Chinese economy incrementally improves, as we expect. Feature In our June 19 Special Report, we reviewed the predictability and cyclicality of equity sector earnings in China's investable & domestic markets, and examined the relevance of earnings in predicting relative sector performance over the past decade. We noted that a few sectors scored highly in terms of earnings predictability and the relevance of those earnings in predicting relative performance. But we also highlighted that most of China's equity sectors, in both the investable and domestic markets, either demonstrated earnings trends that were difficult to predict based on the trend in overall market earnings or exhibited relative performance that was difficult to explain based on the relative earnings profile. Our models are designed to predict equity sector relative performance using a series of macroeconomic and equity market factors. In short, our June report underscored that China’s equity sectors warranted a closer examination, with a particular emphasis on understanding the specific macroeconomic or equity market factors that have historically predicted relative sector performance. Today’s report examines this question in depth, focused on China’s investable equity market. We hope to extend our research to the A-share market in the near future. Our approach focuses on constructing and presenting models that quantify a checklist-based approach to determining the odds of equity sector performance. The aim is to use these models to better understand the drivers of performance at any given moment, and to make more active equity sector recommendations in the future. These recommendations will not mechanically follow the models; rather, we plan to use them as a stand in for what typically would be expected given the macro and financial market environment, and as a basis to investigate “abnormal” relative performance. We conclude by highlighting the substantial underperformance of cyclical vs defensives sectors over the past two years, and argue that it is highly unlikely that cyclicals will underperform defensives over the coming 12 months if China strikes a trade deal with the US and the economy incrementally improves, as we expect. We also explain the importance of monitoring the relative performance of health care & utilities stocks over the coming few months, and present a unique sector-based barometer for gauging China’s reflationary stance. The latter two relative performance trends are likely to assist investors in positioning for the big call: the outperformance of Chinese investable stocks vs the global benchmark. Detailing Our Approach In our effort to better understand historical periods of sector outperformance, we have chosen to model the probability of outperformance of each level 1 GICS sector (plus banks) based on a set of macro and equity market variables. Specifically, we use an analytical tool called a logistic regression, which forecasts the probability of a discrete event rather than forecasting the value of a dependent variable. We utilized this approach when building our earnings recession model for China (first presented in our January 16 Special Report1), and investors will often see it (in its conceptually different but practically similar probit form) employed when analyzing the likelihood of an economic recession. The New York Fed’s US recession model is a notable example of the latter,2 which has received much attention by market participants over the past year following the inversion of the US yield curve. The “events” that we modeled are historical periods of individual Chinese investable sector outperformance from 2010 to 2018, relative to the MSCI China index (the “broad market”). Charts I-1A and I-1B illustrate these periods with shading in each panel. We then attempt to explain these episodes of outperformance with the following macro predictors: Chart I-1AThis Report Builds Models Aimed At... Chart I-1B...Predicting The Shaded Regions Of These Charts Periods of accelerating economic activity, represented by our BCA's China Activity Index Periods of rising leading indicators of economic activity, represented by our BCA Li Keqiang Leading Indicator Episodes of tight monetary policy, defined as periods where China’s 3-month interbank repo rate is rising Periods of accelerating inflation, measured both by headline and core inflation We also include several equity market variables: uptrends in relative sector earnings, periods of rising broad market stock prices, uptrends in broad market earnings, and episodes of extreme technical conditions and relative over/undervaluation for the sector in question. In the case of energy stocks, we also include oil prices as a predictor. Charts I-2A and I-2B illustrate these periods as well as the macro & market variables that we have included as predictors. Chart I-2AWe Use These Macroeconomic And Equity Market Factors... Chart I-2B...To Predict Periods Of Equity Sector Outperformance Our approach also accounts for the existence of any leading or lagging relationships between the macro and market variables we have used as predictors and sector relative performance. In most cases the predictors lead relative sector performance, but in some cases it is the opposite. In the case of the latter, we have limited the lead of any variable in our models to 3 months in order to reduce the need to forecast. The link between tight monetary policy and industrial sector performance is one exception to this rule that we detail below. Finally, our approach also limits the extent to which we consider a leading relationship between our predictors and relative sector performance, in order to avoid picking up overlapping economic cycles. This issue, and the evidence supporting the existence of a 3½-year credit cycle in China, are detailed in Box 1. Box 1 Accounting For China’s 3½-Year Credit Cycle Over the course of the analysis detailed in this report, judgments concerning how much of a lead or lag to allow when accounting for any leading or lagging relationships between sector relative performance and either macroeconomic & stock market predictors were necessary. In cases where sector relative performance led any of our predictors, we capped the lead at 3-months to reduce the need to forecast the predictors when using the models. As explained below, the 8-month lead between industrial sector relative performance and tight monetary policy was the only exception to this rule. We also did not include any leading relationship between relative sector stock performance and the trend in relative sector EPS, and allowed at most a co-incident relationship. Limits were also required in the cases where our predictors led relative sector performance. While more lead time is usually better from the perspective of investment strategy, Chart I-B1 presents strong evidence of a 3½ -year credit cycle in China. Chart I-B2 illustrates the problem with including significant lags between predictors and relative sector performance when economic cycles are short. The chart shows the lead/lag correlation profile of the stylized cycle shown in Chart I-B1, and highlights that lags greater than 12-14 months risk picking up the impact of the previous economic cycle. Given this, we have limited the extent to which our predictors can lead relative sector performance in our models, and in practice lead times are generally less than one year. Chart I-B1Over The Past Decade, China Has Experienced A 3½-Year Credit Cycle Chart I-B2With Short Cycles, Excessive Lags Risk Picking Up The Previous Cycle The Key Drivers Of Chinese Investable Equity Sectors Pages 12-23 present the results of each sector’s outperformance probability model, along with a list of factors that were found to be useful predictors and a summary of the results. The importance of the factors included in the models is shown in each of the tables at the top right of pages 12-23 by a score of 1-3 stars, (loosely representing key levels of statistical significance) as well as each factor’s optimal lead or lag. A minus sign shows that the predictor leads sector relative performance, whereas a plus sign shows that it lags. Rising core inflation in China is the most important signal of sector performance that emerged from our analysis. Chart I-3China’s Sectors Linked Strongly To Core Inflation, Monetary Policy, And Growth Chart I-3 summarizes the significance of the factors in predicting sector performance in general, by summing up each predictor’s number of stars across all of the models. The chart shows that rising core inflation in China is the most important signal of sector performance that emerged from our analysis, followed by tight monetary policy, rising economic activity, rising broad market stock prices, oversold technical conditions, and rising broad market earnings. Chart I-3 highlights two important points: If regarded through the lens of causality alone, the strong relationship between rising core inflation and sector performance is somewhat surprising: normally, pricing power is subordinate to revenue/sales/demand as the primary factor driving fundamental performance. However, given that inflation is a lagging economic variable, we suspect that the significance of inflation in our models actually reflects the middle phase of the economic cycle in which sectors tend to best exhibit meaningful out/underperformance. It is also a stronger predictor of periods of tight monetary policy in China than headline inflation.3 This is an encouraging result for investors, as it suggests good odds that future episodes of meaningful sector outperformance can be identified given a particular macro view. Among the top six factors explaining historical periods of sector performance, three were macroeconomic in orientation, and two were directly related to the broad Chinese equity market. While Chinese equity sector performance can sometimes be idiosyncratic, we see this as strongly supportive of the idea that investors can earn positive excess returns by actively shifting between China’s equity sectors using a top-down approach. Turning to the specific results of our sector models, we present the following big-picture findings of our research: Defining China’s Cyclical & Defensive Sectors From a top-down perspective, the most important element of sector rotation typically involves shifting from defensive to cyclical stocks when economic activity is set to improve (and vice versa). In China, it is clear from the results of our models that the investable energy, materials, industrials, consumer discretionary, and information technology sectors are cyclical sectors. The relative performance of these sectors exhibits a positive relationship to pro-cyclical macro variables, or broad market trends. Following last year’s GICS changes, we also include the media & entertainment industry group (within the new communication services sector) in this list. Correspondingly, investable consumer staples, health care, financials, telecom services, utilities, and real estate are defensive sectors in China. Chart I-4Cyclical Stocks Are Bombed Out Versus Defensives Chart I-4 illustrates how these sectors have performed over the past decade by grouping them into equally-weighted cyclical and defensive stock price indexes, as well as the relative performance of cyclicals versus defensives. The chart makes it clear that cyclical stock performance is essentially as weak as it has ever been relative to defensives over the past decade, with the exception of a brief period in 2013. Panel 2 highlights that all of the underperformance of cyclicals over the past two years has been due to de-rating, rather than due to underperforming earnings. The Atypical Case Of Financials & Real Estate The fact that financial and real estate stocks are defensive in China is somewhat curious. In the case of financials, the abnormality is straightforward: most global equity portfolio managers would consider financials to be cyclical, and our work suggests that this is not true for the investable market. Our explanation for this apparent discrepancy is also straightforward: while small and medium banks in China have obviously grown in prominence over the past decade, large state-owned or state-affiliated commercial banks are still dominant in the provision of credit to China's old economy. In most cases China’s large banks lend to state-owned enterprises with implicit government guarantees, meaning that the earnings risk for Chinese banks has typically been lower than for the investable market in the aggregate. It remains to be seen whether this will remain true in a world where Chinese policymakers are keen to slow the pace at which China’s macro leverage ratio rises and to render the existing stock of debt more sustainable for the non-financial sector. Indeed, over a multi-year time horizon, the risk are not trivial that banks will be forced to recapitalize as a result of forced changes to loan terms (eg: significant increases in the amortization period of existing loans) or the recognition of sizeable loan losses, which would clearly increase the cyclicality of the Chinese investable financial sector. Chart I-5A Seeming Contradiction: Real Estate Is High-Beta, But Defensive On the real estate front, the anomaly is not that real estate stocks respond defensively to macroeconomic and stock market variables, it is that real estate stock prices are considerably more volatile than this