Equities

Special Report

Highlights Since AQR rebranded its flagship “Risk Parity” mutual fund late last year, many clients have asked about risk parity and its potential impact on financial markets if interest rates rise. The key to a “risk-based” approach is “risk diversification” and the use of leverage. Like any investment tool, it has its advantages and limitations. “Risk parity” portfolios differ greatly, depending on the choice of assets and the portfolio construction method. There are many ways to construct a risk-based portfolio. We highlight three: fixed weights; variable weights with inverse volatility; and variable weights with optimization. Fixed-weight risk-parity portfolios are not “risk diversified” ex post. Variable-weight risk-parity portfolios constructed using inverse volatility do not guarantee equal risk allocations. “Truly risk-diversified” portfolios constructed using our proprietary optimization algorithm have consistently outperformed those constructed with inverse volatility. Our approach not only achieves better risk diversification, but can also be used as an alpha overlay strategy. Risk parity does not always outperform in the long run, but always outperforms in recessions. Rising yields alone do not necessarily hurt risk parity. The worst environment for risk parity is the combination of rising yields and the underperformance of bonds relative to both cash and stocks – because both leverage and interest-rate movements work against risk parity. Worryingly, the past three years have been like this, similar to the 1949-1969 period when risk parity would not have performed. Feature Beautiful Simulation! Ugly Reality? Ray Dalio’s Bridgewater Associates created in the 1990s “The All Weather Investment Strategy,” which is known as the foundation of the “Risk Parity” movement.1, 2 Both back-testing and real-life performance from Bridgewater show that the “All Weather” portfolio did live up to its purpose as a low-beta, long-term portfolio that weathers through different economic cycles.2 The term “Risk Parity,” however, was coined by Edward Qian in 2005, and Qian even went as far as saying that risk parity is a way to the “New Holy Grail In Investing” – i.e. “upside participation and downside protection.”3 Only after the 2008 financial crisis did risk parity gain real traction, because investors were hungry for alternative tactics after traditional asset allocation approaches all failed miserably. Invesco began offering a risk parity strategy mutual fund in June 2009, and AQR launched its risk parity mutual fund in September 2010. According to the IMF, risk parity funds had AUM of US$150 billion to $175 billion at the end of 2017,4 while Bridgewater estimated in 2016 that there were about US$400 billion AUM dedicated to risk parity strategies globally, of which about US$150 billion was managed by external managers – with Bridgewater accounting for about half of the externally managed assets.2  While most risk parity believers dedicate a portion of their assets to risk parity strategies, some investors have gone in full-heartedly. For example, in 2016, Danish pension fund ATP completed its transition to a risk-based multi-factor approach by adopting a “four-factor building-block portfolio approach” that is “…in part inspired by Bridgewater’s All Weather” yet “owes more to the thinking of investment manager AQR and the academic field of ‘financial economics’ more generally.”5 At the end of 2018, ATP’s risk allocation to the four risk factors – interest-rate factor, inflation factor, equity factor and other factors – is shown in Chart 1.6 On the other hand, in September 2014, the San Diego County Employees Retirement Association board decided to fire its outsourced CIO from Houston-based Salient Partners, who had favored leverage-heavy (up to five times) risk-parity investments and had been given the reins of the US$10 billion pension fund.7 In fact, the growing popularity of risk parity has been accompanied by growing criticism, especially when risk-parity funds did not do well. In December 2018, AQR re-branded its flagship risk-parity mutual fund by dropping “Risk Parity” out of its name and tweaking the strategy for more flexibility after having suffered heavy outflows.8 Even though the change in the US$344 million fund did not reflect a shift in AQR’s views on the merits of risk-parity strategies (which accounted for about US$30 billion out of AQR’s US$226 billion in assets), Cliff Asness, the co-founder of AQR, did write a long blog discussing sticking with factor investing in general. “If sticking with them were easy, the threat of them being ‘arbitraged away’ would indeed be much greater, and nobody would take the other side,” he wrote.9 Chart 2Beautiful Simulation, Ugly Reality It is easy to say “stick with it for the long run,” especially when back-tests show robust results from well-respected asset managers and researchers.10,11,12 Our own simulations also show beautiful results even for the recent period not covered by most published papers (Chart 2, top panel).  In reality, however, publicly available information shows that risk parity funds have encountered some unpleasant underperformance since 2013 compared to conventional global 60/40 stock-bond portfolios (Chart 2, bottom three panels). Seven years of underperformance is a tough pill to swallow for any investor; it is little wonder we have received client requests on this subject more frequently of late. In this Special Report, we attempt not to take sides to argue for or against risk parity strategies. Instead, we focus our efforts on sorting through the jungle of confusing ways that risk-parity portfolios are defined and constructed, and highlight three typical ways used by many risk parity managers. We present simulated results using these different methods and our own proprietary optimization algorithm, aiming to answer the following questions often asked by our clients: What is risk parity?  How is a risk parity portfolio constructed? What are the key differences among the various ways of constructing risk parity portfolios? Is it true that risk parity outperforms in the long run? Is it true that risk parity can outperform even if yields rise? How should asset allocators use risk-parity strategies? Risk Parity Basics There is no widely agreed-upon definition of risk parity, nor on how to construct a risk-parity portfolio. However, the “risk-based” allocation principle is the same, while differences among different managers lie largely in the process of portfolio construction, especially when the number of assets in consideration is more than two – because correlation does not matter when there are just two assets in a risk-based allocation approach. The Risk-Parity Principle: According to Bridgewater: “Risk parity is the means of adjusting the expected risks and returns of assets to make them more comparable.”13 If so, then a “better diversified portfolio” can be created by equally weighting those adjusted assets with low or no correlation with one another. This way, a portfolio with a higher Sharpe ratio can be achieved than would otherwise be possible using the conventional capital-based approach. Then, different degrees of leverage can be used to achieve desirable levels of risk and return. In terms of risk, investors need to consider not only the volatility of a portfolio, but also the risk of large portfolio drawdowns due to wrong assumptions. Since one does not know for sure in advance how each asset will perform, Bridgewater characterizes the investment regimes using growth and inflation, identifying which asset classes do well in each regime and allocating 25% weight in each of the four growth-inflation regimes.14 Despite robust back-test results from asset managers and researchers, risk parity funds have not lived up to their promise since 2013. So, one key to risk parity is to diversify across asset classes that behave differently across different economic regimes such that each asset contributes equally to portfolio risk. In general, equities do well in rising growth and falling inflation regimes, nominal bonds do well in deflationary or recessionary regimes, and commodities do well in rising inflation regimes.  While Bridgewater includes corporate and EM credits and inflation-linked bonds in its universe of asset classes, not all risk-parity strategies include the exact same breadth of assets. For example, it can be argued that corporate and EM credits share more of the “equity factor,” since they have a high degree of sensitivity to rising growth as do equities, while inflation-linked bonds are a hybrid of nominal bonds and inflation. The Risk-Parity Portfolio Construction: There are many different ways to construct a risk-based diversified portfolio. The key differences are: 1) how the weights of assets are determined for the unlevered risk-parity portfolio, and 2) how leverage is determined to reach the desired return/risk profile. Based on these two key aspects, there are generally three different ways to construct a risk-parity portfolio, as shown in Table 1. The one represented by Bridgewater is more qualitative, while the other two are more quantitatively defined. Table 1Risk Parity Implementation Summary When there are only two assets, it is easy to show that all three methods produce exactly the same allocations for the basic risk-parity portfolio without leverage. When there are more than two assets, however, the two approaches represented by Bridgewater15 and AQR16,17 are easy to compute, but the optimization approach based on equal contribution to risk (either in the sense of marginal contribution to risk or contribution to total risk18) has high demand in computing power. Also, it is not true that risk-parity does not need return estimates. Return estimates are not needed to determine a basic risk-parity portfolio, but they are needed to determine leverage when the target is a specific return other than volatility. Does Strategic Risk Parity Outperform In The Long Run? The pioneering “All Weather” fund was launched by Bridgewater in 1996, and has been used as a “strategic asset allocation mix” that is rebalanced to keep “constant” asset weights.19 To try to understand the early thinking behind risk parity, we used Bridgewater’s method to simulate a simple two-factor constant-weight risk-parity portfolio using global stocks20 and global bonds21 in two steps: First, we used monthly return data of stocks and bonds from January 1970 to December 1995 to estimate stock volatility (Vs ) and bond volatility (Vb ). The stock and bond weights in the unlevered risk parity portfolio (RP1) are determined as follows: Wb = Vs / (Vs +Vb), and Ws = 1- Wb......................