Health Care

Overweight Stick With Health Care Equipment Stick With Health Care Equipment While our overweight S&P health care equipment (HCE) call has given up some of its gains since inception, profit fundamentals have not changed and we continue to recommend an above benchmark allocation in this defensive sector. US medical equipment manufacturers are world leaders in supplying hospitals with quality equipment, and given that BCA’s house view for 2020 calls for a weaker dollar, HCE exporters have a bright future (middle panel, real trade-weighted dollar shown inverted). Further, the industry also showcases some of its defensive characteristics that are similar to its parent GICS1 health care sector, and in light of the recent disappointing ISM manufacturing PMI print, the path of least resistance is higher for relative share prices (bottom panel, ISM manufacturing index shown inverted). Bottom Line: We stand by our overweight S&P health care equipment call. 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, STE.   ​​​​​​​

2020 High-Conviction Calls: S&P Managed Health Care 2020 High-Conviction Calls: S&P Managed Health Care Overweight We upgraded the S&P managed health care group to overweight in April shortly after Bernie Sanders re-introduced his revamped “Medicare For All” bill. Despite the recent explosive run up in relative share prices – partly owing to the drop in Elizabeth Warren’s odds of winning the Democratic candidacy and partly given her watering down of her “Medicare For All” take up plan – we are adding this health care sub-group to our high-conviction overweight call list. HMOs are finally raising prices at the steepest rate of the past fifteen years and while such breakneck pace is unsustainable, profit margins are set to expand smartly. The profit margin backdrop is enticing for health insurers for another reason: labor cost containment. CEOs have been extremely prudent refraining from adding to headcount. One final profit margin booster is the rising 10-year Treasury yield, as roughly 10% of the industry’s operating income is tied to “investment income”. In other words, as insurers receive the premia they typically invest it in Treasurys and that explains the high EPS and margin sensitivity on interest rate moves. Thus, if BCA’s bond view materializes, it will prove a tonic to both margins and profits. With regard to technicals, relative share prices are not as oversold as they were mid-year, but remain below the neutral zone still offering investors a compelling entry point to this position. The ticker symbols for the stocks in this index are: BLBG: S5MANH – UNH, ANTM, HUM, CNC, WCG. ​​​​​​​

Health Care Leading The Pack Health Care Leading The Pack Overweight While we were a tad early lifting the broad S&P health care sector to an overweight stance mid-year, quarter-to-date, health care stocks are the best performing GICS1 sector up 10%, besting the SPX by 450bps. Such consistent health care outperformance is significant and we reiterate our overweight stance on this defensive sector. Elizabeth Warren’s moves in the polls are a key driver behind the recent health care stellar returns and we would continue to lean against any increase in her probabilities of both winning the Democratic nomination and the 2020 Presidency (see chart). Importantly, Warren’s toning down of her “Medicare For All” speedy adoption to a more pragmatic phase-in approach over a number of years fueled the stampede into health care stocks in general and managed health care (which we are also overweight) in particular. Bottom Line: Any selloff in health care equities due to Warren’s rise in the polls presents an excellent buying opportunity. Stay overweight the S&P health care sector.