defensive characterization would suggest. Globally (and especially in the US), real estate stocks are often viewed as bond proxies and thus are typically low-beta, but Chart I-5 shows that this is not the case in China. In our view, this issue is reconciled by the fact that Chinese investable real estate stocks are also highly positively linked to Chinese house price appreciation, with relative performance typically leading a pickup in house prices by up to 1 year. This strongly leading relationship has meant that real estate stocks have often outperformed the broad market as economic activity is slowing, in anticipation that policy easing will lead to an eventual recovery in house prices. Chart I-6Still Following The Defensive Playbook This Year In effect, investable real estate stocks are a high-beta sector that have acted counter-cyclically due to the historical interplay between economic activity, monetary policy, and the housing market. Real estate performance this year has not deviated from this playbook (Chart I-6), and so for now we are content to include real estate stocks in our defensive index. But similar to the case of financials, we can conceive of scenarios in which ongoing Chinese financial sector reform may change this relationship in the future. The Unique Monetary Policy Sensitivity Of Industrials And Consumer Staples Pages 14 and 16 highlight that industrials and consumer staples stocks have typically been sensitive to periods of tight monetary policy. In the case of industrials the relationship is negative, whereas consumer staples relative performance has been positively linked to these periods. In both cases, relative performance has led periods of tight monetary policy, significantly so in the case of industrials (by an average of 8 months). While the relative performance of banks, tech, and real estate stocks have also been linked to periods of tight monetary policy, industrials and consumer staples are the only sectors that have tended to lead these periods. Chart I-7Diverging Corporate Health Explains Industrials/Staples Monetary Policy Sensitivity This is a revelatory finding, and in our view it is explained by divergences in corporate health and leverage for the two sectors. We reviewed Chinese corporate health in our August 28 Special Report,4 and noted that the food & beverage sub-industry was a clear (positive) outlier based on our corporate health monitors. In particular, Chart I-7 highlights that food & beverage corporate health is markedly better than that for machinery companies or for industrial firms in general, supporting the notion that high (low) leverage is impacting the relative performance of industrials (consumer staples). The Leading Nature Of Health Care & Utilities Health care and utilities exhibit similar key drivers of relative performance: in both cases, periods of rising economic activity, rising core inflation, and rising broad market stock prices are all negatively associated with performance. Health care and utilities relative performance also happens to lead all three of those predictors, by 1-3 months on average depending on the variable in question. Our modeling work highlights that these are the only sectors whose relative performance has led multiple factors, suggesting that health care & utilities stocks are particularly interesting market bellwethers to monitor. Core Inflation Matters More Than Headline, Except For Energy & Real Estate As highlighted in Chart I-3, rising core inflation has been a much more important signal about relative sector performance than headline inflation. Chart I-8In China, Food Prices (Not Energy) Account For Headline/Core Differences The two exceptions to this rule relate to the energy and real estate sectors, with the former positively linked to headline inflation and the latter negatively linked. In both cases, we suspect that the relationship is a behavioral rather than a fundamental one. For energy, while rising headline inflation in developed countries is usually associated with rising energy prices, this is not true in the case of China. Chart I-8 highlights that differences between headline and core inflation over the past decade have almost always been driven by rising food prices. This implies that some investors (incorrectly) view energy stocks as a hedge against increases in consumer prices, even if those increases are not driven by rising fuel costs. In the case of real estate, investor expectations of eroding real disposable income and its impact on the housing market are likely the best explanation for the negative link between real estate relative performance and rising headline inflation. Whereas rising core inflation likely reflects a durable improvement in economic momentum (and thus would be positively correlated with income growth), episodes of rising Chinese headline inflation often reflect supply shocks that investors may perceive to be detrimental to household spending power (and thus expected housing demand). Investment Conclusions Our work aimed at explaining historical periods of Chinese investable sector outperformance has three investment implications in the current environment. Cyclicals will probably outperform defensives over the coming year if China strikes a trade deal with the US and the Chinese economy incrementally improves, as we expect. First, within China’s investable market, Chart I-4 illustrated that cyclical stocks are very depressed relative to defensives. Given our view that Chinese investable stocks are likely to outperform their global peers over a 6-12 month time horizon, we would also favor cyclicals to defensives over that period. For investors who are not yet overweight cyclical stocks in China, we would advise waiting for concrete signs that growth has bottomed (which should emerge sometime in Q1) before putting on a long position as we remain tactically neutral towards Chinese versus global stocks. But the key point is that it is highly unlikely that cyclicals will underperform defensives over the coming year if China strikes a trade deal with the US and the Chinese economy incrementally improves, as we expect. Second, the fact that investable health care and utilities stocks have particularly leading properties suggests that they should be monitored closely over the coming few months. A technical breakdown in the relative performance of these sectors would be an important sign that market participants are anticipating a bottoming in China’s economy, which may give investors a green light to position for a bullish cyclical stance. For now, both of these sectors continue to outperform (Chart I-9), supporting our decision to remain tactically neutral towards Chinese stocks. Third, the heightened negative sensitivity of industrials and positive sensitivity of consumer staples to monetary policy suggests that the relative performance trend between the two sectors may serve as a reflationary barometer for China’s economy. Chart I-10 shows that industrials outperformed staples last year once the PBOC shifted into easing mode, and anticipated the recovery in the pace of credit growth. However, industrials soon began to underperform staples, which also seems to have anticipated the fact that the recovery in credit was set to be less powerful than what has occurred during previous cycles. The fact that the relative performance trend is off its recent low is notable, and may suggest that China’s existing reflationary stance will be sufficient to stabilize economic activity if a trade deal with the US is indeed finalized in the near future. Chart I-9Key Defensive Sectors Are Still Outperforming, Supporting Our Neutral Tactical Stance Chart I-10Industrials Vs. Staples Anticipated That Easing Would Only Be Measured As a final point, BCA Research's China Investment Strategy service will aim to use our newly developed sector outperformance probability models to make more active equity sector recommendations in the future. These recommendations will not mechanically follow the models; rather, we plan to use the models as a stand in for what typically would be expected given the macro and financial market environment, and as a basis to investigate “abnormal” relative performance. We hope you will find these models to be a helpful quantification of the risk versus return prospects of allocating among China’s investable sectors. As always, we welcome any feedback that you may have about our approach.   Energy Chart II-1 Table II-1   Unsurprisingly, our energy sector model highlights that periods of energy outperformance are strongly linked to periods of rising crude oil prices. However, what is surprising is that periods of accelerating headline inflation in China are even more closely linked to periods of energy sector outperformance than episodes of rising oil prices, and that these periods of accelerating inflation are not generally caused by rising energy prices. The lack of a clear economic rationale for this relationship implies that some investors (incorrectly) view energy stocks as a hedge against increases in consumer prices, even if those increases are largely driven by rising food prices. The model also highlights that periods of strong undervaluation have historically been significant in predicting future energy sector outperformance, with a lag of roughly 8 months. The probability of energy sector outperformance has fallen sharply according to our model, but for now we continue to recommend a long absolute energy sector position on a 6-12 month time horizon. BCA’s Commodity & Energy Strategy service expects oil prices to trade at $70/barrel on average next year,5 Chinese headline inflation continues to rise, and we noted in our October 2 Weekly Report that energy stocks are heavily discounted.6 Barring a durable decline in oil prices below $55/barrel, investors should continue to favor China’s energy sector. Materials Chart II-2 Table II-2 Our model highlights that the materials sector is one of the clearest plays on accelerating industrial activity within the investable universe. Among the macro variables that we tested, periods of investable materials outperformance are strongly positively linked with periods when our BCA Activity Index and our leading indicator for the index have been rising. Periods of materials sector outperformance have also been positively correlated with prior periods of oversold technical conditions and rising broad market stock prices, underscoring that materials are a strongly pro-cyclical sector. We currently maintain no active relative sector trades, but our model suggests that investors should be underweight the investable materials sector relative to the broad investable index. Industrials Chart II-3 Table II-3 Periods of industrial sector outperformance have historically been positively correlated with relative industrial sector earnings, broad market stock prices, and prior oversold technical conditions. They have been negatively correlated with periods of tight monetary policy, rising core inflation, and prior overbought technical conditions. Since 2010, periods of industrial sector performance have led periods of tight monetary policy by 8 months, the longest lead of relative equity performance to any macro variable that we tested in our model (and the longest lead that we allowed). Industrial sector performance has also been strongly negatively linked with periods of rising core inflation. These findings, and the fact that our Activity Index and its leading indicator have not been highly successful at predicting periods of industrial sector outperformance, strongly suggest that industrials, while pro-cyclical, are primarily driven by expectations of easy monetary policy. We noted in an August 2018 Special Report that state-owned enterprises have become substantially leveraged over the past decade,7 and in a more recent report we highlighted that industries such as machinery have experienced a significant deterioration in corporate health over the past decade.8 This helps explain why industrial sector performance is so negatively impacted by tight policy. Our model suggests that the best time to be overweight industrial stocks is the early phase of an economic rebound, when Chinese stock prices are rising but market participants are not yet expecting tighter policy. These conditions may present themselves sometime in Q1, but probably not over the coming 0-3 months. Consumer Discretionary Ex-Internet & Direct Marketing Retail Chart II-4 Table II-4 Besides materials, China’s investable consumer discretionary sector has historically been the most positively associated with coincident and leading measures of industrial activity. Rising core inflation is also highly positively related to consumer discretionary outperformance, which may reflect improved pricing power for the sector. The strong link with industrial activity is in contrast to depictions of China’s consumer sector as being less correlated to money & credit trends than the overall economy, and is supportive of our view that industrial activity forms one of the three pillars of China’s business cycle.9 We ended the estimation period of our model as of December 2018, in order to avoid including the distortive effects of last year’s changes to the global industry classification standard (which resulted in Alibaba’s inclusion and overwhelming representation in the investable consumer discretionary sector). As such, the results of our model apply today to