(1) Depending on the required target, leverage will be applied to RP1. The leverage ratio is simply the target volatility (or return) divided by the volatility (or return) of the unlevered risk parity portfolio. Table 2 shows the simulated results with seven different targets, which appear to support the following claims of risk-parity supporters: A risk parity portfolio is better than a 60/40 portfolio because it achieves a higher Sharpe ratio; Equities and bonds contribute equally to total portfolio risk in a risk-parity portfolio, while a 60/40 portfolio risk is dominated by equities (85% in the stated period); With the use of proper leverage, risk parity achieves higher return with the same volatility or the same return with lower volatility. The statistics in Table 2, however, are based on “in sample” data with “perfect foresight.” In reality, no portfolio manager has the luxury of going back in time to implement any portfolio. Table 2Global Stock-Bond Risk Parity Portfolios (In Sample) So, the second step of our simulation is to test how these portfolios would have performed going forward if they were rebalanced monthly to the same weights as those in December 1995. Table 3 shows the simulated ex post results for the “out of sample” period between January 1996 and March 2019. Table 3Global Stock-Bond Risk Parity Portfolios (Out Of Sample) Comparing Table 3 to Table 2, several observations are worth highlighting: It is not true that assets have similar Sharpe ratios over longer time frames. Bonds generated higher returns with significantly lower volatility, resulting in a Sharpe ratio of 1.05 in the 1996-2019 period, compared to 0.28 between 1970 and 1995. The Sharpe ratios of stocks in both periods were similar. It is true that RP1 (no leverage) is a better portfolio than 60/40, with a higher Sharpe ratio, even though both portfolios’ Sharpe ratios increased due to the improvement in bonds. More impressively, RP2 (with the same return as 60/40) not only generated 30 basis points of annual outperformance compared to 60/40, it achieved such outperformance with significantly lower volatility. And RP4 (with the same volatility as stocks), also sharply outperformed stocks in terms of both return and volatility. So, the simulated risk-parity portfolios constructed using data from 1970 to 1995 have done well ex post. Upon closer examination, however, two issues arise: Table 4Risk Contribution* Comparison First, as shown in Table 4, the risk-parity portfolio constructed using information as of 1995 turned out not to be risk parity in the subsequent period – because only 12% of the portfolio risk came from bonds, compared to the intended 50%. Granted, 88% from stocks is still less concentrated than the 60/40 portfolio which had 99% risk from equities in the same period, but the ex post risk-parity performance violates the very foundation of the risk-parity principle: true risk diversification. Second, as shown in Chart 3, even though risk-parity portfolios have outperformed their reference portfolios since 1970, the outperformance has not been consistent, with long periods of under- and over-performance. The only consistent observation is that risk parity outperforms in recessions, which is not surprising given its consistently large overweight in bonds. Chart 3Does Risk Parity Outperform In The Long Run? Also, it seems that most of the outperformance came from the period after bond yields peaked in September 1981. Risk parity did poorly during the period from 1978 to 1982, when bond yields increased sharply, while it performed slightly better than the reference portfolios between 1970 and 1978, when rates increased gradually. In reality, even strategic asset allocators do not keep weights constant for such long periods of time. How do variable-weight risk-parity strategies do in different interest-rate environments? Do Rising Yields Hurt Risk Parity? To assess how risk-parity portfolios constructed based on different weighting schemes behave in different interest-rate environments, the simulations in this section use U.S. stocks22 and government bonds23 – only because of their long history that includes both secular rising and falling rate environments.  Variable weights are determined based on moving volatility with different lookback windows. Statistically, the shorter the window length and the more frequent the return measured, the more volatile the volatility estimate is. AQR uses both 1-year24,25 and 3-year26 monthly moving windows, while S&P Dow Jones Risk Parity Indexes are based on a 5-15 year period of a monthly moving window.27 The worst combination for risk parity is rising yields and the underperformance of bonds relative to both cash and stocks. Worryingly, the past three years have been like this. Our research shows that a 1-year monthly moving window is too short, even though it produces higher total returns than longer windows. Chart 4A and 4B show the simulated results of three different moving windows – 36 months, 180 months and 360 months – for two risk-parity portfolios. RP1 is leveraged to have the same volatility as a monthly rebalanced 60/40 U.S. stock-bond portfolio, and RP2 is leveraged to have the same volatility as U.S. stocks. The weights calculated using formula (1) change monthly, based on the corresponding moving window. The following observations are true concerning the choices of our lookback period: Chart 4AU.S. Risk Parity* Vs. 60/40 Chart 4BU.S. Risk Parity* Vs. Stocks The longer the lookback period, the more stable the asset weightings and leverage ratios, and vice versa (bottom three panels in Charts 4A and 4B). This is not specific for risk parity, though. Any approach using historical mean-variance-correlation estimates share this feature. The leverage ratio spikes more often when the window length gets shorter, which may be too uncomfortable for some investors. RP2 has equity weight consistently over 60%, no matter what lookback period is used (this is also true for fixed-weight risk parity). In comparison, the less-leveraged RP1 only briefly assigns higher than 60% to equities when the lookback period is very short (panel 4 in 4A and 4B). In terms of absolute performance from March 1933 to March 2019, the shorter the window length, the better the overall full-period total return (panel 1 in 4A and 4B). However, this outperformance comes with much higher leverage ratios, which may be too high for the majority of investors (panel 5 in 4A and 4B).  In terms of relative performance versus the corresponding reference portfolio, longer window options have not done well overall. Only the shorter window option produced a marginally better relative performance for the full 86-year period (panel 2 in 4A and 4B). However, there are three stages of relative performance: a secular underperformance period from 1950 to 1970, a secular outperformance window from 2000 to July 2016, and a cyclical under- / over-performance period from 1970 to 1999. For the 36-month window, which has a longer history dating back to 1933, it also has a long period of outperformance from 1933 to 1949, as shown in Chart 5. Chart 5Does A Rising Bond Yield Hurt Risk Parity? Risk parity has a heavy weighting in bonds. It is natural to think that underperformance occurs only when rates rise, and vice versa. As shown in Table 5, however, this is true only for three periods. Risk-parity portfolios outperformed from March 1933 to July 1941, and from January 2000 to July 2016 when rates dropped (Table 5 rows 1 and 6). They underperformed from January 1950 to December 1969 when yields rose (row 3). Table 5What Drives Risk Parity Performance? What is puzzling is how risk parity performed in the following three periods: From August 1941 to December 1949, when rates rose slightly yet risk parity outperformed significantly (row 2); From January 1970 to September 1981, when interest rates rose even more than the previous period from 1949 to 1969, but risk parity did not underperform significantly (row 4); From October 1981 to December 1999, when yields dropped more than 900 basis points, yet risk parity did not outperform at all (row 5). Other than interest rates, what are the other forces driving risk parity performance?  A closer examination of Table 5 reveals that the direction of interest-rate movements alone does not fully explain the performance of risk parity relative to its reference portfolio. It is the reason why rates rise or fall, combined with how assets react to those reasons, that determine how risk parity performs. This makes sense because risk parity not only overweights bonds in general, but uses leverage. The worst combination for risk parity is when interest rates rise such that bonds underperform both cash and stocks, as in the period from January 1950 to December 1969 (Table 5 row 3) – because leverage and interest-rate movements both worked against risk parity. This may not sound very encouraging for risk parity going forward, because the current period from July 2016 to March 2019, albeit very short in length, has so far shared similar characteristics to the period from 1949 to 1969 in terms of annualized excess return of stocks and bonds as well as relative performance between stocks and bonds. Table 5 also shows that during the hyper-inflationary period from 1970 to 1981, both stocks and bonds underperformed cash, which also underperformed inflation. Even though risk-parity portfolios performed in line with their reference portfolios, this period was actually the worst for investors because real returns were negative for all three assets. The key to risk parity is to diversify across asset classes that behave differently across different economic regimes such that each asset contributes equally to portfolio risk. So how does diversification across asset classes and geographic regions impact risk parity performance? How To Achieve True Risk Diversification? Commodities outperformed inflation during the hyper-inflationary period from 1970 to 1981. Intuitively, adding commodities to the asset mix would have been beneficial for that period. How about other periods? To assess the impact, we add commodities28 to our two-factor U.S. risk parity and two-factor global risk-parity portfolios to simulate three-factor risk-parity portfolios with two different lookback periods (36 months and 180 months) and three different volatility targets (10%, 12% and 15%). The weight of each asset for the unlevered risk parity portfolio is calculated using the inverse of the volatility (V) of each asset: Wi = (1/Vi) / ((1/Vs +1/Vb +1/Vc)...................