Highlights Building on a previous special report focused on the investable market, in this report we construct and present models designed to predict the odds of Chinese domestic equity sector outperformance. BCA Research's China Investment Strategy service will aim to use our newly developed sector outperformance probability models to better understand the drivers of performance at any given moment, and to make more active equity sector recommendations in the future. Episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) than has been the case for the investable market, suggesting that periods of “abnormal” relative sector performance may occur more frequently than in the investable universe. Among the predictors included in our model, our Li Keqiang leading indicator (based on monetary conditions, money, and credit growth) has been the most important. Our base case view argues in favor of domestic cyclicals over defensives over the coming year, but recent sector performance suggests that domestic consumer discretionary and tech should be favored within a cyclical equity portfolio over energy, materials, and industrials barring a surge in oil prices or a capitulation by Chinese policymakers in favor of “flood irrigation-style” stimulus. Over the long-term, we argue that investors have a good reason to favor domestic defensives over cyclicals until the latter demonstrates meaningfully better earnings performance. Feature We examined China’s investable equity sector performance in detail in our October 30 Special Report,1 with a particular emphasis on understanding the specific macroeconomic or equity market factors that have historically predicted relative sector performance. In today’s report, we extend our approach to China’s A-share market. Our research focused 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 find that episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) that has been the case for the investable market, suggesting that periods of “abnormal” relative sector performance may occur more frequently than in the investable universe. Among the macroeconomic and equity market factors that we found to be important predictors, our Li Keqiang leading indicator was the most significant. This confirms that China’s domestic market is more sensitive to monetary conditions, money, and credit growth than its investable peer. We also note the sharp difference in the relative performance of cyclicals versus defensives in the domestic market compared with the investable market, and what this means for investors over the coming 6-12 months. Finally, we argue that investors should maintain a structural bias towards defensive stocks in the domestic market until cyclicals demonstrate meaningfully better earnings performance, and point to an existing position in our trade book for investors interested in strategically allocating to the A-share market. Detailing Our Approach In our effort to better understand historical periods of domestic sector performance, 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 Report).2 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”). We find that episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) than has been the case for the investable market. Chart I-1A and Chart 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 ##br##Aimed At... Chart 1A This Report Builds Models Aimed At… This Report Builds Models Aimed At… Chart I-1B...Predicting The Shaded Regions Of These Charts Chart IB …Predicting The Shaded Regions Of These Charts …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 (LKI) 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. Chart I-2A and Chart 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 2A We Use These Macroeconomic And Equity Market Factors… We Use These Macroeconomic And Equity Market Factors… Chart I-2B...To Predict Periods Of Equity Sector Outperformance Chart 2B …To Predict Periods Of Equity Sector Outperformance …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 three months in order to reduce the need to forecast. 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, is detailed in Box I-1 of our October 30 Special Report (please see footnote 1). Key Drivers Of Sector Performance: Domestic Versus Investable Pages 11-22 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 11-22 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. Following a review of our domestic equity sector outperformance models, differences in the results from those presented in our previous report can be organized into three distinct elements: 1) the breadth of macro & equity market factors in predicting sector performance, 2) the relative importance of our LKI leading indicator, and 3) the difference between domestic/investable cyclical versus defensive performance. The Breath Of Predictive Factors Chart I-3In The Domestic Market, The Breadth Of Predictive Factors Is Narrower Chart 3 In The Domestic Market, The Breadth Of Predictive Factors Is Narrower In The Domestic Market, The Breadth Of Predictive Factors Is Narrower Compared with the models for investible sector performance that we detailed in our previous report, our work modeling domestic equity sector performance highlights that the breadth of predictive factors is narrower, particularly among cyclical sectors (Chart I-3). Our model for domestic materials (shown on page 12) is one exception to this rule, but we found that our models for energy, industrial, and consumer discretionary relative performance were all focused on fewer predictors than is the case for the investable market. In addition, our domestic utilities