consumer discretionary stocks ex-internet & direct marketing retail. For now, the absence of an uptrend in our Activity Index and in core inflation is signaling underperformance of discretionary stocks outside of internet & direct marketing retail. Outperformance this year largely reflects a significant advance in consumer durable and apparel: by contrast, automobiles & components have underperformed the broad market by roughly 14% year-to-date. Consumer Staples Chart II-5 Table II-5 Historically, periods of consumer staples outperformance have been predicted by a falling Activity Index, periods of tight monetary policy, and over/undervalued conditions. The impact of monetary policy is particularly heavy in the model, suggesting that consumer staples are somewhat the mirror image of industrials in terms of the impact of leverage on relative equity performance. This too is supported by our August 28 Special Report,10 which noted that corporate health for the food & beverage sector was the strongest among the sectors we examined. However, the model failed to capture what has been very significant staples outperformance this year, highlighting the occasional limits of a rule-of-thumb approach to sector allocation. Investable consumer staples are reliably low-beta compared with the broad market, and we are not surprised that investors have strongly favored the sector this year amid enormous economic and policy uncertainty. An eventual improvement in economic activity, coupled with fairly rich valuation, should work against consumer staples stocks sometime in the first quarter of 2020. Investors who are positioned in favor of China-related assets should also be watching closely for any signs of a technical breakdown in the relative performance trend of investable staples. Health Care Chart II-6 Table II-6 Among the macro variables tested in our model, periods of health care outperformance are negatively related to coincident and leading measures of industrial activity and strongly negatively related to rising core inflation.  Health care outperformance is also strongly negatively related to periods of rising broad market stock prices, and positively related to prior oversold technical conditions. These results clearly signify that investable health care is a defensive sector, to be owned when the economy is slowing and when investable stocks in general are trending lower. Our model suggests that health care stocks are likely to continue to outperform, as they have been since the beginning of the year. A substantive US/China trade deal that meaningfully reduces economic uncertainty remains the key risk to health care outperformance over a 6- to 12-month time horizon. Financials Chart II-7 Table II-7 Our model highlights that periods of financial sector outperformance over the past decade have been negatively associated with periods of rising core inflation (a strong relationship), and with periods of rising index earnings. Oversold technical conditions have also helped explain future episodes of financial sector outperformance. The link between core inflation and the outperformance of financials appears to represent a behavioral rather than a fundamental relationship. When modeling periods of rising financial sector relative earnings, the trend in broad market EPS is more predictive than that of core inflation, highlighting that the latter’s explanatory power is due to investor behavior. The results of our model, and the fact that core inflation leads Chinese index earnings, suggests that financials are fundamentally counter-cyclical and that investors see rising Chinese core inflation as confirmation that an economic expansion is underway (and that broad market earnings are likely to rise). Our model is currently predicting financial sector outperformance, but investable financials have modestly underperformed since the beginning of the year. This appears to have been caused by the underperformance of financial sector earnings this year as overall index earnings growth has decelerated, contrary to what history would suggest. We suspect that the ongoing shadow banking crackdown is related to financial sector earnings underperformance, and we would advise against an overweight stance towards investable financials until signs of improving relative earnings emerge. Banks Chart II-8 Table II-8 Our model shows that periods of banking sector outperformance are more linked to macro variables than has been the case for the overall financial sector. Specifically, bank performance is negatively correlated with leading indicators of economic activity and rising core inflation, and especially negatively correlated with periods of tight monetary policy. Banks have also typically outperformed following periods of oversold technical conditions. Similar to financials, bank earnings are typically counter-cyclical, but relative bank earnings have not been good predictors of relative bank performance over the past decade. Still, the negative association of relative stock prices with leading economic indicators, rising core inflation and rising interest rates underscores that investors should normally be underweight banks if they expect overall Chinese stock prices to rise. Also similar to the overall financial sector, our model is currently predicting outperformance for bank stocks, but investable banks have underperformed year-to-date. The shadow banking crackdown is also likely impacting investable bank earnings, leading to a similar recommendation to avoid bank stocks until relative earnings look to be trending higher. “Tech+”   Chart II-9 Table II-9 Our technology model has worked well at predicting periods of tech sector outperformance over the past several years, particularly from 2015 – 2017. The model suggests that, in addition to being negatively related to prior overbought conditions, periods of technology sector outperformance are associated with improving growth conditions, easy monetary policy, and rising prices. In other words, tech stocks are a growth & liquidity play. Owing to last year’s changes to the GICS, the results of our model apply today to Chinese investable internet & direct marketing retail, the media & entertainment industry group (within the new communication services sector), and the now considerably smaller information technology sector (the sum of which could be considered the “tech+” sector). The model has been predicting tech sector outperformance since May (in response to easier monetary policy), which has occurred for the official information technology sector. However, the BAT (Baidu, Alibaba, and Tencent) stocks are only up fractionally in relative terms from their late-May low. Our expectation that China’s economy is likely to bottom in Q1 means that we may recommend upgrading “tech+” stocks relative to the investable benchmark in the coming months. Telecom Services Chart II-10 Table II-10 Our model for telecommunication services (now a level 2 industry group within the communication services sector) illustrates that telecom stocks have historically been counter-cyclical. Periods of telecom outperformance have been negatively associated with periods of rising core inflation, rising broad market stock prices, and rising broad market EPS. It is notable that telecom services stocks are driven more by cycles in overall stock prices than by cycles in economic activity. This suggests that investors tend to focus on the fact that telecom stocks are reliably low-beta compared with the overall investable market, causing out(under)performance of telecoms when the broad market is falling(rising). Similar to financials & banks, telecom stocks have not outperformed this year, in contrast to what our model would suggest. Earnings also appear to be the culprit, with the level of 12-month trailing earnings having fallen nearly 10% since the summer. China Mobile accounts for a sizeable portion of the telecom services index, and the company’s recent earnings weakness seems to be due to depreciation charges stemming from forced investment on 5G spending (mandated by the Chinese government). Our sense is that this will have only a temporary effect on telecom services EPS, meaning that investors should continue to expect the sector to behave in a counter-cyclical fashion over the coming year. Utilities Chart II-11 Table II-11 The early performance of our utilities model was mixed, as it generated several false sell signals during the 2011 – 2013 period despite recommending, on average, an overweight stance. However, over the past five years, the model has performed extremely well in terms of explaining periods of relative utilities performance. The model highlights that utilities are straightforwardly counter-cyclical. The relative performance of utilities stocks is positively related to its relative earnings trend, and negatively related to economic activity, rising core inflation, and broad market stock prices.  Consistent with a decline in the overall MSCI China index, the model has correctly predicted utilities outperformance this year. We expect utilities to underperform over a 6-12 month time horizon, but would advise against an aggressive underweight position until hard evidence of a bottom in Chinese economic activity emerges. Real Estate Chart II-12 Table II-12 Our model for the relative performance of investable real estate has been among the most successful of those detailed in this report, which is somewhat surprising given the macro factors that the model shows drive real estate performance. While periods of relative real estate performance are modestly (negatively) associated with periods of tight monetary policy, rising headline inflation is the most important macro predictor of real estate underperformance. Among market factors driving performance, real estate stocks reliably underperform when broad market EPS are trending higher, and they historically outperform for a time after becoming relatively undervalued. Real estate relative performance is also strongly linked to periods of rising house prices, but the former tends to significantly lead the latter. Given that core inflation has better predicted episodes of tight monetary policy than headline inflation, investor expectations of eroding real disposable income is likely the best explanation for the negative link between real estate relative performance and rising headline inflation. Whereas rising core inflation likely reflects a durable improvement in economic momentum (and thus would be positively correlated with income growth), episodes of rising Chinese headline inflation often reflect supply shocks that investors may perceive to be detrimental to household spending power (and thus expected housing demand). Beyond the negative link between higher inflation and interest rates on investable real estate performance, the strong negative association with broad market earnings underscores that investors treat real estate as a defensive sector. We thus expect real estate stocks to continue to outperform in the near term, but underperform over a 6-12 month time horizon.   Jonathan LaBerge, CFA Vice President jonathanl@bcaresearch.com   Footnotes 1. Please see China Investment Strategy, "Six Questions About Chinese Stocks," dated January 16, 2019. 2. Please see Federal Reserve Bank of New York, The Yield Curve as a Leading Indicator at https://www.newyorkfed.org/research/capital_markets/ycfaq.html 3. This is despite frequent concerns among investors that the PBOC is inclined to tighten in response to detrimental supply shocks. 4. Please see China Investment Strategy, "Messages From BCA’s China Industry Watch," dated August 28, 2019. 5. Please see Commodity & Energy Strategy, "Policy Uncertainty Lifts USD, Stifles Global Oil Demand Growth," dated October 17, 2019. 6. Please see China Investment Strategy, "China Macro & Market Review," dated October 2, 2019. 7. Please see China Investment Strategy, "Chinese Policymakers: Facing A Trade-Off Between Growth And Leveraging," dated August 29, 2018. 8. Please see China Investment Strategy, "Messages From BCA’s China Industry Watch," dated August 28, 2019. 9. Please see China Investment Strategy, "The Three Pillars Of China’s Economy," dated May 16, 2018. 10. Please see China Investment Strategy, "Messages From BCA’s China Industry Watch," dated August 28, 2019. Cyclical Investment Stance Equity Sector Recommendations

Overweight Managed health care stocks cheered UnitedHealth Group’s better than expected earnings and higher guidance. The news is offsetting recent HMO uncertainty courtesy of Elizabeth Warren’s slingshot rise in the polls to win the Democratic Presidential nomination (middle panel).  Worryingly for HMOs, Warren is also closing in on Trump for the 2020 Presidential Election (bottom panel). Warren is advocating the creation of government-owned pharmaceutical manufacturers, elimination of private health insurance, and price controls on pharmaceuticals. All of her initiatives are a clear negative for the health care stocks in general and HMOs in particular. While the Warren threat is far from negligible, our sister Geopolitical Strategy service still believes that Trump has the upper hand in winning re-election especially if the economy avoids recession. Bottom Line: Stay overweight the S&P managed health care index, despite heightened Presidential Election uncertainty. The ticker symbols for the stocks in the index are: BLBG: S5MANH – UNH, ANTM, HUM, CNC, WCG.