(2) Where i stands for s (stocks), b (bonds) and c (commodities). The volatility of the unlevered risk-parity portfolio (URP) in each window period is then calculated as Vurp and the leverage ratio is calculated as Vtarget / Vurp. Chart 6A and 6B compare how the addition of commodities to the asset universe changes the performance of risk parity. For a longer history of performance, we show the simulations with the 36-month moving window. Chart 6ACommodity Impact On U.S. Risk Parity Chart 6BCommodity Impact On Global Risk Parity Overall the addition of commodities has performed in line with the two-asset risk parity portfolios. However, the three-factor risk parity portfolio did significantly outperform the two-factor portfolio before 1990. After more than a decade of ups and downs, relative performance made a strong rebound during the GFC, only to give up all the gains in the next seven years (Charts 6A and 6B, panel 1), coinciding with a sharp change in commodities-stocks correlations (panel 5). A “truly risk-diversified” portfolio constructed using our proprietary optimization algorithm outperforms consistently a risk-parity portfolio based on inverse of volatility. Chart 7Risk Contributions It is worth noting that diversification across asset classes and geographies is not exclusive to risk parity. It is a well-accepted practice in the asset management industry. Panel 4 in both 6A and 6B show that a 50/40/10 stock-bond-commodity portfolio also outperforms or underperforms a 60/40 equity-bond portfolio in line with the movement of relative asset performance. Risk parity, however, amplifies the upside by using leverage and slightly limits downside risk by allocating risk in a more diversified fashion (Chart 7). Chart 7 shows that a conventional portfolio, despite a 50% weight in equities, is dominated by equity risk, while the risk-parity portfolio has much less concentrated risk allocations.  However, the three assets in the risk-parity portfolio do not have an equal share of risk contribution. Why? Because we constructed the risk-parity portfolio using the inverse of volatility according to formula (2). It assigns a higher weight to a lower volatility asset, but does not guarantee equal allocation of risk. How will a more precisely equal risk allocation improve risk-parity performance? We ran another simulation using the same three global assets and a 180-month moving window. However, asset weights were optimized using a proprietary optimization procedure such that each asset contributed equally to total portfolio risk. Chart 8, shows that the optimized risk-parity portfolios have outperformed those constructed by using formula (2), i.e. inverse volatility. Impressively, the outperformances are consistent through time in terms of both returns and Sharpe Ratios (panels 1 and 2). The optimized risk contributions are equally distributed (panel 4) as intended. By contrast, when the weights were constructed using inverse volatility, each asset's contribution to total risk varied considerably (panel 3). This makes sense because the optimization procedure takes into consideration not only volatility but also correlations between assets. Correlation between stocks and bonds, and correlation between stocks and commodities, have both gone through significant changes over time, especially since 2006 when the directions reversed. (Chart 9, panel 5). Consequently, on an unlevered basis, ex ante volatility of the optimized portfolio has turned lower since 2006, resulting in a higher Sharpe ratio (Chart 9, panels 3 and 4). Chart 8True Risk Diversification Works Better Chart 9Why Does True Risk Diversification Work Better?   Even though the returns of the two unlevered portfolios are similar, the optimized portfolio’s lower volatility permits a higher leverage ratio at any given target portfolio volatility, which in turn drives much better returns of the leveraged portfolios (panels 1 and 2). The bottom line is that a “truly risk-diversified” portfolio constructed using our proprietary optimization algorithm does produce better results than a risk-parity portfolio constructed using less risk-diversified approaches, such as the inverse of volatility. It does require more computing power, but this will become much less an issue with technological advancement. Our finding can also be used as a pure alpha overlay strategy. The implementation, though, is out of the scope of this report. Conclusions The key features of a “risk-based” approach is “risk diversification” and the use of leverage. The risk parity approach is one of many investment tools. Like any other investment tool, it has its advantages and limitations. Because of choices in the universe of assets and also portfolio construction methods, not all “risk parity” portfolios are equal. Investors should apply rigorous due diligence before choosing a risk-parity manager. Based on our simulations, we find: Risk parity outperforms in recessions due to its large allocation to bonds. The direction of interest-rate movements alone does not fully determine how risk parity performs. The worst environment for risk parity is the combination of rising yields and the underperformance of bonds relative to both cash and stocks – because both leverage and interest-rate movements work against risk parity. Worryingly, the past three years have been like this, similar to the 1949-1969 period when risk parity would not have performed. Fixed-weight risk-parity portfolios are not truly risk diversified ex post. An inverse volatility approach generates less concentrated risk allocation, but not necessarily equal risk contribution. Risk-parity portfolios constructed with shorter lookback periods outperform those with longer lookback periods if historical volatility estimates are used. Risk-parity portfolios constructed using our proprietary optimization algorithm that truly allocates risks equally to all assets, consistently outperform those constructed using approximation, such as inverse volatility. This finding not only proves that “true risk diversification” works, it can also be used as an alpha overlay strategy for asset allocators.   Xiaoli Tang, Associate Vice President xiaoliT@bcaresearch.com   Footnotes 1      Bridgewater Associates, “The All Weather Story” 2      Bridgewater Associates, “Our Thoughts about Risk Parity and All Weather,” Daily Observations, September 16, 2016. 3      Edward E. Qian, “Risk Parity Fundamentals,” CRC Press, 2016. 4      Sergei Antoshin, Fabio Cortes, Will Kerry and Thomas Piontek, “Volatilities Strike Back,” IMF Blog, dated May 3, 2018. 5      Rachel Fixsen, ”ATP: Rebalancing the risk diet,” IPE Magazine, July/August 2016. 6      “Annual Announcement of Financial Statements 2018,” ATP Group. 7      Jeff Macdonald, “Pension board to consider firing CIO,” The San Diego Union-Tribune, September 18, 2014.   8      Miles Weiss, “AQR Strips ‘Risk Parity’ Name From Mutual Fund After Redemptions,” Bloomberg, December 7, 2018. 9      Cliff Asness, “Liquid Alt Ragnarök?” AQR Alternative Investing, September 7, 2018. 10     Bridgewater Associates, “Our Thoughts about Risk Parity and All Weather,” Daily Observations, September 16, 2016. 11     Edward E. Qian, “Risk Parity Fundamentals,” CRC Press, 2016. 12     Clifford S. Asness, Andrea Frazzini, and Lasse H. Pedersen, “Leverage Aversion and Risk Parity,” Financial Analyst Journal, Jan/Feb 2012. 13    Bridgewater Associates, “Our Thoughts about Risk Parity and All Weather,” Daily Observations, September 16, 2016. 14     Bridgewater Associates, “The All Weather Story” 15     Bridgewater Associates, “The All Weather Story” 16     Clifford S. Asness, Andrea Frazzini, and Lasse H. Pedersen, “Leverage Aversion and Risk Parity,” Financial Analyst Journal, Jan/Feb 2012. 17     Brian Hurst, Bryan Johnson, Yao Hua Ooi, “Understanding Risk Parity,” AQR, Fall 2010. 18     Edward E. Qian, “Risk Parity Fundamentals,” CRC Press, 2016. 19     Bridgewater Associates, “Our Thoughts about Risk Parity and All Weather,” Daily Observations, September 16, 2016. 20       MSCI All Country World Total Return Index in U.S. dollars, unhedged, from December 1987 to now. For back history, we used the MSCI World from December 1969. Prior to December 1969 we used the S&P 500. 21     Bloomberg Barclays (BB) Global Aggregate hedged total return in U.S. dollar from January 1990 to the present. For back history, we used the BB Global Treasury hedged total return in U.S. dollar from January 198, the BB U.S. aggregate total return from January 1976, and the BB U.S. Treasury total return from December 1972. Prior to December 1972 we used our own calculations based on U.S. 10-year government bond yield. 22     MSCI U.S. Total Return Index from December 1969 to the present. Back history was the S&P 500 Total Return Index. 23     Bloomberg Barclays (BB) U.S. Treasury Total Return Index from December 1972. Back history was calculated based on U.S. 10-year government bond yield. 24     Brian Hurst, Bryan Johnson, Yao Hua Ooi, “Understanding Risk Parity,” AQR, Fall 2010. 25     Brian Hurst, Michael, Yao Hua Ooi, “Can Risk Parity Outperform If Yields Rise?,” AQR, July 2013. 26     Clifford S. Asness, Andrea Frazzini, and Lasse H. Pedersen, “Leverage Aversion and Risk Parity,” Financial Analyst Journal, Jan/Feb 2012. 27     https://eu.spindices.com/indices/strategy/sp-risk-parity-index-12-target-volatility-tr 28     GSCI Commodities Total Return Index from December 1969, before which the total return index of the Bloomberg Commodities Index was used.  