model has considerably worse predictive power than our model for investable utilities. The case of industrials is particularly notable: our model for investable industrials highlighted the importance of tight monetary policy, rising core inflation, rising broad market stock prices & earnings, and overbought and oversold technical conditions in explaining past periods of industrial sector outperformance. By contrast, our domestic industrials model is quite simple: the sector has been more likely to outperform, with a lag, when our BCA China Activity Index and LKI leading indicator have been rising, and underperform following periods of extreme overvaluation. One of the core conclusions of our previous report was that investors should view the relative performance of investable industrials versus consumer staples as a reflationary barometer, given the strong sensitivity of both sectors to tight monetary policy. We explained this sensitivity by pointing to the substantial difference in corporate health between the two sectors: industrial firms are heavily debt-laden and thus experience deteriorating operating performance and an environment of rising interest rates. In comparison, food and beverage firms appear to have the strongest balance sheets among the sub-sectors that we have examined, suggesting that they would benefit less from easier monetary conditions than firms in other industries. Our leading indicator for Chinese economic activity has been considerably more important in predicting domestic equity sector outperformance than in the investable market. However, these dynamics appear to be completely absent in influencing performance in China’s domestic equity market. Not only has domestic industrial sector relative performance not been negatively linked to periods of tight monetary policy, but our model for consumer staples (shown on page 15) highlights that periods of staples performance have been driven by two simple factors: the relative trend in staples EPS  (positive sign), and the trend in broad market EPS (negative sign). The Relative Importance Of Monetary Conditions, Money, And Credit Growth Chart I-4 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 our LKI leading indicator is the most important signal of sector performance that emerged from our analysis, followed by rising core inflation, rising broad market stock prices, rising economic activity, and oversold technical conditions. The ranking of results shown in Chart I-4 is fairly similar to those that we listed for the investable market, with two exceptions. First, for the domestic market, periods of tight monetary policy were considerably less important than in the investable market as an important predictor of relative sector performance. Instead, our LKI leading indicator was by far the most important predictor, which underscores a point that we have made in previous reports: domestic stocks appear to be much more sensitive to the trend in monetary conditions, money, and credit growth than for the investable market. This increased sensitivity has helped explain the difference in performance this year between the investable and domestic market, underscoring that the former has more catch-up potential than the latter in a trade truce scenario. Chart I-4Monetary Conditions, Money, & Credit Growth Drive A-Share Performance Chart 4 Monetary Conditions, Money, & Credit Growth Drive A-Share Performance Monetary Conditions, Money, & Credit Growth Drive A-Share Performance Second, in the investable market, episodes of significant overvaluation had essentially no power to predict future episodes of equity market underperformance. But this factor was an important or very important contributor to our domestic industrials, health care, and tech models. This finding is consistent with our May 23 Special Report, which noted that value stocks have outperformed in China’s domestic equity market over the past five years and underperformed in the investable market (Chart I-5). Chart I-5Value Has Been A More Successful ##br##Factor In The Domestic Market Chart 5 Value Has Been A More Successful Factor In The Domestic Market Value Has Been A More Successful Factor In The Domestic Market   Major Differences In The Performance Of Cyclicals Versus Defensives The results of our models for domestic equity sector performance did not change the cyclical & defensive labels that we applied in our previous report. The signs of the predictors shown in the tables on pages 11-22 clearly highlight that the domestic energy, materials, industrials consumer discretionary, and information technology sectors are cyclical sectors, and that consumer staples, health care, financials, telecom services, utilities, and real estate are defensive. What is striking, however, is that there is a major difference in the relative performance of equally-weighted domestic cyclicals versus defensives compared with what has occurred in the investable market over the past decade. Chart I-6A and Chart I-6B illustrate the different relative performance trends, along with their corresponding trends in relative P/E and relative EPS. Whereas the relative performance of investable cyclicals versus defensives has had somewhat of a stable mean over the past decade, domestic cyclicals have badly underperformed since early-2011. The charts also make it clear that this underperformance has been driven by a downtrend in relative EPS, not due to trend differences in relative valuation. Chart I-6ACyclicals/Defensives Somewhat Mean-Reverting In The Investable Market... Chart 6A Cyclicals/Defensives Somewhat Mean-Reverting In The Investable