Global

Special Report

HighlightsU.S. inflation is on a structural uptrend. Monetary and fiscal policy, populism, and demographics will tend to push inflation higher over the coming decade.How can investors protect portfolios against inflation risk? We look at periods of rising inflation to determine which assets were the best inflation hedge.We find that the level of inflation is very important in determining which assets work best.When inflation is rising and high, or very high, the best inflation hedges at the asset class level are commodities and U.S. TIPS.When inflation is very high, gold is the best commodity to hold and defensive sectors will minimize losses in an equity portfolio.However, hedges have a cost. Allocating a large percentage of a portfolio to inflation hedges will be a drag on returns. Investors should opt for a low allocation to hedges now, and increase to a medium level when inflation rises further.FeatureSome 38 years have passed since the last time the U.S. suffered from double-digit inflation. The Federal Reserve reform of 1979, championed by Paul Volcker, changed the way the Fed approached monetary policy by putting a focus on controlling money growth.1 The reform gave way to almost four decades of relatively controlled inflation, which persists today.But times are changing. While most of today’s investors have never experienced anything other than periods of tame inflation, BCA expects that rising inflation will be a major driving force of asset returns over the coming decade.2 The main reasons behind this view are the following:A rethink in the monetary policy framework: At its most recent meeting, the FOMC openly discussed the idea of a price-level target, implying that it would be open to the economy running hot to compensate for the past 10 years of below-target inflation (Chart I-1A, top panel).Procyclical fiscal policy: The U.S. is conducting expansionary fiscal policy while the economy is at near-full employment (Chart I-1A, middle panel). The last time this happened in the U.S., during the 1960s, high inflation followed, as the fiscal boost made the economy run substantially above capacity.Waning Fed independence: President Trump has openly questioned the hiking campaign undertaken by the Fed. Moreover, he has tried to nominate Fed governors with dovish tendencies. Historically around the world, a lack of central bank independence has often led to higher inflation rates (Chart I-1A, bottom panel).Peak in globalization: Globalization accelerated significantly in the 1990s and 2000s, flooding the global economy with cheap labor (Chart I-1B, top panel). However, we believe that globalization has peaked. Instead, populism and protectionism will be the dominant paradigms for years to come, reducing the cheap pool of workers and goods previously available.Demographics: The population in the U.S. is set to age in coming years (Chart I-1B, middle panel). As the percentage of U.S. retirees increases, the number of spenders relative to savers will begin to rise (Chart I-1B, bottom panel). Higher spending and lower savings in the economy should create upward pressure on inflation. Chart I-1AStructural Forces Point To Higher Inflation In The Coming Decade (I)  Chart I-1BStructural Forces Point To Higher Inflation In The Coming Decade (II) If our view is correct, how should investors allocate their money?We attempt to answer this question by evaluating the performance of five major asset classes during periods when inflation was rising. Furthermore, we look into sub-asset class performance to determine how investors should position themselves within each asset class to take advantage of an inflationary environment.In our asset-class analysis, we use a data sample starting in 1973 and we limit ourselves to five publicly traded assets that have adequate history: global equities, U.S. Treasuries, U.S. real estate (REITs), U.S. inflation-linked bonds,3 and commodities. We compare asset classes according to their Sharpe ratios: average annualized excess returns divided by annualized volatilities.4 BCA expects that rising inflation will be a major driving force of asset returns over the coming decade.In our sub-asset class analysis, we analyze global equity sectors, international vs U.S. equities, and individual commodities. In some of the sections in our sub-asset class analysis, our sample is slightly reduced due to lack of historical data. Moreover, since in some instances all sectors have negative returns, we compare sub-asset classes according to their excess returns only.We base our analysis on the U.S. Consumer Price Index, given that most of the assets in our sample are U.S. based. We opt for this measure because it tends to track the living expenses for most U.S. citizens and it is the preferred measure to index defined-benefit payments.Finally, we decompose the periods of rising inflation into four quartiles in order to examine whether the level of inflation has any impact on the performance of each asset. Chart I-2 and Table I-1 show the different ranges we use for our analysis as well as a description of the typical economic and monetary policy environments in each of them.Summary Of ResultsTable I-2 shows the summary of our results. For a detailed explanation on how each asset class and sub-asset class behaves as inflation rises, please see the Asset Class section and the Sub-Asset Class section below.Which assets perform best when inflation is rising?Rising