The Fed that has adopted an abruptly dovish stance and a recently inverted 10-year/fed funds rate yield curve indicates the market’s expectation that the next Fed move will be a cut, corroborated by elevated probabilities of a cut by December. This has driven a marked increase in client requests on positioning if rates are falling. Accordingly, we have updated our research to answer the question: what sectors perform best when the Fed eases? The results of our analysis of the seven Fed loosening cycles since 1965 are presented in the table below. The sector results are telling: defensives lead the pack in advance of a rate cut as market participants smell trouble and a defensive rotation occurs. The key source of funds in this defensive rotation in advance of a loosening cycle is S&P tech which underperforms early and continues to underperform dramatically through the initial stages of the loosening cycle. While we are not forecasting a cut and BCA’s view remains one of no recession for the coming 12 months, the production of this report may well be early. Nevertheless, its use as a sector positioning/return road map is evergreen; please see Monday’s Special Report for more details. ​​​​​​​

Special Report

Feature Leading indicators of inflation, and hence a hawkish Fed, remain biased to the upside. The S&P 500 is close to all-time highs, the U.S. dollar has been strong this year, and wage growth has been resilient. Almost exactly eight years ago, we published a report examining historical sector performance across the various Fed tightening cycles.1 We now find ourselves on the other side with a Fed that has adopted an abruptly dovish stance and a recently inverted 10-year/fed funds rate yield curve indicating the market’s expectation that the next Fed move will be a cut. Accordingly, we have updated our research to analyze the opposite perspective when rates are falling and answer the question: what sectors perform best when the Fed eases? Such an exercise may seem ill-timed; leading indicators of inflation, and hence a hawkish Fed, remain biased to the upside. The S&P 500 is close to all-time highs, the U.S. dollar has been strong this year, and wage growth has been resilient (Chart 1). Nevertheless, we have been inundated by client requests on this topic and, while we may well be early in its production, its use as a sector positioning/return road map is evergreen and not necessarily to forecast that a Fed cut is nearing. Chart 1Inflation Indicators Still Don’t Point To A Cut The results of our analysis of the seven Fed loosening cycles since 1965 are presented in Table 1. While we highlight the May 1980 iteration as an easing cycle, we have excluded it from our analysis owing to its returns overlap with the March 1981 iteration less than a year later, which offers a cleaner analysis. Table 1Sector Relative Performance And Seven Fed Easing Cycles Still, the sector results are telling: defensives lead the pack in advance of a rate cut as market participants smell trouble and a defensive rotation occurs. Some of the results should be taken with a grain of salt. As shown in Table 1, the broad market delivers significant returns 24 months after an easing cycle begins. However, the last two easing cycles (January 2001 and September 2007) witnessed the S&P returning -37% and -31%, respectively, two years post rate cut. Thus, a rate cut does not signal with certainty a positive two year return. The key source of funds in this defensive rotation in advance of a loosening cycle is S&P tech which underperforms early and continues to underperform dramatically through the initial stages of the loosening cycle. Still, the sector results are telling: defensives lead the pack in advance of a rate cut as market participants smell trouble and a defensive rotation occurs (Chart 2). However, the results are not unambiguous as the rate-sensitive defensive S&P utilities and S&P telecoms indexes both underperform early while S&P consumer staples and S&P health care are the top performers of all sectors prior to, and both one and two years post rate cut (Charts 4 & 5). The key source of funds in this defensive rotation in advance of a loosening cycle is S&P tech which underperforms early and continues to underperform dramatically through the initial stages of the loosening cycle (Chart 3). This is an excellent and consistent leading signal that we are monitoring closely. S&P tech’s deep cyclical peer S&P industrials surprisingly does not show advance warning of a loosening cycle, though persistently underperform once the cycle is underway. Also surprising is S&P energy’s outperformance in the early stages of a lower rate environment. The current implied fed funds probabilities are roughly 50-50 for a rate cut at the Fed’s December 2019 meeting and move increasingly towards a rate cut thereafter. While we are not forecasting a cut and BCA’s view remains one of no recession for the coming 12 months, were a Fed cut to materialize, our barbell portfolio approach will likely be able to absorb the Fed shock. We highlight our overweight recommendation on S&P consumer staples and S&P energy along with our neutral recommendation on S&P health care as sector winners in an easing cycle and our underweight recommendation for S&P consumer discretionary as a sector laggard as rates fall. We further note our neutral recommendation on S&P tech. The reference charts below show individual sector relative performance charts along with the fed funds rate (shaded areas depict the initial Fed rate cut).   Chris Bowes, Associate Editor U.S. Equity Strategy ChrisB@bcaresearch.com Anastasios Avgeriou, U.S. Equity Strategist anastasios@bcaresearch.com   Chart 6 Chart 7 Chart 8 Chart 9 Chart 10 Chart 11 Chart 12 Chart 13 Chart 14 Chart 15   Footnotes 1      Please see BCA U.S. Equity Strategy Special Report, “Sector Performance And Fed Tightening Cycles: An Historical Roadmap” dated April 25, 2011, available at uses.bcaresearch.com.

Special Report

Feature The U.S.-China trade talks have not yet collapsed but they appear to be reaching a “make it or break it” moment. President Donald Trump renewed his threat of heightening tariffs on Chinese imports on May 5, in the interim between two weeks of shuttle diplomacy in Beijing and next in Washington that have been billed as the final round of negotiations. Chinese officials responded to Trump’s new tariff remarks by threatening to pull out of the talks. The status of the Chinese delegation due in Washington this week is unclear as we go to press. Specifically, President Trump has claimed that he would increase the current 10% tariff rate on $200 billion worth of Chinese imports to 25%, a move that was originally due on March 1, but was delayed to extend the talks and seek a better agreement. Trump also threatened to raise tariffs on the remaining $325 billion of Chinese imports that are so far untouched. This is the most significant escalation in rhetoric since before the tariff truce agreed on December 1 between Trump and Chinese President Xi Jinping in Buenos Aires. True, the threat to increase the tariffs is a last-minute pressure tactic tied to the administration’s attempt to make this week “the final week” of the talks. American advisers have said that at the end of these two weeks they would make a recommendation to the president either to sign a deal or walk away. For this reason, it is not certain that Trump will follow through with the increase. However, we consider the threat credible. The costs of trade war are not prohibitive to the U.S. or China considering the strategic interests at stake in their great power competition (Chart 1). And since December 1, we have argued that a relapse into trade war and rising tariffs was a substantial risk at 30% odds; this threat increases those odds. Chart 1The Era Of U.S.-China Detente Is Over Talks have been deteriorating for the past month at least. First, the trade grievances at the root of the trade war with China – namely corporate espionage, hacking, forced technology transfer, intellectual property theft, and the American-allied restrictions on Chinese telecoms firm Huawei – were always going to be extremely difficult to settle. These are apparently weighing on the ability of Washington and Beijing to close an agreement. Second, tensions have recently flared across the entire range of U.S.-China strategic disagreements, including most importantly North Korea and Iran. In late April, the U.S. demanded that China halt all imports of Iranian oil by the end of May in order to avoid secondary sanctions that, in theory, could affect China’s central bank and other banks. Meanwhile North Korea has conducted two minor but provocative weapon tests (including short-range missiles on May 4) since the failed summit between Trump and Kim Jong Un in Hanoi. Washington expects Beijing to keep North Korea in check and involved in diplomacy as part of the broader strategic negotiation. Taiwan and the South China Sea are also simmering due to U.S.-Taiwan diplomacy and arms sales, Chinese military drills, and the U.S. decision to treat China’s “maritime militia” like its navy. Trump’s latest threat reduces the chances of an extension of the talks beyond June to 10%, while raising the odds of a collapse in talks and escalation of trade war to 40%. As a result of these developments, and the dragging on of talks, we put the odds of a trade deal by the end of June at 50% in our April 10 report. Trump’s latest threat reduces the chances of an extension of the talks beyond June to 10%, while raising the odds of a collapse in talks and escalation of trade war to 40% (Table 1). Table 1Updated Trade War Probabilities (May 2019) From the Chinese point of view, Trump’s threat makes it harder to clinch a deal. Trump’s use of sweeping, unilateral tariffs on national security grounds has forced China into an awkward position. It is politically and ideologically toxic for Beijing to appear to capitulate to coercion, i.e. nineteenth-century-style tactics of gunboat diplomacy and western imperialism. The tariff truce in Buenos Aires minimized the appearance that China is negotiating under duress, giving Xi Jinping the ability to negotiate and make concessions without losing face. While China is in the weaker position economically, and therefore would prefer a deal, it will batten down the hatches and fight a trade war if forced to do so. The risk of other executive decisions disruptive to markets is going up. The implication for investors is threefold. First, the USD and U.S. equities will continue to outperform global counterparts as trade policy uncertainty shoots back up (Chart 2). The American economy is more insulated from global trade and the dollar is counter-cyclical. But as U.S. equities have rallied and volatility will go up, U.S. equities may simply fall less rapidly than Chinese and others. Chart 2U.S. Will Outperform On Rising Trade Uncertainty Second, our view that China’s economic stimulus will surprise to the upside is reinforced by this development, as Beijing cannot afford to withdraw or pause stimulus when it still faces such a severe external risk to its manufacturing sector and employment (Chart 3). This will counteract the negative impact to global sentiment and manufacturing expected from any additional tariffs, creating more volatility in commodity and emerging market assets. Third, as we recognized in the case of Trump’s renewed “maximum pressure” tactic on Iran, the president is apparently not concerned with minimizing risks to the economy ahead of the 2020 election. His risk appetite remains voracious. Therefore the risk of other executive decisions disruptive to markets is going up. For instance, our 35% chance that Trump will impose Section 232 tariffs on auto and auto part imports, particularly from Europe, is rising toward 50% (Chart 4). Chart 3China Cannot Afford to Withhold Stimulus   Bottom Line: The odds of a re-escalation of the trade war have risen to 40%. American equities should outperform global, while safe-haven assets, such as a portfolio hedge of Swiss bonds and gold, should catch a bid. We are closing out our long copper trade for a loss of 3.58% as well as our long Chinese equities ex-tech trade for a gain of 6.59%. Matt Gertken, Geopolitical Strategist mattg@bcaresearch.com