Market… Cyclicals/Defensives Somewhat Mean-Reverting In The Investable Market… Chart I-6B...But Not So In The Domestic##br## Market Chart 6B …But Not So In The Domestic Market …But Not So In The Domestic Market Digging further, it appears that this discrepancy can be largely explained by the significant difference in performance between investable and domestic tech over the past decade (Chart I-7). Whereas the former has outperformed the overall investable index by roughly 4-5 times since 2010, the relative performance of the latter has only very modestly risen. In effect, Charts I-6 and I-7 highlight that Chinese cyclical sectors have been structurally impaired over the past decade and have only been “saved” in the investable market by massive outsized outperformance of the tech sector. The fact that investable tech sector performance itself has been largely driven by 2 extremely successful firms underscores how narrowly based the investible cyclical versus defensives performance trend has been. Chart I-7A Huge Gap In Tech Explains Domestic Cyclical Underperformance Chart 7 A Huge Gap In Tech Explains Domestic Cyclical Underperformance A Huge Gap In Tech Explains Domestic Cyclical Underperformance Investment Conclusions There are three conclusions that investors can draw from our analysis. First, our research shows that episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) that has been the case for the investable market. This does not mean that domestic sector performance is not significantly impacted by macro and top down equity market factors, but it suggests that periods of “abnormal” relative sector performance may occur more frequently than in the investable universe. As such, investors should be prepared to include episode-specific investigation of abnormal performance as a regular part of their domestic equity sector allocation decisions. Investors should favor domestic cyclicals over the coming year, with exposure focused on consumer discretionary and tech. Second, the fact that our LKI leading indicator is in an uptrend suggests that investors should favor domestic cyclicals over defensives over the coming year, with a caveat. We have noted in several previous reports that our indicator is in a shallow uptrend, and the slower pace of money and credit growth than during previous economic upswings suggests that the bar may be higher for some cyclical sectors to outperform. We would advise investors to watch closely over the coming 3-6 months for signs of a technical breakout in all cyclical sectors. But sector performance in Q1 of this year, when the overall A-share market rose sharply versus global stocks, suggests that domestic consumer discretionary and tech should be favored within a cyclical equity portfolio over energy, materials, and industrials barring a surge in oil prices or a capitulation by Chinese policymakers in favor of “flood irrigation-style” stimulus (Chart I-8). Within resources, we prefer the investable energy sector to its domestic peer, due to a sizeable valuation advantage. Chart I-8Favor Select Domestic Cyclical Sectors Over The Coming Year Chart 8 Favor Select Domestic Cyclical Sectors Over The Coming Year Favor Select Domestic Cyclical Sectors Over The Coming Year As a third and final point, abstracting from our bullish outlook for select cyclical sectors over the coming year, Charts 6 and 7 clearly argue for investors to maintain a structural bias towards defensive stocks in the domestic market until cyclicals demonstrate meaningfully better earnings performance. In the May 23 Special Report that we referred to above, we noted that an A-share portfolio formed of industry groups with above-median return on equity and below-median ex-post beta has significantly outperformed over the past decade. Table I-1 presents the current industry group weights of this portfolio, and shows that overweight exposure is concentrated in the health care, consumer staples, and real estate sectors (all of which are defensive), and a heavy underweight towards industrials. Table I-1Current High ROE / Low Beta Factor Industry Group Portfolio Weights* Table 1 Current High ROE / Low Beta Factor Industry Group Portfolio Weights* Current High ROE / Low Beta Factor Industry Group Portfolio Weights* For clients who are interested in strategically allocating to the A-share market, we maintain a long position in this portfolio relative to the MSCI China A Onshore index in our trade book, and plan to continue to update the performance of the trade on a weekly basis. Energy Chart II-1 Chart II-1 Energy Energy Table II-1 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Similar to the investable energy sector, periods of domestic energy sector outperformance are strongly positively related to rising oil prices and rising headline inflation in China. We noted in our previous report that this is a behavioral relationship, rather than a fundamental one. Domestic energy stocks are negatively associated with rising broad market stock prices, unlike their investable peers. This largely reflects the fact that the relative performance of domestic energy stocks has been in a structural downtrend over the past decade. From 2010 to mid-2016, this decline was caused by a persistent underperformance in earnings. Since mid-2016, domestic energy sector EPS have been rising in relative terms, meaning that more recent underperformance has been due to multiple contractions. While not as relatively cheap as their investable peers, domestic energy stocks are heavily discounted versus the broad domestic market based on both the price/earnings ratio and the dividend