Highlights New structural recommendation: long GBP/USD. The substantial Brexit discount in the pound makes it a long-term buy for investors who can tolerate near-term volatility. The most powerful equity play on a fading Brexit discount would be the U.K. homebuilders. Specifically, Persimmon still has a further 25 percent of upside. Take profits in long Euro Stoxx 50 versus Shanghai Composite. Within Europe, close the overweight to Switzerland and the underweight to the Netherlands. Stay overweight banks versus industrials. Stay overweight the Euro Stoxx 50 versus the Nikkei 225. Fractal trade: long NZD/JPY. Feature Chart of the WeekThe Pound Has Substantial Upside If The Brexit Discount Fades Carnival Says The Pound Is Cheap Carnival, the world’s largest cruise liner company, lists its shares on both the London and New York stock exchanges. But there is an apparent riddle: in London the shares trade on a forward PE of 8.8, while in New York they trade on 9.4. How can Carnival trade at different valuations on the two sides of the Atlantic when the market should instantly arbitrage the difference away? The answer to the riddle is that the London listing is quoted in pounds, the New York listing is quoted in dollars, while Carnival’s sales and profits are denominated in a mix of international currencies. Neither Brexit developments nor a potential Jeremy Corbyn led government will prevent the pound from rallying in the longer term.  Carnival is trading on a higher valuation in New York versus London because the market is expecting its mixed currency earnings to appreciate more in dollar terms than in pound terms. Put another way, the valuation differential is expecting the pound to appreciate versus the dollar to a ‘fair value’ of around $1.40 (Chart I-2). Likewise, BHP Billiton shares are trading on a higher valuation in their Sydney listing compared to their London listing. This valuation differential is expecting the pound to appreciate versus the Australian dollar to around A$2.00 (Chart I-3). Chart I-2Carnival Says The Pound Is Cheap Chart I-3BHP Billiton Says The Pound Is Cheap In other words, the market believes that neither Brexit developments nor a potential Jeremy Corbyn led government will prevent the pound from rallying in the longer term. We tend to agree. The Wrong Way To Pick Stock Markets… And The Right Way Before continuing with the pound’s prospects, let’s wander into the wider investment landscape. One important lesson from dual-listed companies like Carnival and BHP Billiton is that a multinational’s valuation will appear attractive in a market where the currency is structurally cheap.1 This lesson has deep ramifications. Today, multinationals dominate all the major stock markets, meaning that the entire stock market will appear cheap if its currency is cheap. The stock market will also appear cheap if it is skewed towards lower-valued sectors. But sectors trade on a low valuation for a reason – poor long-term growth prospects. Through the past decade, Japanese banks seemed a relative bargain, trading on a forward PE of less than half of that on personal products companies (Chart I-4). Yet Japanese banks were not a relative bargain. Quite the contrary. Through the past decade Japanese personal products have outperformed the banks by 500 percent! (Chart I-5) Chart I-4Japanese Banks Seemed A Relative Bargain... Chart I-5...But Japanese Banks Were Not A Relative Bargain Hence, beware of picking stock markets on the basis of observations such as ‘European stocks are cheaper than U.S. stocks’. Given that a stock market valuation is the result of its currency valuation and its sector composition, assessing relative value across major stock markets is extremely difficult, if not impossible. To repeat, Carnival appears to be trading at a valuation discount in London versus New York, but the cheapness is illusory. Here’s the right way to pick major stock markets. Identify your preferred sectors and currencies, and then pick the regional and country stock markets that are skewed to these preferred sectors and currencies. In this regard, large underweight sector skews also matter. For example, China and EM have a near-zero exposure to healthcare equities, so their performances tend to correlate negatively with that of the global healthcare sector – albeit the causality could run in either direction. Identify your preferred sectors and currencies, and then pick the regional and country stock markets that are skewed to these preferred sectors and currencies. In early May, we noticed that the extreme outperformance of technology versus healthcare was at a critical technical point at which there was a high probability of a trend reversal. This high conviction sector view implied overweight Europe versus China, as well as overweight Switzerland and underweight Netherlands within Europe (Chart I-6 and Chart I-7). Chart I-6When Tech Underperforms Healthcare, China Underperforms Switzerland Chart I-7When Tech Underperforms Healthcare, The Netherlands Underperforms Switzerland   Given that this sector trend reversal has played out exactly as anticipated, it is time to bank the profits:   Close long Euro Stoxx 50 versus Shanghai Composite. And within Europe, close the overweight to Switzerland and the underweight to the Netherlands. Right now, it is appropriate to overweight banks versus industrials. It is the pace of the bond yield’s decline that has weighed on bank performance this year. But if the sharpest decline in bond yields is behind us, as seems likely, then banks should fare better versus other cyclicals (Chart I-8). Chart I-8If The Sharpest Decline In Bond Yields Is Over, Banks Will Outperform Industrials Once again, this sector view carries an equity market implication: stay overweight the Euro Stoxx 50 versus the Nikkei 225 (Chart I-9). Chart I-9Euro Stoxx 50 Vs. Nikkei 225 = Global Banks In Euros Vs. Global Industrials In Yen The Pound Is A Long-Term Buy Back to the pound. The message from the dual listings of Carnival and BHP Billiton is that the pound is cheap, and this is neatly corroborated by the relationship between relative interest rates and the pound versus the euro and dollar. Based on the pre-Brexit relationship between relative real interest rates and the pound’s exchange rate, we can quantify the ‘Brexit discount’. Absent this discount, the pound would now be trading close to €1.30 and well north of $1.40 (Chart of the Week and Chart I-10). Chart I-10The Pound Has Substantial Upside If The Brexit Discount Fades In the Brexit psychodrama, we do not claim to know exactly how the next few days or weeks will play out. In the short term, Brexit is a classic non-linear system, and non-linear systems are inherently unpredictable. However, in the longer term we expect the Brexit discount to fade in any sort of transitioned resolution that allows the U.K. to adapt to a new trading relationship with the world, or alternatively to stay in a relationship broadly similar to the current one. Whatever the eventual endpoint is, the key requirement to remove the Brexit discount is to avoid a cliff-edge. We expect the Brexit discount to fade in any sort of transitioned resolution. The stumbling block to a resolution is that the three key actors – the EU, the U.K. government, and the U.K. parliament – have conflicting red lines, so the Brexit ‘Venn diagram’ has had no overlap. The EU will not countenance a customs border that divides Ireland; the current U.K. government wants a Free Trade Agreement, which implies casting away Northern Ireland into the EU customs union; and the current U.K. parliament – unless its intentions suddenly change – wants the whole of the U.K., including Northern Ireland, to remain in the EU customs union.   Given that the EU will not budge its red line, the only way to a lasting resolution is for the government and parliament red lines to realign, This could happen via parliament being willing to sacrifice Northern Ireland, via a second referendum, or via a general election in which the government’s intentions and/or the composition of parliament changed. Given a long enough investment horizon – 2 years or more – it is likely that the government and parliament will realign their red lines to a Free Trade Agreement or to a customs union, one way or another. On this basis, the substantial Brexit discount in the pound makes it a long-term buy for investors who can tolerate near-term volatility. Accordingly, today we are initiating a new structural recommendation: long GBP/USD.  For equity investors, the most powerful play on a fading Brexit discount would be the U.K. homebuilders (Chart I-11). Specifically, if the pound reached $1.40, Persimmon still has a further 25 percent of upside. Chart I-11U.K. Homebuilders Have Substantial Upside If The Brexit Discount Fades Fractal Trading System*  Based on its collapsed fractal structure, we anticipate a countertrend rally in NZD/JPY within the next 130 days. Accordingly, go long NZD/JPY setting a profit target of 3 percent and a symmetrical stop-loss. Chart I-12 For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment’s fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions.   * For more details please see the European Investment Strategy Special Report “Fractals, Liquidity & A Trading Model,” dated December 11, 2014, available at eis.bcaresearch.com. Dhaval Joshi, Chief European Investment Strategist dhaval@bcaresearch.com Footnotes 1 There are also several companies with dual listings in the U.K. and the euro area. Unfortunately, these valuation differentials have been temporarily distorted by the risk of a no-deal Brexit, in which EU27 investors may have been forbidden from trading in the U.K. listed shares. Fractal Trading System Cyclical Recommendations Structural Recommendations Fractal Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields   Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch - Interest Rate Expectations  

Special Report

In late-summer 2010, we published a Special Report overviewing long-term U.S. equity sector relative performance during deflationary periods. Since then, inflation – core PCE deflator to be more specific – only briefly flirted with the Federal Reserve’s 2% target in mid-2018, while long-term inflation expectations never managed to re-anchor higher. Worrisomely, there are now budding signs that inflation will weaken in the coming quarters rather than rear its ugly head. Pundits – us included – are still waiting for inflationary pressures to finally pass-through. Worrisomely, there are now budding signs that inflation will weaken in the coming quarters rather than rear its ugly head (Chart 1). The late-2018 tightening in financial conditions will exert downward pressure on year-over-year CPI growth, albeit with a slight lag (top panel, Chart 1). More broadly, the ongoing deceleration in the U.S. economy, as evidenced by the sharp decline in the ISM manufacturing PMI (and most of its subcomponents), represents a serious headwind for inflation (second panel, Chart 1). Given weak global growth, the appreciating U.S. dollar – a countercyclical currency – will also weigh on inflation going forward (not shown). Further, we don’t view the recent perky inflation prints as sustainable. In fact, core goods CPI – which accounts for 25% of core CPI and has been the main driver lately – is expected to roll over and contract over the next 18 months (third panel, Chart 1). Chart 1Still Looking For Inflation? U.S. Equity Strategy’s corporate pricing power proxy has also sharply sunk corroborating that the path of least resistance is lower for core inflation (bottom panel, Chart 1). In other words, if Marty McFly could ride the DeLorean to travel back in time once more, he would certainly approve of deflation/disinflation being a major equity theme at BCA, and would even ask us to delve deeper into our prior analysis. That is precisely what we do in this Special Report. We acknowledge the current disinflationary trend and provide more details on the historical relative performance of the different equity sectors in such periods. We introduce a simple trading rule based on these deflationary episodes, which we define as two