Feature The U.S.-China trade talks have not yet collapsed but they appear to be reaching a “make it or break it” moment. President Donald Trump renewed his threat of heightening tariffs on Chinese imports on May 5, in the interim between two weeks of shuttle diplomacy in Beijing and next in Washington that have been billed as the final round of negotiations. Chinese officials responded to Trump’s new tariff remarks by threatening to pull out of the talks. The status of the Chinese delegation due in Washington this week is unclear as we go to press. Specifically, President Trump has claimed that he would increase the current 10% tariff rate on $200 billion worth of Chinese imports to 25%, a move that was originally due on March 1, but was delayed to extend the talks and seek a better agreement. Trump also threatened to raise tariffs on the remaining $325 billion of Chinese imports that are so far untouched. This is the most significant escalation in rhetoric since before the tariff truce agreed on December 1 between Trump and Chinese President Xi Jinping in Buenos Aires. True, the threat to increase the tariffs is a last-minute pressure tactic tied to the administration’s attempt to make this week “the final week” of the talks. American advisers have said that at the end of these two weeks they would make a recommendation to the president either to sign a deal or walk away. For this reason, it is not certain that Trump will follow through with the increase. However, we consider the threat credible. The costs of trade war are not prohibitive to the U.S. or China considering the strategic interests at stake in their great power competition (Chart 1). And since December 1, we have argued that a relapse into trade war and rising tariffs was a substantial risk at 30% odds; this threat increases those odds. Chart 1The Era Of U.S.-China Detente Is Over Talks have been deteriorating for the past month at least. First, the trade grievances at the root of the trade war with China – namely corporate espionage, hacking, forced technology transfer, intellectual property theft, and the American-allied restrictions on Chinese telecoms firm Huawei – were always going to be extremely difficult to settle. These are apparently weighing on the ability of Washington and Beijing to close an agreement. Second, tensions have recently flared across the entire range of U.S.-China strategic disagreements, including most importantly North Korea and Iran. In late April, the U.S. demanded that China halt all imports of Iranian oil by the end of May in order to avoid secondary sanctions that, in theory, could affect China’s central bank and other banks. Meanwhile North Korea has conducted two minor but provocative weapon tests (including short-range missiles on May 4) since the failed summit between Trump and Kim Jong Un in Hanoi. Washington expects Beijing to keep North Korea in check and involved in diplomacy as part of the broader strategic negotiation. Taiwan and the South China Sea are also simmering due to U.S.-Taiwan diplomacy and arms sales, Chinese military drills, and the U.S. decision to treat China’s “maritime militia” like its navy. Trump’s latest threat reduces the chances of an extension of the talks beyond June to 10%, while raising the odds of a collapse in talks and escalation of trade war to 40%. As a result of these developments, and the dragging on of talks, we put the odds of a trade deal by the end of June at 50% in our April 10 report. Trump’s latest threat reduces the chances of an extension of the talks beyond June to 10%, while raising the odds of a collapse in talks and escalation of trade war to 40% (Table 1). Table 1Updated Trade War Probabilities (May 2019) From the Chinese point of view, Trump’s threat makes it harder to clinch a deal. Trump’s use of sweeping, unilateral tariffs on national security grounds has forced China into an awkward position. It is politically and ideologically toxic for Beijing to appear to capitulate to coercion, i.e. nineteenth-century-style tactics of gunboat diplomacy and western imperialism. The tariff truce in Buenos Aires minimized the appearance that China is negotiating under duress, giving Xi Jinping the ability to negotiate and make concessions without losing face. While China is in the weaker position economically, and therefore would prefer a deal, it will batten down the hatches and fight a trade war if forced to do so. The risk of other executive decisions disruptive to markets is going up. The implication for investors is threefold. First, the USD and U.S. equities will continue to outperform global counterparts as trade policy uncertainty shoots back up (Chart 2). The American economy is more insulated from global trade and the dollar is counter-cyclical. But as U.S. equities have rallied and volatility will go up, U.S. equities may simply fall less rapidly than Chinese and others. Chart 2U.S. Will Outperform On Rising Trade Uncertainty Second, our view that China’s economic stimulus will surprise to the upside is reinforced by this development, as Beijing cannot afford to withdraw or pause stimulus when it still faces such a severe external risk to its manufacturing sector and employment (Chart 3). This will counteract the negative impact to global sentiment and manufacturing expected from any additional tariffs, creating more volatility in commodity and emerging market assets. Third, as we recognized in the case of Trump’s renewed “maximum pressure” tactic on Iran, the president is apparently not concerned with minimizing risks to the economy ahead of the 2020 election. His risk appetite remains voracious. Therefore the risk of other executive decisions disruptive to markets is going up. For instance, our 35% chance that Trump will impose Section 232 tariffs on auto and auto part imports, particularly from Europe, is rising toward 50% (Chart 4). Chart 3China Cannot Afford to Withhold Stimulus   Bottom Line: The odds of a re-escalation of the trade war have risen to 40%. American equities should outperform global, while safe-haven assets, such as a portfolio hedge of Swiss bonds and gold, should catch a bid. We are closing out our long copper trade for a loss of 3.58% as well as our long Chinese equities ex-tech trade for a gain of 6.59%. Matt Gertken, Geopolitical Strategist mattg@bcaresearch.com

Indonesian financial assets have benefited from the Federal Reserve’s dovish turn and corresponding fall in U.S. bond yields (Chart I-1, top panel). Moreover, the market is cheering President Joko Widodo’s lead in the presidential vote tally. Yet investors are ignoring the budding weakness in industrial metals prices, which has historically been an important driver of Indonesia’s exchange rate (Chart I-1, middle panel). Going forward, the Indonesian currency, equities and local currency bonds all remain vulnerable: Falling global growth in general and Chinese imports in particular will intensify Indonesia’s exports contraction and worsen the country’s already wide current account deficit. In turn, the latter will induce currency depreciation, which will then lead to higher interbank rates (Chart I-2). Chart I-1Global Growth Matters For Indonesian Markets Chart I-2Falling Current Account Deficit = Higher Local Rates Upward pressure on local interbank rates will cause a slowdown in domestic private loan growth.   The Indonesian central bank – Bank Indonesia (BI) – has been attempting to lower interbank rates, which have been hovering above the central bank's policy rate (Chart I-3). To achieve this, the central bank has substantially increased excess reserves in the banking system (Chart I-4). It has done so by purchasing central bank certificates from commercial banks, conducting foreign exchange swaps and providing repo lending. Chart I-3A Sign Of Liquidity Strains Chart I-4Bank Indonesia Is Injecting Liquidity   Yet by expanding banking system liquidity so aggressively, BI risks renewed currency depreciation. Like any central bank in a country with an open capital account, BI cannot expect to have full control over the exchange rate while simultaneously targeting local interest rates. The Impossibly Trinity dilemma dictates that a central bank needs to choose between controlling the two. Therefore, if BI continues to inject local currency liquidity to cap or bring down interest rates (interbank rates), the resulting excess liquidity could encourage and facilitate speculation against the rupiah. Scratching below the surface, the recent strong outperformance of Indonesian equities has been entirely due to the surge in the country’s bank share prices (Chart I-5, top panel). Remarkably, the performance of Indonesian non-financial as well as small-cap stocks has been especially dismal (Chart I-5, middle and bottom panels). This is an upshot of poor profitability among Indonesia’s non-financial listed companies (Chart I-6). Chart I-5Indonesian Bank Stocks Are The Only Outperformers Chart I-6Falling Non-Financial Corporate Profitability Furthermore, deteriorating financial health of non-financial corporates, especially small companies, will lead to higher NPLs on banks’ books. Notably, Indonesian banks are more heavily exposed to businesses than to households. As NPLs rise anew, Indonesian commercial banks will need to lift their bad-loan provisioning levels, generating a major profit relapse (Chart I-7). Importantly, Indonesian commercial banks have been boosting their profits by reducing NPL provisions since early 2018. Reversing this will materially affect their earnings. Chart I-7Indonesian Bank Share Prices Are Vulnerable Additionally, bank stocks are vulnerable due to falling net interest income margins. Moreover, their share prices are overbought and not cheap. To be clear, we are not negative on Indonesia’s structural outlook. The above-mentioned alarms are more near-to-medium terms issues. Still, foreign ownership of local currency bonds and stocks – at 38% each – are high, and could be a major source of potential outflows if the rupiah depreciates. This would cause Indonesian stocks and local currency bonds to sell off severely. Bottom Line: The global growth slowdown/commodities downturn and the U.S. dollar upturn are not yet over. Consequently, foreign flows into EM will diminish, which will be particularly negative for Indonesian financial markets. We recommend investors continue underweighting Indonesian equities and avoid Indonesian local currency bonds for now. We continue to recommend a short position in the IDR versus USD. Ayman Kawtharani, Associate Editor ayman@bcaresearch.com

Highlights In Indonesia, investors are ignoring the weakness in global growth, which is an important driver of the country’s financial markets. The Indonesian currency, equities and local currency bonds all remain vulnerable. We continue to recommend underweighting Indonesian assets for now. In Turkey, additional adjustments in the exchange rate and interest rates are unavoidable. Stay put/underweight Turkish financial markets. In the UAE, the economy is set to improve marginally this year. We recommend overweighting UAE equities and corporate spreads within their respective EM portfolios. Feature Indonesia: The Currency And Bank Stocks Are At Risk  Indonesian financial assets have benefited from the Federal Reserve’s dovish turn and corresponding fall in U.S. bond yields (Chart I-1, top panel). Moreover, the market is cheering President Joko Widodo’s lead in the presidential vote tally. Yet investors are ignoring the budding weakness in industrial metals prices, which has historically been an important driver of Indonesia’s exchange rate (Chart I-1, middle panel). Going forward, the Indonesian currency, equities and local currency bonds all remain vulnerable: Falling global growth in general and Chinese imports in particular will intensify Indonesia’s exports contraction and worsen the country’s already wide current account deficit. In turn, the latter will induce currency depreciation, which will then lead to higher interbank rates (Chart I-2). Chart I-1Global Growth Matters For Indonesian Markets Chart I-2Falling Current Account Deficit = Higher Local Rates Upward pressure on local interbank rates will cause a slowdown in domestic private loan growth.   