yield. Consequently, it is possible that domestic energy stocks may at some point begin to outperform in a rising broad equity market environment. For now, our model argues for an underweight stance towards domestic energy due to the lack of a clear uptrend in oil prices. As a pure value play, investable energy stocks maintain a dividend yield of nearly 6.5%, and are thus more attractive than their domestic peers. Materials Chart II-2 Chart II-2 Materials Materials Table II-2 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our model for the domestic materials highlights that the sector’s performance has been related to strengthening economic activity and strongly related to a rising Li Keqiang leading indicator. Among the equity market variables that we tested, materials outperformance has been positively associated with rising relative EPS, rising broad market EPS, and prior oversold technical conditions. Similarly, the investable materials sector, these results show that domestic materials are a strong play on accelerating Chinese economic activity. The factors included in our domestic materials sector model are similar to those included in our investable material, except that relative material earnings have also been a significant predictor of sector relative performance. In addition, the macro & equity market predictors included in our domestic materials model have done a better job of leading material sector performance. The odds of domestic materials outperformance rose twice above the 50% mark this year according to our model, without any corresponding improvement in relative stock prices. The spikes in the model occurred largely because domestic materials became significantly oversold; technical conditions for the sector have only twice been weaker over the past decade. This underscores that investors should be watching domestic materials closely in Q1 of next year for signs of a relative rebound. Industrials Chart II-3 Chart II-3 Industrials Industrials Table II-3 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance The results of our model for domestic industrial sector outperformance are interesting, as they imply that the drivers of performance are different between the domestic and investable markets. In the investable index, we found that industrials were heavily sensitive to monetary policy, rising core inflation, relative sector earnings, and periods of rising broad market stock prices. Our domestic model is considerably simpler: industrials outperform, with a lag, when our activity index and Li Keqiang leading indicator are rising. Periods of strong overvaluation have also been significant in predicting future episodes of domestic industrial sector underperformance. It is not clear to us why the drivers of relative performance for domestic industrials have been different than in the investable equity index, But the good news is that the relative simplicity of the model makes the investment decision making process for domestic industrials considerably easier. Today, domestic industrials are significantly undervalued, and our Li Keqiang leading indicator is in a shallow uptrend. This suggests that domestic industrials are likely to begin outperforming at some point in early-2020 following a bottoming in Chinese economic activity, unless policymakers are quick to tighten once activity begins to improve (which would be contrary to our expectations). Consumer Discretionary Chart II-4 Chart II-4 Consumer Discretionary Consumer Discretionary Table II-4 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our domestic consumer discretionary model highlights that the sector’s relative performance is positively associated with a rising Li Keqiang leading indicator, rising core inflation, and rising broad market stock prices. Similar to its investable peers, domestic consumer discretionary stocks are cyclical, and positive relationship with core inflation may reflect improved pricing power for the sector. Unlike investable consumer discretionary, the domestic consumer discretionary has not been meaningfully impacted by the December 2018 changes to the global industry classification standard. Hence, our model does not exclude the internet & direct marketing retail sector as we did in our previous report on investable sectors. For now, our model suggests that the domestic consumer discretionary sector is likely to continue to underperform, given decelerating core inflation and the lack of a clear uptrend in the broad domestic equity index. However, as a cyclical sector, we will be watching closely for an upside breakout in domestic consumer discretionary performance in the first quarter as a signal to increase exposure to the sector. Consumer Staples Chart II-5 Chart II-5 Consumer Staples Consumer Staples Table II-5 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our domestic consumer staples model is significantly different than that shown in our previous report for investable staples. This reflects sizeable differences in investable/domestic staples relative performance over the past decade, particularly from mid-2015 to late-2017 (where domestic staples outperformed significantly and investable staples languished). Of the two predictors found to be significant in explaining historical periods of domestic staples performance, a negative relationship with the trend in broad market EPS has been the most important. This underscores that staples are defensive sector. The trend in staples relative earnings has closely followed in importance, showing that the tremendous outperformance in domestic consumer staples over the past several years has, at