or more consecutive quarters of negative corporate sector price deflator growth (Chart 2). We treat single quarters of positive growth within broader deflationary trends as outliers, which translate into the occasional quarterly rebounds within the shaded areas. Chart 2Deflationary Periods The next pages provide some more color on the sectors historical relative performance. Notably, we add a brief overview of the annualized returns realized by heeding the signals from two consecutive quarters of negative corporate sector price deflator growth. Since 1960, there have been 27 such signals, with a median duration of 15 months and the shortest one being six months. As such, we feel comfortable using 6-, 12- and 24-month horizons to go long (short) the sectors we identified did well during deflationary (inflationary) periods, whenever signaled. Table 1 summarizes the results of this empirical exercise. Table 1 Sector Relative Performance And Deflation (From 1960 To Present) Our hypothesis during disinflationary periods is that defensives outshine cyclicals. The results for the GICS11 relative sector performance are consistent with our hypothesis. Specifically, following our deflationary signal, defensives are up 1.4% on a 6-month horizon, while cyclicals are down 2.5%. We also note an inflection point around the 12-month mark as cyclicals start to recover their losses moving from -2.5% to just -0.21%, while defensives are giving up their gains moving from 1.38% to 0.76%. This finding is consistent with the median deflation period duration of 15 months, as highlighted earlier. Similarly, if we look 24 months out, we observe that cyclicals are outperforming the market by 0.5% (largely driven by tech), and defensives are lagging the market by -1.2% (dragged by telecom and utilities) signaling that the market has recovered. Diagram 1Performance Time Line Importantly, we are currently in a deflationary environment as defined by our two-quarter signal that commenced mid-2018, and U.S. Equity Strategy has been actively reducing cyclical exposure over the past six months and highlighting that investors should be cautious on the prospects of the broad equity market. Turning back to Table 1, we also see some divergences in the GICS1 sector performance vs. some of our expectations. Utilities should outperform during disinflation periods, owing to two factors: (1) steady cash flow growth, (2) falling interest rates boost the allure of high yielding competing assets. Another notable outlier is the S&P consumer discretionary index. Specifically, the roughly 2% underperformance in the six months following our deflationary signal took us by surprise, as discretionary spending should at the margin get a boost from declining interest rates. To conclude, we also present a time line that summarizes results from Table 1 as well as the sector specific comments. Importantly, the time line is a road map that should be only used “as a rule of thumb” guide to navigate a deflationary environment. Keep in mind, that even though the median duration for a deflationary period is 15 months, it can still last anywhere from just under a year to over four years. As always, context is key. Finally, stay tuned for an update on our traditional U.S. equity sector profit margin outlook report that is due in the upcoming months. What follows are additional details of our analysis on a per sector basis, along with charts on sector specific pricing power and revenue turnover.     Jeremie Peloso, Research Analyst JeremieP@bcaresearch.com   Arseniy Urazov, Research Associate ArseniyU@bcaresearch.com   Consumer Staples (Overweight) The S&P consumer staples index performs well during deflationary periods. Likely explanatory variables are the safe haven status of this index along with an ongoing industry consolidation. Our sector pricing power proxy reveals that staples have not experienced a contraction in pricing power since 2003. While relative share prices are staging a recovery, they are still one standard deviation below the historical time trend. Further gains are likely given impressive returns on a 6-, 12-, and 24-month time horizon following our deflationary signal. We remain overweight the S&P consumer staples index. Energy (Overweight) Among the cyclical sectors, S&P energy is the second largest underperformer, declining 3.4% on average in relative terms in the six months following our deflationary signal. The underperformance is also evident in our PP proxy. Energy companies’ PP declines right as the economy enters deflation, which is consistent with our expectations, as oil plays a key role in virtually any inflation/deflation measure. One caveat at the current juncture is the recent oil price spike that may serve as a catalyst to unlock excellent value in bombed out energy equities. As a result of the drone attacks on Saudi Arabia’s production and refining facilities we expect geopolitical premia to get built into crude oil prices on a sustained basis. We are currently overweight the S&P energy index. Health Care (Overweight) During deflationary periods the S&P health care sector has outperformed the broad market, similar to its defensive sibling, the S&P consumer staples sector. On top of the safe haven nature of the health care industry, pricing power has never crossed below the zero line during the entire history of the data series. This remarkable feat also applies to the sector’s sales growth. We are currently overweight the S&P health care index. Industrials (Overweight) On the eve of deflation, industrials equities start wrestling with two opposing forces: cheapened raw materials versus slowing economic activity. In the end, economic softness wins the tug-of-war as this deep cyclical index underperforms the market on 6-, 12- and 24-month time horizon by -1.4%, -1.0% and -0.5%, respectively. The sector’s pricing power usually displays a sharp decline as we enter a deflationary zone weighing on industrials revenue prospects and thus relative performance. We are currently overweight the S&P industrials sector. Financials (Overweight) Being an early cyclical sector, it is not surprising that the S&P financials sector tends to underperform the broad market on 6-, 12- and 24-month horizon following our two-quarter deflation signal. The largest underperformance for financials comes late into the deflationary period. In fact, had we excluded utilities from our analysis, the S&P financials sector would have been the worst performing sector across the board on a 12- and 24-month time horizon. The heavyweight banks subgroup accounting for roughly 42% of the S&P financials market capitalization weight explains the underperformance. As a reminder banks underperform when the price of credit is falling owing to deflation/disinflation. Given that our fixed income strategists expect a selloff in the bond market, we remain overweight the S&P financials index. Technology (Neutral – Downgrade Alert) Back in 2010, we reiterated that tech equities were deflationary winners, a fact that has not changed since then. The frenetic pace of innovation in and of itself, has prepared the sector to cope with episodes of deflation. Within cyclicals, technology is by far the best performing sector in our Table 1, but the present-day geopolitical and trade tensions compel us to be neutral on the sector with a potential downgrade coming down the line via a software subgroup downgrade. Tech pricing power is resilient during deflationary episodes. However, tech sales growth, which appears to have peaked for the cycle, swings violently, warning of potential turbulence ahead if a down oscillation is looming. We are neutral the S&P technology sector, which is also on our downgrade watch list. Telecommunication Services (Neutral) Traditionally defensive telecom services stocks have been struggling recently, saddled with rising debt, fighting to remain relevant and avoid becoming a “dumb pipe”. The industry’s pricing power proxy also highlights the point as telecom companies never managed to regain their footing since the GFC. Another important point is that the index materially underperforms the market across all the time horizons we examined returning: -1.5%, -2.0% and -4.4%. Our hypothesis was that telecom carriers should outperform during deflationary periods owing to stable cash flow growth generation and a high dividend yield profile. But, empirical evidence shows the opposite. Likely, the four decades-long sustained underperformance of this now niche safe haven industry suggests that sector specific dynamics are at fault. We are currently neutral the S&P telecommunication services index. Materials (Underweight) Despite the massive demand from China and, more generally, from the EM complex for commodities over the past several years, the S&P materials sector never actually managed to break free from its structural downtrend. The sector is one of the major disinflationary losers as evident from the chart. Importantly, since the mid-70s, most of the periods when materials managed to outperform the broad market occurred outside the shaded areas and recessions. On average, materials sector pricing power also tends to decline sharply when global growth weakens, as is currently the case. And, with a slight delay, materials sector revenue growth will likely suffer a setback, warning that revenue growth has crested for the cycle. We reiterate our recent downgrade of the S&P materials sector to underweight. Consumer Discretionary (Underweight – Upgrade Alert) Contrary to our hypothesis, S&P consumer discretionary stocks underperform during disinflationary periods that weigh on interest rates. Likely decelerating economic activity trumps that fall in interest rates and consumers gravitate toward staple goods and services and away from discretionarfy purchases. Table 1 reveals that consumer discretionary stocks actually suffer the most early in a deflationary period (-2.0%), and then sharply recover 12 months out and turn marginally positive (0.1%). We are currently underweight the S&P consumer discretionary index, but have it on upgrade alert as a potential buying opportunity. Utilities (Underweight) As for the final sector of this Special Report, we had highlighted that the S&P utilities is a notable outlier in our analysis as it does not behave according to our expectations. Likely, some industry specific dynamics are at play as high-yielding safe haven utilities stocks severely underperform during deflationary periods. The sector returns -3.5%, -4.3%, and -4.5% versus the broad marekt on a 6-, 12, and 24-month time horizon, respectively. In theory, two factors should have pushed the relative share price higher: (1) steady cash flow growth and (2) falling interest rates, both of which boost the allure of high yielding competing assets. Neither one was sufficient to break away from the structural downtrend that has been haunting the sector over the years. We are currently underweight the S&P utilites index.   Footnotes 1    We are using GICS 2 Telecommunication Services index instead of the parent GICS 1 Communication Services index due to the lack of data as the index was only recently introduced.

Overweight While the latest ISM manufacturing survey made for grim reading, there is a corner of the manufacturing landscape that excels when overall manufacturing is in retreat: health care equipment (HCE) makers (second panel, ISM shown inverted). This defensive health care sub-group is firing on all cylinders. Not only is medical equipment industrial production going against the grain and climbing at a healthy clip, but also the industry’s new orders-to-inventories ratio is in its third consecutive year of a sling shot recovery. Moreover, HCE pricing power is expanding smartly at a time when our overall corporate pricing power proxy is contracting. All of this suggests that the earnings-driven vault to all-time relative performance highs has staying power. Bottom Line: We reiterate our recent boost to an overweight stance in the S&P health care equipment index. The ticker symbols for the stocks in the index are: BLBG: S5HCEP – ABT, MDT, DHR, BDX, SYK, ISRG, BSX, BAX, EW, ZBH, IDXX, RMD, TFX, HOLX, ABMD, VAR.