The Indonesian central bank – Bank Indonesia (BI) – has been attempting to lower interbank rates, which have been hovering above the central bank's policy rate (Chart I-3). To achieve this, the central bank has substantially increased excess reserves in the banking system (Chart I-4). It has done so by purchasing central bank certificates from commercial banks, conducting foreign exchange swaps and providing repo lending. Chart I-3A Sign Of Liquidity Strains Chart I-4Bank Indonesia Is Injecting Liquidity   Yet by expanding banking system liquidity so aggressively, BI risks renewed currency depreciation. Like any central bank in a country with an open capital account, BI cannot expect to have full control over the exchange rate while simultaneously targeting local interest rates. The Impossibly Trinity dilemma dictates that a central bank needs to choose between controlling the two. Yet investors are ignoring the budding weakness in industrial metals prices, which has historically been an important driver of Indonesia’s exchange rate. Therefore, if BI continues to inject local currency liquidity to cap or bring down interest rates (interbank rates), the resulting excess liquidity could encourage and facilitate speculation against the rupiah. Scratching below the surface, the recent strong outperformance of Indonesian equities has been entirely due to the surge in the country’s bank share prices (Chart I-5, top panel). Remarkably, the performance of Indonesian non-financial as well as small-cap stocks has been especially dismal (Chart I-5, middle and bottom panels). This is an upshot of poor profitability among Indonesia’s non-financial listed companies (Chart I-6). Chart I-5Indonesian Bank Stocks Are The Only Outperformers Chart I-6Falling Non-Financial Corporate Profitability Furthermore, deteriorating financial health of non-financial corporates, especially small companies, will lead to higher NPLs on banks’ books. Notably, Indonesian banks are more heavily exposed to businesses than to households. As NPLs rise anew, Indonesian commercial banks will need to lift their bad-loan provisioning levels, generating a major profit relapse (Chart I-7). Importantly, Indonesian commercial banks have been boosting their profits by reducing NPL provisions since early 2018. Reversing this will materially affect their earnings. Chart I-7Indonesian Bank Share Prices Are Vulnerable Additionally, bank stocks are vulnerable due to falling net interest income margins. Moreover, their share prices are overbought and not cheap. To be clear, we are not negative on Indonesia’s structural outlook. The above-mentioned alarms are more near-to-medium terms issues. Still, foreign ownership of local currency bonds and stocks – at 38% each – are high, and could be a major source of potential outflows if the rupiah depreciates. This would cause Indonesian stocks and local currency bonds to sell off severely. Bottom Line: The global growth slowdown/commodities downturn and the U.S. dollar upturn are not yet over. Consequently, foreign flows into EM will diminish, which will be particularly negative for Indonesian financial markets. We recommend investors continue underweighting Indonesian equities and avoid Indonesian local currency bonds for now. We continue to recommend a short position in the IDR versus USD. Ayman Kawtharani, Associate Editor ayman@bcaresearch.com Turkey’s Foreign Debt Bubble: The Worst Is Not Yet Behind Us Turkish financial assets, and the currency especially, will remain under selling pressure in the coming months. Additional adjustments in the exchange rate and interest rates - as well as in the real economy and current account balance - appear unavoidable. The key imbalance remains the gap between foreign debt obligations (FDOs) and the availability of foreign currency to meet these debt obligations. Turkey’s FDOs in 2019 are equivalent to $180 billion (Chart II-1). FDOs measure the sum of short-term claims, interest payments and amortization over the next 12 months. This consists of $15 billion in interest payments, $65 billion in debt amortization and $100 billion in maturing short-term (under one year) claims. In theory, these debt obligations can either be rolled over, or the nation should generate current account and capital account surpluses and use these surpluses to pay down FDOs. Even though the current account deficit is shrinking, it is still in a deficit of $18 billion. Net FDI inflows remain weak at US$10 billion. Hence, it appears that Turkey’s only options are either to roll over maturing foreign currency debt or to lure foreign investors into local currency assets and use the surplus in net portfolio inflows to meet these FDOs. The central bank’s foreign currency reserves excluding both commercial banks’ deposits at the Central Bank of Turkey and FX swaps now stand at $13 billion. However, due to a lack of credibility in the Turkish government’s macro policies - in addition to the ongoing deep economic recession and heightened financial market volatility - external creditors will be unwilling to roll over the debt. In fact, net portfolio flows into government debt and equities have tumbled for the same reason. Typically, when foreign funding dries up temporarily, a country can use its foreign exchange reserves to meet its FDOs. However, Turkey’s foreign exchange reserves have already plummeted to extremely low levels (Chart II-2). The central bank’s foreign currency reserves excluding both commercial banks’ deposits at the Central Bank of Turkey and FX swaps now stand at $13 billion. This is negligible compared with the $180 billion FDO figure due in 2019. Chart II-1Turkey: A Large Foreign Debt Servicing Burden Chart II-2Foreign Exchange Reserves Are Too Small   The recent plunge in the central bank’s net foreign exchange reserves excluding swaps (i.e. net international reserves) has put many pertinent metrics at record lows. In particular, net international reserves are at a precarious level relative to both total imports and external debt (Chart II-3). Finally, the net international reserves-to-broad money supply ratio has fallen to 7% (from 15% in 2014) despite the fact that the massive lira depreciation reduced the U.S. dollar measure of broad money supply (Chart II-4). Chart II-3FX Reserves Do Not Cover Imports Or External Debt Chart II-4Low Coverage Of Broad Money By International Reserves The currency will have to depreciate further and interest rates will have to move higher to shrink domestic demand/imports more. This is needed to generate a current account surplus that could be used to service FDOs, or that otherwise entices foreign creditors to be willing to roll over foreign debt or invest in Turkey. Finally, while the adjustment in the real economy is advanced, it is unlikely to be over, due to the large foreign debt bubble. Importantly, with large foreign and local currency debt obligations coming due for both companies and households - in addition to the deterioration in economic activity and higher interest rates - NPLs are bound to rise (Chart II-5). This is especially likely to occur because a lot of borrowing has been used in the property market both for construction and purchases. Notably, real estate volumes are shrinking, and prices are deflating in real terms (Chart II-6). Chart II-5NPLs Will Rise A Lot Chart II-6Turkey: Real Estate Is In Free Fall     Bottom Line: The macro adjustment in Turkey is not yet complete. The country still lacks foreign currency supply to service its enormous 2019 FDOs. Further currency depreciation and higher interest rates are required to depress domestic demand/imports and push the current account into surplus. Stay put / underweight Turkish financial markets. The authorities are becoming desperate, and the odds of capital control enforcement are not negligible. While such an outcome is not possible to forecast with any certainty or time frame, investors should consider this very real risk. Andrija Vesic, Research Analyst andrijav@bcaresearch.com Overweight UAE Equities And Corporate Bonds Over the next six to nine months, we believe both UAE equities and corporate spreads will outperform their respective emerging market (EM) benchmarks. The UAE economy is set to improve marginally this year (Chart III-1). It will benefit from expansionary fiscal policy, rising oil output, a buoyant tourism sector, a resilient banking sector and less of a drag from the real estate sector. First, sizable fiscal spending will lead to rising non-oil economic growth. The UAE’s federal budget spending for 2019 will increase by 17.3% from a year ago, much higher than the 5.5% year-on-year growth in 2018. Second, UAE oil output could increase by 15% later this year from current levels (Chart III-2). The U.S. announced on April 22 that all Iran sanction waivers will not be extended beyond the early-May expiration date. The U.S. administration also stated that it has secured pledges from Saudi Arabia and the UAE to increase their oil production in order to offset disrupted supply from Iran. Rising oil output will mitigate the negative impact of potentially lower oil prices on the UAE’s economy. Chart III-1Improving UAE Economy Chart III-2Rising Oil Output   Third, the outlook for the tourism sector is also positive. The number of tourists is set to rise as Expo 2020 approaches. The government is targeting 20 million visitors in 2020, 26% higher than last year’s levels. The UAE is building theme parks, museums, hotels and infrastructure to attract more tourists. The UAE economy is set to improve marginally this year. Fourth, the UAE’s banking sector will enjoy rising credit growth, robust profitability and improved asset quality this year. The banking system has been in consolidation mode since January 2016, with a 15% reduction in branches and a 14% drop in the number of employees. This has improved the banking sector’s profitability by cutting operating costs and increasing efficiency. The improving growth outlook will lift credit growth. The central bank’s most recent Credit Sentiment Survey suggests banks’ lending standards for both business and personal loans are loosening (Chart III-3). In addition, UAE banks enjoy large capital buffers. Despite rising non-performing loans (Chart III-4), UAE banks still reported a Tier-1 capital adequacy ratio of 17% as of December 2018. Chart III-3Credit Growth Is Likely To Increase Chart III-4Rising NPLs, But Still Large Capital Buffers   Lastly, the real estate markets in both Dubai and Abu Dhabi have suffered from oversupply (from both mushrooming supply and weaker demand) over the past several years. Property prices have already fallen over 20% in both Dubai and Abu Dhabi from their 2014 peaks (Chart III-5). Odds are high that the most dangerous phase of the property market downturn is behind us. Chart III-5Real Estate Adjustment Is Advanced In addition, the government’s efforts to attract people to stay in the country longer will somewhat offset the ongoing exodus of expatriates. Last May, the UAE introduced a new visa system that will allow investors, innovators and talented specialists in the medical, scientific, research and technical fields to stay in the country for up to 10 years. Overall, a potential bottom in property demand and restrained supply will likely make the real estate sector less of a drag on this bourse this year. Finally, the authorities are also more open to increasing the foreign ownership cap in the banking sector, albeit not up to 100%. For example, in early April, the largest UAE lender – First Abu Dhabi Bank – obtained regulatory approval to increase its foreign ownership limit to 40% from 25%. This has boosted foreign equity purchases and has supported the equity index. Bottom Line: We recommend an overweight position in UAE equities within an EM portfolio this year (Chart III-6). For fixed income investors, we recommend overweighting UAE corporate credit in an EM corporate credit portfolio. UAE corporate credit is a lower beta market and will outperform as EM corporate spreads widen (Chart III-7). Most UAE-dollar corporate bonds have been issued by banks. Banks in the UAE do not suffer from structural overhangs, and the cyclical downturn in the property market is well advanced. This is why they have been, and will remain, a lower beta sector within an EM corporate credit portfolio. Chart III-6Overweight UAE Equities Within An EM Portfolio Chart III-7UAE Corporate Credit Will Likely Outperform EM Benchmark   Ellen JingYuan He, Associate Vice President ellenj@bcaresearch.com Footnotes Equity Recommendations Fixed-Income, Credit And Currency Recommendations

Overweight The S&P tech hardware, storage & peripherals (THSP) index was cheering yesterday as index heavyweight Apple reported results that, while not strong, were better than the market had feared after the terrible Q4 print. Importantly, management commented that the rate of decline in China had eased significantly over the course of the quarter while services revenues hit a new record. Perhaps more important to equity investors was the $27 billion the company returned to shareholders in Q1, the authorization of another $75 billion for share repurchases and a 5% increase in the dividend. In the context of the still-pristine sector balance sheets (bottom panel), further shareholder friendly actions seem likely. Nevertheless, while sector valuations have bounced off the recent relative lows, the S&P THSP index continues to trade at a wide (though shrinking) discount to the broad market (second panel). We continue to find this discount excessive in anticipation of a sector rerating. Bottom Line: Troughing results in China, progress in services and a surge in return of capital to shareholders all point to more gains for the S&P THSP index; stay overweight. The ticker symbols for the stocks in the S&P THSP index are: BLBG: S5CMPE - HPQ, WDC, STX, XRX, AAPL, HPE, NTAP.