least in part, been driven by fundamentals. Still, domestic consumer staples are currently priced at 34x earnings per share, compared with 15x for the overall domestic market. While our model currently argues for continued staples outperformance, the risk of a valuation mean reversion next year, against the backdrop of an improving economy, is above average. Over the coming 6-12 months, investors should be closely monitoring domestic staples for signs of waning earnings momentum and/or a major technical breakdown as potential signals to reduce domestic staples exposure. Health Care Chart II-6 Chart II-6 Health Care Health Care Table II-6 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Over the past decade, periods of domestic health care outperformance have been negatively associated with rising economic activity, rising core inflation, and rising broad market stock prices. Oversold technical conditions and periods of overvaluation have also helped predict future episodes of health care relative performance. These factors clearly point to the defensive nature of domestic health care, similar to health care stocks in the investable index. However, one clear difference between investable and domestic health care is that the former appears to have leading properties and the latter does not. We noted in our previous report that periods of investable health care underperformance appeared to lead, on average, our BCA Activity Index, periods of rising core inflation, and uptrends in the broad investable index. By contrast, domestic health care lags the Activity Index and core inflation by just over a year, and also lags the trend in broad market EPS. Our model points to further health care outperformance, but we would expect domestic health care stocks to underperform at some point next year following an improvement in economic activity and a resumed uptrend in broad domestic EPS. Financials Chart II-7 Chart II-7 Financials Financials Table II-7 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our outperformance probability model for domestic financials highlights that the sector is countercyclical: periods of outperformance have been negatively related to our LKI leading indicator, rising core inflation, and rising broad market stock prices. Similar to the case of the investable index and unlike the case globally, financials are clearly defensive. Investable financials have exhibited atypical performance this year according to the model presented in our previous report. By contrast, domestic financials have performed in line with what our model has suggested: our LKI leading indicator is in a shallow uptrend, and the relative performance of domestic financials has trended flat-to-down since late-2018. Barring a major shift by the PBoC towards a hawkish stance in the coming year (which we do not expect), our base case view for the Chinese economy implies that domestic financials are likely to continue to underperform. Banks Chart II-8 Chart II-8 Banks Banks Table II-8 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our model for domestic banks is similar to that of financials, with some important differences. In addition to being sensitive to our LKI leading indicator, domestic bank performance is negatively related to our Activity Index. Oversold technical conditions have also been quite important in predicting future episodes of domestic bank outperformance. The model is currently forecasting domestic bank underperformance, although it was late in predicting the selloff in bank stocks that began late last year. Similar to the case for domestic financials, our baseline view for the Chinese economy implies that domestic bank are likely to continue to underperform over the coming year. Information Technology Chart II-9 Information Technology Information Technology Table II-9 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our model for the domestic technology sector is different than that of investable tech, which reflects the vast difference in performance between the two sectors. While the relative performance of domestic tech has trended sideways over the past decade, investable tech stock prices have risen fourfold relative to the broad investable index. This difference is largely accounted for by the absence of the BAT stocks (Baidu, Alibaba, Tencent) from the domestic market. Similar to investable tech, domestic technology stocks are negatively related to tight monetary policy, and positively linked with a pro-cyclical economic variable (a rising LKI leading indicator). However, strangely, domestic tech has been strongly and negatively related to rising headline inflation, a finding with no clear fundamental basis. The model has been less successful in predicting domestic tech performance over the past year than in the past, which appears to be linked to the inclusion of headline inflation in the model. Rising headline inflation has been clearly associated with three major episodes of domestic tech underperformance since 2010, but over the past year domestic tech has outperformed as headline inflation accelerated. For now we would advise investors to focus on the other factors in the model: the lack of overvaluation, and our view that policy will remain easy on a measured basis, supports an overweight stance towards domestic tech over the coming year. Telecom Services Chart II-10 Telecom Services Telecom Services Table II-10 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our domestic telecom services relative performance model highlights that the sector is defensive like its investable peer, but the factors driving performance are