Highlights Portfolio Strategy Despite the Fed’s supra natural powers, the deep rooted global growth slowdown will likely win the tug of war versus flush liquidity, especially if the trade war spat stays unresolved and the U.S. dollar remains well bid, both of which undermine U.S. corporate sector profitability. Recent Changes There are no changes to the portfolio this week. Table 1 Feature Equities hit all-time highs last week, eagerly anticipating this Wednesday’s Fed decision to commence an easing interest rate cycle and save the day. The looming global liquidity injection is the sole reason that stocks are holding near their all-time highs. While markets are treating the Fed as a deity, empirical evidence suggests that risks are actually lurking beneath the surface. Over the past two decades the correlation between stocks and the fed funds rate has been tight and positive. Given the bond market’s view of four fed cuts in the coming year, equity gains are likely running on fumes (Chart 1). Chart 1Mind The Positive Correlation As we highlighted recently, we remain perplexed that stocks are diverging from earnings.1 Anticipating a flush global liquidity backdrop (i.e. global central banks increasing their reflationary efforts) likely explains this dynamic as the former should ultimately rekindle economic growth, which in turn should boost profit growth. However, the disinflationary fallout from the ongoing manufacturing recession and the petering out in the global credit impulse signal that the liquidity pipes remain clogged. We recently read and re-read the Bank For International Settlements (BIS) Hyun Song Shin’s “What is behind the recent slowdown” speech where he eloquently argues that the global trade deceleration predates last spring’s U.S./China trade dispute.2 Shin has a compelling argument blaming the growth deceleration on the drop in manufactured goods global value chains (GVC) and he depicts this as global trade trailing global GDP (top panel, Chart 2). Interestingly, despite the V-shaped recovery following the Great Recession, global trade never really regained its footing, failing to surpass the 2007 peak. Shin then links this slowdown in global supply chains to financial conditions and the role that banking plays in global trade financing. The middle panel of Chart 2 shows that the GVC move with the ebbs and flows of global banks. In other words, healthy banks tend to boost global trade and vice versa. Finally, given that most trade financing is conducted in U.S. dollars, the greenback’s recent appreciation also explains trade blues. Simply put, decreased availability of U.S. dollar denominated bank credit as a result of a rising greenback is another culprit (U.S. dollar shown inverted, bottom panel, Chart 2). Ergo, there is no miracle cure for the sputtering world economy, especially given the recent re-escalation in global trade tensions and the stubbornly high U.S. dollar, and the gap between buoyant share prices and poor profit performance is likely to narrow via a fall in the former. Two weeks ago we highlighted that foreign sourced profits for U.S. multinationals are under attack as BCA’s global ex-U.S. ZEW survey ticked down anew (top panel, Chart 3). Tack on the global race to ZIRP (and in some cases further into NIRP) and it is crystal clear that the profit recession has yet to run its course. Chart 2Grim Trade Backdrop... Chart 3...Will Continue To Weigh On Foreign Sourced Profits   Meanwhile, China is likely exporting its deflation to the rest of the world and until its business sector regains pricing power, U.S. profits will continue to suffer (bottom panel, Chart 3). Turning over to U.S. shores and domestic corporate pricing power, the news is equally grim. Our pricing power proxy is outright contracting and warns that revenue growth is also under duress for U.S. corporates. Similarly, the ISM manufacturing prices paid subcomponent fell below the 50 boom/bust line and steeply contracting raw industrials commodities are signaling that 6%/annum top line growth for the SPX is unsustainable (Chart 4). On a cyclical 3-12 month time horizon we remain cautious on the broad equity market. Chart 4Sales Pressures... Chart 5...Are Building Rapidly Melting inflation expectations and the NY Fed’s softening Underlying Inflation Gauge (UIG) best encapsulate this softening revenue backdrop and warn that any further letdown in inflation risks sinking S&P 500 sales growth below the zero line (Chart 5).   Netting it all out, despite the Fed’s supra natural powers, the deep rooted global growth slowdown will likely win the tug of war versus flush liquidity, especially if the trade war spat stays unresolved and the U.S. dollar remains well bid, both of which undermine U.S. corporate sector profitability. On a cyclical 3-12 month time horizon we remain cautious on the broad equity market. This is U.S. Equity Strategy’s view, which stands in contrast to the more sanguine equity BCA House View. What follows is a recap of recent (mostly) defensive moves in the health care, consumer staples, materials, tech, consumer discretionary and communication services sectors.   Anastasios Avgeriou, U.S. Equity Strategist anastasios@bcaresearch.com   S&P Health Care (Overweight) Upgraded from Neutral S&P Health Care Equipment (Overweight) Upgraded from Neutral Fear-based sell-off created a buying opportunity in the U.S. health care equipment index as fundamentals remain upbeat. Rising U.S. medical equipment exports are a tailwind for this health care subgroup as 60% of its revenues are generated outside the United States (second panel). The EM demographic shift (not shown) represents yet another boost to the sector as U.S. companies are the technology leaders and often the only source for equipping hospitals/clinics around the globe. Our move to upgrade the S&P health care equipment index also pushed the entire health care sector from neutral to overweight (bottom panel). S&P Health Care S&P Managed Health Care (Overweight) Upgraded from Neutral The Bernie Sanders “Medicare For All” bill reintroduction created a buying opportunity in the S&P managed health care index and we were swift to act on it in mid-April. Contained industry cost factors including wages staying at the 2% mark help preserve industry margins (bottom panel). Melting medical cost inflation signals that HMO profit margins will likely expand (third panel). Overall healthy labor market conditions with unemployment insurance claims probing 60-year lows should underpin managed health care enrollment (top & second panels). S&P Managed Health Care   S&P Hypermarkets (Overweight) Upgraded from Neutral S&P Soft Drinks (Neutral) Upgraded from Underweight A deteriorating macro landscape reflected in the steep fall in U.S. economic data surprises, the drubbing of the 10-year U.S. Treasury yield and melting inflation make a compelling case for an overweight stance in the S&P Hypermarkets index (top & second panels). Similarly, safe haven soft drinks stocks shine when economic conditions are deteriorating (third panel). This defensive pure-play consumer goods sub-sector is also enjoying a rebound in operating metrics, and thus it no longer pays to stay bearish. We lifted exposure to neutral last week, locking in gains of 5.5% since inception. S&P Hypermarkets   S&P Materials (Neutral) Downgraded from Overweight S&P Chemicals (Underweight) Downgraded from Neutral Global macro headwinds continue to weigh on this deep cyclical sub-index as the risks of a full-blown trade war will likely take a bite out of final demand (third panel). Chemical producers garner 60% of their revenues from abroad and falling U.S. chemical exports are troublesome for this index (top & second panels). Given that chemicals have a 74% market cap weight in the S&P materials index, our move to underweight on the sub-index level also pushed the entire S&P materials index to neutral from overweight. S&P Materials   S&P Technology (Neutral) Downgrade Alert S&P Software (Overweight) Lifted trailing stops As a part of our portfolio de-risking measures, we put a 27% profit-taking stop loss on our overweight S&P software index call on June 10. Once triggered, a downgrade to neutral in the S&P software index would also push our S&P tech sector weight to a below benchmark allocation. Meanwhile, our EPS model for the overall tech sector is on the verge of contraction on the back of sinking capex and a firming U.S. dollar (middle panel). The San Francisco Fed’s Tech Pulse Index is also closing in on the expansion/contraction line warning that tech stocks are in for a rough ride (bottom panel). S&P Technology   S&P Technology Hardware, Storage & Peripherals (Neutral) Downgraded from Overweight As nearly 60% of the revenues for the S&P technology hardware, storage & peripherals (THS&P) index are sourced from abroad, deflating EM currencies sap foreign consumer purchasing power and weigh on the industry’s exports (third panel). Global export volumes have sunk into contractionary territory, to a level last seen during the Great Recession (not shown) and underscore that industry exports will remain under pressure. The IFO World Economic Survey confirms this challenging export backdrop as it is still pointing toward sustained global export ails (second panel). As a result, all of this has shaken our confidence in an overweight stance in the S&P THS&P and we were compelled to move to the sidelines in early June for a modest relative loss since inception. S&P Technology Hardware, Storage & Peripherals S&P Consumer Discretionary (Underweight) Upgrade Alert S&P Home Improvement Retail (Neutral) Upgraded from underweight In the July 8 Weekly Report, we put the S&P consumer discretionary sector on an upgrade alert as this early-cyclical sector benefits the most from lower interest rates (bottom panel). The way we will execute this upgrade will be by triggering the upgrade alert on the S&P internet retail index. Melting interest rates and rebounding lumber prices are a boon for home improvement retailers (HIR, second & third panels). Tack on profit-augmenting industry productivity gains and it no longer pays to be bearish HIR. S&P Consumer Discretionary S&P Homebuilders (Neutral) Downgraded from overweight Long S&P Homebuilders / Short S&P Home Improvement Retail Booked Profits Lumber represents an input cost to homebuilders (we booked profits of 10% in our overweight recommendation on May 22 and downgraded to neutral) whereas it is an important selling item in Big Box building & supply retailers that make a set margin on it (third panel). On June 18, as part of our de-risking strategy, we locked in 10% gains in the long S&P homebuilders/short S&P home improvement retail trade that hit our stop loss and we moved to the sidelines. S&P Homebuilders S&P Telecommunication Services (Neutral) Upgraded from Underweight The recent escalation of the trade spat has pushed July’s Markit’s flash U.S. manufacturing PMI reading to 50 - the lowest level since the history of the data. Historically, relative S&P telecom services share price momentum has moved inversely with the manufacturing PMI and the current message is to expect a sustained rebound in the former (bottom panel). Rock bottom profit expectations and firming industry operating metrics signal that most of the grim news is priced in bombed out telecom services valuations (middle panel), and it no longer pays to be underweight. In late-May, we lifted exposure to neutral for 6% relative gains since inception. S&P Telecommunication Services S&P Movies & Entertainment (Overweight) Upgraded from Neutral Structural shifts in the streaming services industry marked a start of a pricing war with incumbents and new entrants fighting for market share, as evidenced by DIS’s pricing of their upcoming Disney+ service. Consumer confidence remains glued to multi-decade highs and there are high odds that the big gulf that has opened up between confidence and relative S&P movies & entertainment share prices will narrow via a rise in the latter (top panel). Moreover, more dollars spent on recreation is synonymous with a margin expansion in the S&P movies & entertainment index (bottom panel). This consumer spending backdrop is also conducive to a rise in relative profitability, the opposite of what the sell-side currently expects. S&P Movies & Entertainment   Arseniy Urazov, Research Associate ArseniyU@bcaresearch.com Footnotes 1      Please see BCA U.S. Equity Strategy Weekly Report, “Beware Profit Recession” dated July 8, 2019, available at uses.bcaresearch.com. 2      https://www.bis.org/speeches/sp190514.pdf   Current Recommendations Current Trades Size And Style Views Favor value over growth Favor large over small caps

Special Report