Highlights Open an equity market relative overweight to Europe versus China. Upgrade Denmark to neutral. Downgrade the Netherlands to underweight. Maintain Switzerland at overweight. With the Euro Stoxx 50 now up almost 20 percent from its January 3 low, the majority of this year’s absolute gains have already been made. Core euro area bond yields will edge modestly higher… …and EUR/USD will appreciate, as the backward-looking data on which the ECB depends catches up with the more perky real-time economic data.   Feature Vertical charts scare us, as we contemplate falling over the edge. But they also excite us, as we contemplate a lucrative investment opportunity. Right now, the vertical chart that is causing us palpitations is technology versus healthcare (Chart of the Week).  Chart of the WeekTechnology Versus Healthcare Has Gone Vertical! The technology versus healthcare sector pair is critical, because it looms large in several stock markets’ ‘fingerprint’ sector skews. Meaning that the technology versus healthcare relative performance has unavoidable consequences for regional and country stock market allocation (Chart I-2 and Chart I-3). The technology versus healthcare sector pair is critical, because it looms large in several stock markets’ ‘fingerprint’ sector skews. Chart I-2When Technology Underperforms Healthcare, Netherlands Underperforms Switzerland Chart I-3When Technology Underperforms Healthcare, China Underperforms Switzerland Specifically, from a European stock market perspective, the Netherlands is overweight technology while Switzerland and Denmark are both overweight healthcare. Further afield, the U.S. is overweight technology while China is both overweight technology and underweight healthcare. Explaining Verticality And The Subsequent Fall What creates vertical charts? To answer the question, let’s turn it on its head: what prevents vertical charts? The answer is: the presence of value investors. In a healthy market, a cohort of value investors will sit on the side lines and only transact with the marginal seller when the price falls to a semblance of value. In other words, the value sensitive investors help to set the price, preventing verticality. But if the value sensitive cohort switches out of character to join a strong uptrend, the cohort will suddenly become value insensitive. In this case, the marginal seller will set the price higher and the formerly uninterested value sensitive buyer will now buy at the higher price. The market has morphed into a trend-following market. As more of the value cohort switch sides, the process adds rocket fuel to the rally. Driven by the ‘fear of missing out’ the marginal buyer will buy at larger and larger price increments, and the chart becomes vertical. What triggers the subsequent fall? When all of the value cohort have joined the uptrend, the fuel has run out: the marginal seller will no longer find a willing marginal buyer at the elevated price. At this critical point, one of two things will happen. Either: a completely new cohort of even deeper value investors will switch out of character and provide new fuel to the trend, allowing it to continue. Or: the deep value investors will stay true to character and will only deal with the marginal seller when the price falls, perhaps sharply, to a semblance of deep value. Technology versus healthcare is now at this critical technical point at which the probability of trend-reversal has significantly increased. Both the theoretical and empirical evidence suggests that at this critical point, the probability of trend-continuation decreases to about a third and the probability of a trend-reversal increases to about two-thirds. Technology versus healthcare is now at this critical technical point at which the probability of trend-reversal has significantly increased (Chart I-4). Chart I-4Technology Versus Healthcare: The Probability Of A Trend-Reversal Is High Therefore, on a tactical horizon, it is now appropriate to underweight technology versus healthcare – which, to reiterate, carries unavoidable consequences for country and regional stock market allocation: Open an overweight to Europe versus China. Upgrade Denmark to neutral. Downgrade the Netherlands to underweight. Maintain Switzerland at overweight. Distinguishing Between Valuation And Growth Is Extremely Difficult There is another problem for value investors. Over short periods – meaning less than a year – it is very difficult, if not impossible, to decompose a price return into its two components: the component coming from the change in valuation and the component coming from the change in earnings growth expectations. A stock market’s actual earnings are highly sensitive to small changes in economic growth. This is universally the case but is especially true in Europe, because the European stock market’s skew towards growth-sensitive cyclicals gives it a very high operational leverage to GDP growth: a seemingly minor 0.5 percent change in economic growth translates into a major 25 percent change in stock market earnings growth (Chart I-5). The slightest improvement in economic growth expectations causes the market to upgrade its forecasts for earnings very sharply. Chart I-5A Minor Upgrade To Economic Growth = A Major Upgrade To Profits Growth Given this very high operational leverage, the slightest improvement in economic growth expectations causes the market to upgrade its forecasts for earnings very sharply. Which of course lifts the market’s price, P, very sharply. In contrast, equity analysts’ forecasts for earnings, which drive the market’s ‘official’ forward earnings, E, adjust much more slowly. As my colleague, Chris Bowes explains: “analysts get married to a view and usually require overwhelming evidence to materially change it.” The upshot is that the P rises very sharply but the official forward E does not, meaning that the official forward P/E also rises very sharply. This gives the impression that the move is mostly valuation driven, but the truth is that the move is mostly earnings growth driven. In a similar vein, when central banks guide interest rates lower, how much of the equity market’s move is due to a higher valuation, and how much is due to improved prospects for economic growth resulting from the central bank policy change? Over relatively short periods of time, it is extremely difficult to tell. All of which provides an important lesson: over short periods, do not focus on separately forecasting the valuation change and earnings growth change of a stock market. Much better to forecast the stock market price directly, by focussing on the two main things which will drive it: changes to central bank policy, and changes to short-term real-time economic growth. Focus On Central Banks And Short-Term Economic Growth Central bank policy now ‘depends’ on relatively longer-term changes (say, year-on-year) in backward-looking data, most notably the consumer price index. Whereas the stock market’s earnings growth expectations take their cue from shorter-term changes in real-time economic indicators (Chart I-6). Chart I-6Quarter-On-Quarter Growth Is Rebounding Hence, the ‘sweet spot’ for equity markets is when, in simple terms, year-on-year CPI inflation is decelerating, implying central banks will become more dovish, while quarter-on-quarter economic growth is accelerating, implying the market will upgrade earnings growth (Chart I-7). The stock market’s earnings growth expectations take their cue from shorter-term changes in real-time economic indicators. The ‘weak spot’ for equity markets is the exact opposite, when year-on-year CPI inflation is accelerating, implying central banks will become less dovish, while quarter-on-quarter economic growth is decelerating, implying the market will downgrade earnings growth. As 2019 progresses, our high-conviction prediction is that equity markets will move from a sweet spot to a weak spot. With the Euro Stoxx 50 now up almost 20 percent from its January 3 low, it implies that the majority of 2019’s gains have already been made in the first four months of the year – and the market is unlikely to be significantly higher at the end of the year. Compared to the equity market, the bond, interest rate, and currency markets are – almost by definition – much more dependent on central banks’ lagging reaction functions than on real-time growth. Which solves the mystery as to why bond yields are close to new lows while equity markets are close to new highs. It also solves the mystery as to why EUR/USD has lagged the very clear recovery in euro area real-time growth and in euro area stock markets (Chart I-8). Central banks are following lagging indicators. Chart I-7Stock Markets Take Their Cue from Real-Time Indicators Chart I-8Central Banks Are Following Lagging Indicators, Stock Markets Are Following Real-Time Indicators But as the backward-looking data, on which the ECB depends, catches up with the more perky real-time data, core euro area bond yields will edge modestly higher, and EUR/USD will gently appreciate. Next week, in lieu of the usual weekly report, I will be giving this quarter’s webcast titled ‘From Sweet Spot to Weak Spot?’ live on Wednesday May 8 at 10.00 AM EDT (3.00 PM BST, 4.00 PM CEST, 10.00 PM HKT). Through a series of key charts, the webcast will reveal the prospects and opportunities for all asset-classes through the remainder of 2019. At the end of the webcast, I will also unveil a brand new investment recommendation. So don’t miss it! Fractal Trading System* Supporting the arguments in the main body of this report, fractal analysis suggests that the recent rally in China’s stock market is at a technical point that has reliably signaled previous major reversals. Accordingly, this week’s recommended trade is a stock market pair trade, short China versus Japan. Set the profit target at 2.5 percent with a symmetrical stop-loss. We now have six open positions. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment’s fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-9Short China Vs. Japan   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 Recommendations Asset Allocation Equity Regional and Country Allocation Equity Sector Allocation Bond and Interest Rate Allocation Currency and Other Allocation Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch - Interest Rate Expectations    