somewhat different. The only similarity between the two models is that periods of outperformance are negatively related to rising broad market stocks prices for both investable and domestic telecom services, with domestic telecom stocks responding with a lag. Among the macro factors included in the model, periods of domestic telecom services outperformance are negatively and coincidently related to our LKI leading indicator, and positively related to tight monetary policy (with a slight lead). Oversold technical conditions have also proven to help predict future episodes of outperformance. The model failed to predict a brief period of outperformance in mid-2018, but has generally accurately predicted underperformance of domestic telecom stocks since early-2017. Barring a collapse in the US/China trade talks or considerably weaker near-term economic conditions than we expect, domestic telecom services will likely continue to underperform until the specter of tighter monetary policy emerges. This is unlikely to occur until the middle of 2020, at the earliest. Utilities Chart II-11 Utilities Utilities Table II-11 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Overall, our domestic utilities model has considerably worse predictive power than our model for investable utilities. The model shows that the performance of domestic utilities is negatively related to rising core inflation (with a lag) and rising broad market EPS, but these relationships are not particularly strong. We noted in our June 19 Special Report that domestic utilities ranked highly on the impact that relative EPS had on predicting relative stock prices , yet relative sector earnings did not register as a significant predictor in our model. This apparent discrepancy is resolved by differences in the time horizon between these two approaches. The analysis that we presented in our June 19 Special Report examined the relationship between earnings and stock prices over the entire sample period (2011-2018), meaning that it examined the predictive power of earnings over the long-term. The models built in this report have focused strongly on explaining periods of outperformance over a 6-12 month time horizon, there have been enough deviations in the trend between the relative performance of utilities and relative utilities earnings that the relationship between the two was not sufficiently strong to show up in the model. In other words, the long-term link between utilities relative earnings and stock prices is strong, but the short-term link is fairly weak. Real Estate Chart II-12 Real Estate Real Estate Table II-12 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Similar to investable real estate, our model shows that domestic real estate is a counter-cyclical sector in that it is negatively related to periods of rising economic activity, a rising LKI leading indicator, tight monetary policy, and rising core inflation. Overbought technical conditions have also aided in predicting future episodes of domestic real estate underperformance. Our model for domestic real estate stocks has performed quite well on average, but its predictive success since late-2017 has been mixed. This period of atypical underperformance has coincided with a considerably weaker rebound in residential floor space sold than has occurred in previous recoveries in the real estate market. This suggests that domestic real estate stocks are more susceptible to trends in housing sales than their investable peers (which appear to be mostly sensitive to rising house prices). We noted in our November 6 Weekly Report that floor space sold is picking up , but it still remains weak when compared with history. This, in combination with our view that the Chinese economy will improve over the coming year, suggests that investors should avoid domestic real estate exposure relative to the overall domestic equity market. Footnotes 1  Please see China Investment Strategy Special Report "A Guide To Chinese Investable Equity Sector Performance," dated October 30, 2019, available at cis.bcaresearch.com 2  Please see China Investment Strategy "Six Questions About Chinese Stocks," dated January 16, 2019, available at cis.bcaresearch.com 3  Please see China Investment Strategy Special Report "Chinese Equity Sector Earnings: Predictability, Cyclicality, And Relevance," dated June 19, 2019, available at cis.bcaresearch.com 4  Please see China Investment Strategy Weekly Report "China Macro And Market Review," dated November 6, 2019, available at uses.bcaresearch.com Cyclical Investment Stance Equity Sector Recommendations

Biotech Recovery Biotech Recovery Overweight While our overweight call in the S&P biotech index is offside, it is more than offset by the concurrent underweight call we have on the S&P pharma index. But, biotech stocks are now in the recovery ward as the sector made a U-turn in early October and has been rallying ever since. The rebound coincides with the return of M&A activity following the dramatic 50% contraction since the recent peak in dollar terms (middle panel) and completely disappearing premia (bottom panel). As a reminder this is a key theme behind our preference for biotech stocks that big pharma is still on the hunt for (for additional details please refer to our mid-February Weekly Report). Meanwhile, the divergence between biotech’s relative share prices and 10-year Treasury yields has been extreme and is unsustainable. The upshot is that there is plenty of scope for relative share prices to rally further and narrow the gap, despite the recent selloff in the bond market (top panel, 10-year Treasury yield shown inverted). News on the earnings front is also positive as most of the major players have reported a solid quarter.   Bottom Line: We continue to recommend a barbell approach preferring the S&P biotech index at the expense of big pharma. The ticker symbols for the stocks in the S&P biotech index are: BLBG: S5BIOT – ABBV, AMGN, GILD, BIIB, CELG, VRTX, REGN, ALXN, INCY. ​​​​​​​