Productivity growth is experiencing a cyclical rebound, but remains structurally weak. The end of the deepening of globalization, statistical hurdles, and the possibility that today’s technological advances may not be as revolutionary as past ones all hamper productivity. On the back of rising market power and concentration, companies are increasing markups instead of production. This is depressing productivity and lowering the neutral rate of interest. For now, investors can generate alpha by focusing on consolidating industries. Growing market power cannot last forever and will meet a political wall. Structurally, this will hurt asset prices.   “We don’t have a free market; don’t kid yourself. (…) Businesspeople are enemies of free markets, not friends (…) businesspeople are all in favor of freedom for everybody else (…) but when it comes to their own business, they want to go to Washington to protect their businesses.” Milton Friedman, January 1991. Despite the explosion of applications of growing computing power, U.S. productivity growth has been lacking this cycle. This incapacity to do more with less has weighed on trend growth and on the neutral rate of interest, and has been a powerful force behind the low level of yields at home and abroad. In this report, we look at the different factors and theories advanced to explain the structural decline in productivity. Among them, a steady increase in corporate market power not only goes a long way in explaining the lack of productivity in the U.S., but also the high level of profit margins along with the depressed level of investment and real neutral rates. A Simple Cyclical Explanation The decline in productivity growth is both a structural and cyclical story. Historically, productivity growth has followed economic activity. When demand is strong, businesses can generate more revenue and therefore produce more. The historical correlation between U.S. nonfarm business productivity and the ISM manufacturing index illustrates this relationship (Chart II-1). Chart II-1The Cyclical Behavior Of Productivity Chart II-2Deleveraging Hurts Productivity Since 2008, as households worked off their previous over-indebtedness, the U.S. private sector has experienced its longest deleveraging period since the Great Depression. This frugality has depressed demand and contributed to lower growth this cycle. Since productivity is measured as output generated by unit of input, weak demand growth has depressed productivity statistics. On this dimension, the brief deleveraging experience of the early 1990s is instructive: productivity picked up only after 1993, once the private sector began to accumulate debt faster than the pace of GDP growth (Chart II-2). The recent pick-up in productivity reflects these debt dynamics. Since 2009, the U.S. non-financial private sector has stopped deleveraging, removing one anchor on demand, allowing productivity to blossom. Moreover, the pick-up in capex from 2017 to present is also helping productivity by raising the capital-to-workers ratio. While this is a positive development for the U.S. economy, the decline in productivity nonetheless seems structural, as the five-year moving average of labor productivity growth remains near its early 1980s nadir (Chart II-3). Something else is at play. The Usual Suspects Three major forces are often used to explain why observed productivity growth is currently in decline: A slowdown in global trade penetration, the fact that statisticians do not have a good grasp on productivity growth in a service-based economy, and innovation that simply isn’t what it used to be. Slowdown In Global Trade Penetration Two hundred years ago, David Ricardo argued that due to competitive advantages, countries should always engage in trade to increase their economic welfare. This insight has laid the foundation of the argument that exchanges between nations maximizes the utilization of resources domestically and around the world. The collapse in new business formation in the U.S. is another fascinating development. Rarely was this argument more relevant than over the past 40 years. On the heels of the supply-side revolution of the early 1980s and the fall of the Berlin Wall, globalization took off. The share of the world's population participating in the global capitalist system rose from 30% in 1985 to nearly 100% today. Generating elevated productivity gains is simpler when a country’s capital stock is underdeveloped: each unit of investment grows the capital-to-labor ratio by a greater proportion. As a result, productivity – which reflects the capital-to-worker ratio – can grow quickly. As more poor countries have joined the global economy and benefitted from FDI and other capital inflows, their productivity has flourished. Consequently, even if productivity growth has been poor in advanced economies over the past 10 years, global productivity has remained high and has tracked the share of exports in global GDP (Chart II-4). Chart II-4The Apex Of Globalization Represented The Summit Of Global Productivity Growth This globalization tailwind to global productivity growth is dissipating. First, following an investment boom where poor decisions were made, EM productivity growth has been declining. Second, with nearly 100% of the world’s labor supply already participating in the global economy, it is increasingly difficult to expand the share of global trade in global GDP and increase the benefit of cross-border specialization. Finally, the popular backlash in advanced economies against globalization could force global trade into reverse. As economic nationalism takes hold, cross-border investments could decline, moving the world economy further away from an optimal allocation of capital. These forces may explain why global productivity peaked earlier this decade. Productivity Is Mismeasured Recently deceased luminary Martin Feldstein argued that the structural decline in productivity is an illusion. As the argument goes, productivity is not weak; it is only underestimated. A parallel with the introduction of electricity in the late 19th century often comes to mind. Back then, U.S. statistical agencies found it difficult to disentangle price changes from quantity changes in the quickly growing revenues of electrical utilities. As a result, the Bureau Of Labor Statistics overestimated price changes in the early 20th century, which depressed the estimated output growth of utilities by a similar factor. Since productivity is measured as output per unit of labor, this also understated actual productivity growth – not just for utilities but for the economy as a whole. Ultimately, overall productivity growth was revised upward. Chart II-5Plenty Of Room To Mismeasure Real Output Growth In today’s economy, this could be a larger problem, as 70% of output is generated in the service sector. Estimating productivity growth is much harder in the service sector than in the manufacturing sector, as there is no actual countable output to measure. Thus, distinguishing price increases from quantity or quality improvements is challenging. Adding to this difficulty, the service sector is one of the main beneficiaries of the increase in computational power currently disrupting industries around the world. The growing share of components of the consumer price index subject to hedonic adjustments highlight this challenge (Chart II-5). Estimating quality changes is hard and may bias the increase in prices in the economy. If prices are unreliably measured, so will output and productivity. Pushing The Production Frontier Is Increasingly Hard Chart II-6A Multifaceted Decline In Productivity Another school of thought simply accepts that productivity growth has declined in a structural fashion. It is far from clear that the current technological revolution is much more productivity-enhancing than the introduction of electricity 140 years ago, the development of the internal combustion engine in the late 19th century, the adoption of indoor plumbing, or the discovery of penicillin in 1928. It is easy to overestimate the economic impact of new technologies. At first, like their predecessors, the microprocessor and the internet created entirely new industries. But this is not the case anymore. For all its virtues, e-commerce is only a new method of selling goods and services. Cloud computing is mainly a way to outsource hardware spending. Social media’s main economic value has been to gather more information on consumers, allowing sellers to reach potential buyers in a more targeted way. Without creating entirely new industries, spending on new technologies often ends up cannibalizing spending on older technologies. For example, while Google captures 32.4% of global ad revenues, similar revenues for the print industry have fallen by 70% since their apex in 2000. If new technologies are not as accretive to production as the introduction of previous ones were, productivity growth remains constrained by the same old economic forces of capex, human capital growth and resource utilization. And as Chart II-6 shows, labor input, the utilization of capital and multifactor productivity have all weakened. Some key drivers help understand why productivity growth has downshifted structurally. Let’s look at human capital. It is much easier to grow human capital when very few people have a high-school diploma: just make a larger share of your population finish high school, or even better, complete a university degree. But once the share of university-educated citizens has risen, building human capital further becomes increasingly difficult. Chart II-7 illustrates this problem. Growth in educational achievement has been slowing since 1995 in both advanced and developing economies. This means that the growth of human capital is slowing. This is without even wading into whether or not the quality of education has remained constant. This is pure market power, and it helps explain the gap between wages and productivity. Human capital is also negatively impacted by demographic trends. Workers in their forties tend to be at the peak of their careers, with the highest accumulated job know-how. Problematically, these workers represent a shrinking share of the labor force, which is hurting productivity trends (Chart II-8). Chart II-8Demographics Are Hurting Productivity   The capital stock too is experiencing its own headwinds. While Moore’s Law seems more or less intact, the decline in the cost of storing information is clearly decelerating (Chart II-9). Today, quality adjusted IT prices are contracting at a pace of 2.3% per annum, compared to annual declines of 14% at the turn of the millennium. Thus, even if nominal spending in IT investment had remained constant, real investment growth would have sharply decelerated (Chart II-10). But since nominal spending has decelerated greatly from its late 1990s pace, real investment in IT has fallen substantially. The growth of the capital stock is therefore lagging its previous pace, which is hurting productivity growth. Chart II-10The Impact Of Slowing IT Deflation Chart II-11A Dearth Of New Businesses   The collapse in new business formation in the U.S. is another fascinating development (Chart II-11). New businesses are a large source of productivity gains. Ultimately, 20% of productivity gains have come from small businesses becoming large ones. Think Apple in 1977 versus Apple today. A large decline in the pace of new business formation suggests that fewer seeds have been planted over the past 20 years to generate those enormous productivity explosions than was the case in the previous 50 years.   The X Factor: Growing Market Concentration The three aforementioned explanations for the decline in productivity are all appealing, but they generally leave investors looking for more. Why are companies investing less, especially when profit margins are near record highs? Why is inflation low? Why has the pace of new business formation collapsed? These are all somewhat paradoxical. Chart II-12Wide Profit Margins: A Testament To The Weakness Of Labor This is where a growing body of works comes in. Our economy is moving away from the Adam Smith idea of perfect competition. Industry concentration has progressively risen, and few companies dominate their line of business and control both their selling prices and input costs. They behave as monopolies and monopsonies, all at once.1 This helps explain why selling prices have been able to rise relative to unit labor costs, raising margins in the process (Chart II-12). Let’s start by looking at the concept of market concentration. According to Grullon, Larkin and Michaely, sales of the median publicly traded firms, expressed in constant dollars, have nearly tripled since the mid-1990s, while real GDP has only increased 70% (Chart II-13).2 The escalation in market concentration is also vividly demonstrated in Chart II-14. The top panel shows that since 1997, most U.S. industries have experienced sharp increases in their Herfindahl-Hirshman Index (HHI),3 a measure of concentration. In fact, more than half of U.S. industries have experienced concentration increases of more than 40%, and as a corollary, more than 75% of industries have seen the number of firms decline by more than 40%. The last panel of the chart also highlights that this increase in concentration has been top-heavy, with a third of industries seeing the market share of their four biggest players rise by more than 40%. Rising market concentration is therefore a broad phenomenon – not one unique to the tech sector.     