Highlights The March data brought the first signs of a stabilization in China’s “hard” economic data, albeit from a weak level. The April PMIs disappointed, but they remained in expansionary territory; this is in addition to a continued significant improvement in the trade-related subcomponents of the official survey. Chinese credit growth is unlikely to relapse over the coming year, despite recent investor concerns that Chinese policymakers may dial back their stimulus efforts. The pace of growth may moderate, but halting the uptrend in growth this year would constitute a major policy mistake that we do not expect. Chinese stocks may trend flat-to-down in the very near term as investors await a signed trade deal with the U.S. and further signs of a recovery in activity. Over the next 6-12 months, however, an overweight stance is warranted, barring a major relapse in our leading indicator. Feature Tables 1 and 2 on pages 2 and 3 highlight key developments in China’s economy and its financial markets over the past month. On the growth front, March’s data brought the very first (albeit modest) signs of stabilization in actual Chinese economic activity. While the April manufacturing PMIs released earlier this week disappointed, the trade related components of the official survey continued to improve meaningfully, which implies that an improvement in domestic demand is still early. This conclusion is not particularly surprising given that the first green shoots in the actual data are emerging from a depressed level of activity. Credit growth has only recently picked up, implying that actual activity will strengthen over the coming 6-12 months followed a signed trade deal and a continued (modest) uptrend in credit. Table 1China Macro Data Summary Table 2China Financial Market Performance Summary Within financial markets, the most significant recent development has been that Chinese stocks have sagged somewhat due to concerns that policymakers may meaningfully dial back their stimulus efforts over the coming year. In our view, recent statements from policymakers, as well as the fact that the recovery in activity is only now beginning, underscores that credit growth is unlikely to relapse over the coming year. It may not grow at the breakneck pace observed in the first quarter, but beyond the near-term jitters that this may introduce into the equity market, we do not see it as a threat to an overweight stance towards Chinese stocks over the coming 6-12 months. In reference to Tables 1 and 2, we provide below several detailed observations concerning developments in China’s macro and financial market data: Chart 1 highlights that March brought the first sign of a stabilization in actual Chinese economic activity. When measured on a smoothed basis, the Li Keqiang index itself weakened further in March, but total import growth moved sideways and nominal manufacturing output ticked higher. We noted in our last Macro & Market review that future changes in activity measures were now more likely to reflect actual changes in underlying economic circumstances given that the previously beneficial tariff front-running effect had probably washed out of the data. March’s data confirms this view, and underscores that activity will pickup in the second half of the year. Chart 1The First (Albeit Tentative) Sign Of Economic Stabilization Chart 2 shows that the uptrend in our leading indicator for Chinese economic activity is so far modest, but also that it is now at a 2-year high relative to its 12-month moving average. The indicator is being weighed-down by weak money growth (M2 and our definition of M3), even though monetary conditions remain easy and our measures of credit growth picked up sharply in Q1. We doubt that the trend in Chinese money and credit growth can sustainably decouple in a scenario where the latter is sustainably improving, as it would imply that all of the credit improvement was originating from non-bank financial institutions. As such, we expect money growth to catch up to credit growth in the coming months. The annual change in the PBOC’s pledged supplementary lending injection remained in negative territory in March, and both floor space started and sold decelerated modestly further. Construction and sales activity continue to diverge, with the latter still pointing to a further slowdown in the former. We will be updating our Chinese housing outlook in a Special Report next week. April’s Caixin and official manufacturing PMI disappointed, but this overshadowed a continued significant improvement in the new export orders and import components of the official PMI (Chart 3). In our view, this is consistent with a stabilization in the export outlook, but implies that Chinese domestically-oriented manufacturing activity is not yet booming. Nonetheless, a signed trade deal, improving importer/exporter sentiment, and an uptrend in credit growth still implies that activity will pick up meaningfully later in the year. Chart 2Our Leading Indicator Is Now Modestly Trending Higher Chart 3Trade-Related Components Of The Official PMI Continue To Rise   Over the past month, Taiwanese and domestic Chinese stocks have been the best performers within “Greater China”, relative to the MSCI Hong Kong index, the MSCI China index, and the Hang Seng China Enterprises index. The latter in particular has lagged other Chinese equity indexes since late-March (Chart 4), and may be due for a catch-up. Over the nearer-term, Chinese stocks, especially the domestic market, have sagged due to concerns that Chinese policymakers may meaningfully dial back their stimulus efforts over the coming year. We discussed this risk in our April 17thWeekly Report,1 and noted that while we expected credit growth to moderate somewhat, a more meaningful slowdown, particularly if coupled with signals from policymakers that a much slower pace of growth is desired, could pose a risk to our overweight equity stance. The April manufacturing PMIs disappointed, but the trade-related components of the official survey continued to improve meaningfully. In our view, recent statements from policymakers, particularly from PBOC Deputy Governor Liu Guoqiang,2 underscores that credit growth is unlikely to relapse over the coming year; it will simply not be growing at the breakneck pace observed in the first quarter. Beyond the near-term jitters that this may introduce into the equity market, we do not see it as a threat to an overweight stance towards Chinese stocks over the coming 6-12 months. Chart 5 highlights that Chinese consumer stocks have been the clear winners since the beginning of the year, particularly in the domestic market. Consumer stocks, including staples, sold off substantially in 2H2018 as investors responded to shockingly weak consumer spending data. Stimulus measures targeted to Chinese households, along with a meaningful improvement in some measures of consumer spending, has helped restore investor confidence in consumer stocks (which had previously been viewed as a bullish “no-brainer” structural trade). Chart 4Is An H-Share Catchup##br## Looming? Chart 5Chinese Consumer Stocks Have Been On Fire   The sharp rise in the 7-day interbank repo rate in April fed concerns among equity investors that Chinese policymakers might be in the process of paring back their stimulus efforts. However, as Chart 6 shows, China’s 7-day repo rate is extraordinarily volatile, and is affected by a variety of seasonal and technical factors. The chart shows that a 1-month moving average of the 7-day repo rate is broadly in line with the level that has prevailed over the past 9 months. In addition, the 3-month repo rate (which we have argued has been a more informative predictor of China’s monetary policy stance) remains well on the low end of its range over the past year. In short, despite investor concerns, Chinese interbank repo rates are not signaling a change in China’s monetary policy stance. Tighter monetary policy is not in the cards for this year. After having risen noticeably in late-March, Chinese onshore corporate bond spreads have fallen back to the low end of their trading range over the past 8 months. We continue to recommend that domestic investors hold a diversified portfolio of SOE corporate bonds, on the basis that actual bond defaults over the coming 6-12 months are likely to be materially lower than what investors are pricing in even though they are indeed likely to rise. Chart 7 shows that USD-HKD has eased somewhat over the past month from the top end of the band, and now trades closed at 7.845. This modest appreciation in HKD appears to have been catalyzed by a further reduction in the supply of interbank liquidity by the HKMA. While the appreciation in HKD is some modest good news for Hong Kong’s monetary authority, it remains reluctant to reduce liquidity in the system given how extremely weak loan growth is in Hong Kong. This implies that, barring a meaningful upturn in credit, a significant appreciation in HKD is not likely in the cards. Chart 6Interbank Repo Rates Are Not Trending Higher Chart 7A Modest Appreciation In HKD (Which Is Not Likely To Continue)   Jonathan LaBerge, CFA, Vice President Special Reports jonathanl@bcaresearch.com Footnotes 1      Please see China Investment Strategy Weekly Report “In The Wake Of An Upgrade: An Investment Strategy Post-Mortem,” dated April 17, 2019, available at cis.bcaresearch.com 2      During a PBOC briefing on April 25, Deputy Governor Guoqiang noted that “no one can bear it if policy swings back and forth between tightening and loosening many times a year”. Cyclical Investment Stance Equity Sector Recommendations