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 Growth Is Experiencing A Welcome Rebound Growth 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... Economic Indicators Do Not Lead The Markets... Economic 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 Depressed Performances Have Scope For Long-Term Upside ...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 The Credit 6-Month Impulse Should Briefly Rebound The 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 The Oil Price 6-Month Impulse Should Help Oil Importing Economies The 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 If The Sharpest Decline In Bond Yields Is Over, Cyclicals Could Outperform If 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 Long Sweden Versus Denmark = Long Financials And Industrials Versus Biotech Long Sweden Versus Denmark = Long Financials And Industrials Versus Biotech Overweight banks means overweight Spain (Chart I-8). Chart I-8Long Spain = Long Banks Long Spain = Long Banks Long 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 Long Norway = Long Oil And Gas Long Norway = Long Oil And Gas Chart I-10Long Ireland = Long Airlines Long Ireland = Long Airlines Long 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 Long FTSE250 Versus FTSE100 = Long Pound Long 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 US: Oil & Gas Vs. Telecom US: Oil & Gas Vs. Telecom Chart I-13Tin Tin Tin 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 Four Impulses, Three Mistakes Four Impulses, Three Mistakes Four Impulses, Three Mistakes Four Impulses, Three Mistakes Four Impulses, Three Mistakes Four Impulses, Three Mistakes Four Impulses, Three Mistakes Four Impulses, Three Mistakes Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields   Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II_8Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations  

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... This Report Builds Models Aimed At... This Report Builds Models Aimed At... Chart I-1B...Predicting The Shaded Regions Of These Charts ...Predicting The Shaded Regions Of These Charts ...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... We Use These Macroeconomic And Equity Market Factors... We Use These Macroeconomic And Equity Market Factors... Chart I-2B...To Predict Periods Of Equity Sector Outperformance ...To Predict Periods Of Equity Sector Outperformance ...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 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance Chart I-B2With Short Cycles, Excessive Lags Risk Picking Up The Previous Cycle With Short Cycles, Excessive Lags Risk Picking Up The Previous Cycle With 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 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Cyclical Stocks Are Bombed Out Versus Defensives Cyclical 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 A Seeming Contradiction: Real Estate Is High-Beta, But Defensive A 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 Still Following The Defensive Playbook This Year Still 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 Diverging Corporate Health Explains Industrials/Staples Monetary Policy Sensitivity Diverging 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 In China, Food Prices (Not Energy) Account For Headline/Core Differences In 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 Key Defensive Sectors Are Still Outperforming, Supporting Our Neutral Tactical Stance Key Defensive Sectors Are Still Outperforming, Supporting Our Neutral Tactical Stance Chart I-10Industrials Vs. Staples Anticipated That Easing Would Only Be Measured Industrials Vs. Staples Anticipated That Easing Would Only Be Measured Industrials 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 Energy Energy Table II-1 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance   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 Materials Materials Table II-2 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Industrials Industrials Table II-3 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Consumer Discretionary Ex-Internet & Direct Marketing Retail Consumer Discretionary Ex-Internet & Direct Marketing Retail Table II-4 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Consumer Staples Consumer Staples Table II-5 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Health Care Health Care Table II-6 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Financials Financials Table II-7 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Banks Banks Table II-8 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Tech+' Tech+' Table II-9 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Telecom Services Telecom Services Table II-10 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Utilities Utilities Table II-11 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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 Real Estate Real Estate Table II-12 A Guide To Chinese Investable Equity Sector Performance A Guide To Chinese Investable Equity Sector Performance 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

Going Against The Grain Going Against The Grain 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.