This rising market concentration has also happened on the employment front. In 1995, less than 24% of U.S. private sector employees worked for firms with 10,000 or more employees, versus nearly 28% today. This does not seem particularly dramatic. However, at the local level, the number of regions where employment is concentrated with one or two large employers has risen. Azar, Marinescu and Steinbaum developed Map II-1, which shows that 75% of non-metropolitan areas now have high or extreme levels of employment concentration.4 Chart II-15The Owners Of Capital Are Keeping The Proceeds Of The Meagre Productivity Gains This growing market power of companies on employment can have a large impact on wages. Chart II-15 shows that real wages have lagged productivity since the turn of the millennium. Meanwhile, Chart II-16 plots real wages on the y-axis versus the HHI of applications (top panel) and vacancies (bottom panel). This chart shows that for any given industry, if applicants in a geographical area do not have many options where to apply – i.e. a few dominant employers provide most of the jobs in the region – real wages lag the national average. The more concentrated vacancies as well as applications are with one employer, the greater the discount to national wages in that industry.5 This is pure market power, and it helps explain the gap between wages and productivity as well as the widening gap between metropolitan and non-metropolitan household incomes. Growing market power and concentration do not only compress labor costs, they also result in higher prices for consumers. This seems paradoxical in a world of low inflation. But inflation could have been even lower if market concentration had remained at pre-2000s levels. In 2009, Matthew Weinberg showed that over the previous 22 years, horizontal mergers within an industry resulted in higher prices.6 In a 2014 meta-study conducted by Weinberg along with Orley Ashenfelter and Daniel Hosken, the authors showed that across 49 studies ranging across 21 industries, 36 showed that horizontal mergers resulted in higher prices for consumers.7 While today’s technology may be enhancing the productive potential of our economies, this is not benefiting output and measured productivity. Instead, it is boosting profit margins. In a low-inflation environment, the only way for companies to garner pricing power is to decrease competition, and M&As are the quickest way to achieve this goal. After examining nearly 50 merger and antitrust studies spanning more than 3,000 merger cases, John Kwoka found that, following mergers that augmented an industry’s concentration, prices increased in 95% of cases, and on average by 4.5%.8 In no industry is this effect more vividly demonstrated than in the healthcare field, an industry that has undergone a massive wave of consolidation – from hospitals, to pharmacies to drug manufacturers. As Chart II-17 illustrates, between 1980 and 2016, healthcare costs have increased at a much faster pace in the U.S. than in the rest of the world. However, life expectancy increased much less than in other advanced economies. In this context of growing market concentration, it is easy to see why, as De Loecker and Eeckhout have argued, markups have been rising steadily since the 1980s (Chart II-18, top panel) and have tracked M&A activity (Chart II-18, bottom panel).9 In essence, mergers and acquisitions have been the main tool used by firms to increase their concentration. Another tool at their disposal has been the increase in patents. The top panel of Chart II-19 shows that the total number of patent applications in the U.S. has increased by 3.6-fold since the 1980s, but most interestingly, the share of patents coming from large, dominant players within each industry has risen by 10% over the same timeframe (Chart II-19, bottom panel). To use Warren Buffet’s terminology, M&A and patents have been how firms build large “moats” to limit competition and protect their businesses. Chart II-18Markups Rise Along With Growing M&A Activity Chart II-19How To Build A Moat?   Why is this rise in market concentration affecting productivity? First, from an empirical perspective, rising markups and concentration tend to lead to lower levels of capex. A recent IMF study shows that the more concentrated industries become, the higher the corporate savings rate goes (Chart II-20, top panel).10 These elevated savings reflect wider markups, but also firms with markups in the top decile of the distribution display significantly lower investment rates (Chart II-20, bottom panel). If more of the U.S. output is generated by larger, more concentrated firms, this leads to a lower pace of increase in the capital stock, which hurts productivity. Second, downward pressure on real wages is also linked to a drag on productivity. Monopolies and oligopolies are not incentivized to maximize output. In fact, for any market, a monopoly should lead to lower production than perfect competition would. Diagram II-I from De Loecker and Eeckhout shows that moving from perfect competition to a monopoly results in a steeper labor demand curve as the monopolist produces less. As a result, real wages move downward and the labor participation force declines. Does this sound familiar?   The rise of market power might mean that in some way Martin Feldstein was right about productivity being mismeasured – just not the way he anticipated. In a June 2017 Bank Credit Analyst Special Report, Peter Berezin showed that labor-saving technologies like AI and robotics, which are increasingly being deployed today, could lead to lower wages (Chart II-21).11 For a given level of technology in the economy, productivity is positively linked to real wages but inversely linked to markups – especially if the technology is of the labor-saving kind. So, if markups rise on the back of firms’ growing market power, the ensuing labor savings will not be used to increase actual input. Rather, corporate savings will rise. Thus, while today’s technology may be enhancing the productive potential of our economies, this is not benefiting output and measured productivity. Instead, it is boosting profit margins.12 Unsurprisingly, return on assets and market concentration are positively correlated (Chart II-22).     Finally, market power and concentration weighing on capex, wages and productivity are fully consistent with higher returns of cash to shareholders and lower interest rates. The higher profits and lower capex liberate cash flows available to be redistributed to shareholders. Moreover, lower capex also depresses demand for savings in the economy, while weak wages depress middle-class incomes, which hurts aggregate demand. Additionally, higher corporate savings increases the wealth of the richest households, who have a high marginal propensity to save. This results in higher savings for the economy. With a greater supply of savings and lower demand for those savings, the neutral rate of interest has been depressed. Investment Implications First, in an environment of low inflation, investors should continue to favor businesses that can generate higher markups via pricing power. Equity investors should therefore continue to prefer industries where horizontal mergers are still increasing market concentration. Second, so long as the status quo continues, wages will have a natural cap, and so will the neutral rate of interest. This does not mean that wage growth cannot increase further on a cyclical basis, but it means that wages are unlikely to blossom as they did in the late 1960s, even within a very tight labor market. Without too-severe an inflation push from wages, the business cycle could remain intact even longer, keeping a window open for risk assets to rise further on a cyclical basis. Third, long-term investors need to keep a keen eye on the political sphere. A much more laissez-faire approach to regulation, a push toward self-regulation, and a much laxer enforcement of antitrust laws and merger rules were behind the rise in market power and concentration.13 The particularly sharp ascent of populism in Anglo-Saxon economies, where market power increased by the greatest extent, is not surprising. So far, populists have not blamed the corporate sector, but if the recent antitrust noise toward the Silicon Valley behemoths is any indication, the clock is ticking. On a structural basis, this could be very negative for asset prices. An end to this rise in market power would force profit margins to mean-revert toward their long-term trend, which is 4.7 percentage-points below current levels. This will require discounting much lower cash flows in the future. Additionally, by raising wages and capex, more competition would increase aggregate demand and lift real interest rates. Higher wages and aggregate demand could also structurally lift inflation. Thus, not only will investors need to discount lower cash flows, they will have to do so at higher discount rates. As a result, this cycle will likely witness both a generational peak in equity valuations as well as structural lows in bond yields. As we mentioned, these changes are political in nature. We will look forward to studying the political angle of this thesis to get a better handle on when these turning points will likely emerge. Mathieu Savary Vice President The Bank Credit Analyst   Footnotes 1       A monopsony is a firm that controls the price of its input because it is the dominant, if not unique, buyer of said input. 2       G. Grullon, Y. Larkin and R. Michaely, “Are Us Industries Becoming More Concentrated?,” April 2017. 3       The Herfindahl-Hirschman Index (HHI) is calculated by taking the market share of each firm in the industry, squaring them, and summing the result. Consider a hypothetical industry with four total firm where firm1, firm2, firm3 and firm4 has 40%, 30%, 15% and 15% of market share, respectively. Then HHI is 402+302+152+152 = 2,950. 4       J. Azar, I. Marinescu, M. Steinbaum, “Labor Market Concentration,” December 2017. 5     J. Azar, I. Marinescu, M. Steinbaum, “Labor Market Concentration,” December 2017. 6     M. Weinberg, “The Price Effects Of Horizontal Mergers”, Journal of Competition Law & Economics, Volume 4, Issue 2, June 2008, Pages 433–447. 7     O. Ashenfelter, D. Hosken, M. Weinberg, "Did Robert Bork Understate the Competitive Impact of Mergers? Evidence from Consummated Mergers," Journal of Law and Economics, University of Chicago Press, vol. 57(S3), pages S67 - S100. 8    J. Kwoka, “Mergers, Merger Control, and Remedies: A Retrospective Analysis of U.S. Policy,” MIT Press, 2015. 9     J. De Loecker, J. Eeckhout, G. Unger, "The Rise Of Market Power And The Macroeconomic Implications," Mimeo 2018. 10     “Chapter 2: The Rise of Corporate Market Power and Its Macroeconomic Effects,” World Economic Outlook, April 2019. 11     Please see The Bank Credit Analyst Special Report "Is Slow Productivity Growth Good Or Bad For Bonds?"dated May 31, 2017, available at bca.bcaresearch.com. 12     Productivity can be written as: 13     J. Tepper, D. Hearn, “The Myth of Capitalism: Monopolies and the Death of Competition,” Wiley, November 2018.

Yesterday we were stopped out on our long S&P managed health care/short S&P semis market neutral pair trade initiated on May 13, 2019 for a gain of 10%. Our thesis remains intact that a lot of negative news has been priced into HMOs on the back of the threat of the “Medicare For All” bill passage, while a lot of euphoria has been baked in the cake for semis despite their current down cycle. However, portfolio risk management is forcing our hand and given our ongoing de-risking, we are obeying our trailing stop loss for a gain of 10% in a very short time span. Bottom Line: Book gains of 10% in the long S&P managed health care/short S&P semis pair trade since inception and move to the sidelines for now.  

Overweight As a follow up to yesterday’s Insight Report where we highlighted our sanguine view on the S&P health care equipment index, a structural EM macroeconomic trend further reiterates our constructive view on the U.S. health care equipment providers. Aging population, one of the major factors that has been driving the explosion of health care spending in DM for the past 20 years, is now rapidly impacting EM. According to the UN, the share of the population aged 65 and older in EM countries will rise from roughly 7% this year to 16% by 2060, while population growth slows to below the replacement rate (see chart). Meanwhile, IMF data shows that EM health care spending is approximately 5% of GDP, whereas it stands in excess of 14% in DM. U.S. health care equipment providers are the first in line to benefit from the upcoming increase in health care spending in EM. Indeed, U.S. companies are often the only source of equipment for hospitals/clinics globally given their status of technological leaders. Bottom Line: Long-term EM demographic trends as well as the short-term “fear selling” discussed in Monday’s Special Report create an exploitable trading opportunity in the S&P health care equipment index. The ticker symbols for the stocks in the S&P health care equipment index are: BLBG: S5HCEP – ABT, MDT, DHR, BDX, SYK, ISRG, BSX, BAX, EW, ZBH, IDXX, RMD, TFX, HOLX, ABMD, VAR.