inflation affects assets very differently, and is especially dependent on how high inflation is.Global equities performed positively when inflation was rising and low or mild, but they were one of the worst-performing assets when inflation was rising and high or very high. Importantly, equities underperformed U.S. Treasuries in periods of both high and very high inflation.Commodities and U.S. TIPS were the best performers when inflation was high or very high.U.S. REITs were not a good inflation hedge.Which global equity sectors perform best when inflation is rising?Energy and materials outperformed when inflation was high.Every single sector had negative excess returns when inflation was very high, but defensive sectors such as utilities, healthcare, and telecommunications5 minimized losses.Which commodities perform best when inflation is rising?With the exception of energy, most commodities had subpar excess returns when inflation was in the first two quartiles.Industrial metals outperformed when inflation was high.Gold and silver outperformed when inflation was very high. Additionally, gold had consistent returns and low volatility.What is the cost of inflation hedging?To answer this question, we construct four portfolios with different levels of inflation hedging:Benchmark (no inflation hedging): 60% equities / 40% bonds.Low Inflation Hedging: 50% equities / 40% bonds / 5% TIPS / 5% commoditiesMedium Inflation Hedging: 40% equities / 30% bonds / 15% TIPS / 15 % commoditiesPure Inflation Hedging: 50% TIPS / 50% commodities. At the asset-class level, investors should allocate to commodities and U.S. TIPS to hedge inflation. Chart I-3Inflation Hedging Comes At A Cost While increased inflation hedging provides better performance when inflation is high and rising, these hedges are costly to hold when inflation is at lower ranges or when it is falling (Chart I-3, panels 1 & 2). However, adding moderate inflation hedging (low or medium) to a portfolio achieved the right balance between cost and protection, and ultimately improved risk-adjusted returns over the whole sample (Chart I-3, panel 3).What about absolute returns? The benchmark outperformed over the whole sample. However, the low and medium inflation hedging did not lag far behind, while avoiding the big drawdowns of high inflation periods (Chart I-3, panel 4).Investment ImplicationsHigh inflation may return to the U.S. over the next decade. Therefore, inflation hedging should be a key consideration when constructing a portfolio. Based on our results, our recommendations are the following:1.  At the asset-class level, investors should allocate to commodities and U.S. TIPS to hedge inflation.2.  However, these hedges are costly to hold as they will create a drag on returns in periods when inflation is not high or very high. Therefore, a low allocation to inflation hedges is warranted now.3.  Inflation will probably start to pick up in the 2020s. A medium allocation to inflation hedges will then be appropriate.4.  When inflation is high (3.3%-4.9%), investors should overweight energy and materials in their equity portfolios. Likewise, they should overweight industrial metals and energy within a commodity portfolio.5.  When inflation is very high (4.9% or more), investors should overweight defensive sectors in their equity portfolio to minimize losses. Moreover, investors should overweight gold within a commodity portfolio.Asset ClassesGlobal EquitiesThe relationship between equity returns and rising inflation depends on how high inflation is, with outstanding performance when inflation is rising but low or mild, and poor performance as it gets higher (Chart II-1, top panel).This relationship can be explained by the interaction between interest rates, inflation, earnings, and valuations:Earnings growth was usually slightly negative when inflation was recovering from low levels. However, given that interest rates were very low in this environment and growth expectations were high, multiple expansion boosted equity returns (Chart II-1, bottom panel).When inflation was mild, the Fed typically started to raise rates, resulting in a declining multiple. However, equities had the best performance in this range thanks to very high earnings growth – a result of the economy growing strongly due to a healthy level of inflation.When inflation climbed into the high or very high range, earnings growth was usually positive but beginning to slow, as high inflation weighed on growth. Meanwhile the multiple started to decline rapidly due to rising interest rates and declining growth expectations.With the exception of the mild inflation range, the return profile of equities during inflationary periods was similar to its normal profile: negative skew and excess kurtosis (Table II-1). However, the consistency of returns decreased at higher levels of inflation, with only 45% of months with positive returns when inflation was rising and in its highest quartile.U.S. TreasuriesU.S. Treasuries reacted in a similar fashion to equities when inflation was rising (Chart II-2). However, while Treasuries underperformed equities when inflation was low or mild, they actually outperformed equities when inflation was high or very high. This was in part due to the fact that at higher inflation ranges, U.S. Treasuries offer a higher coupon return when rates are high, at least partially counteracting losses from falling prices.The steady stream of cash flows from the coupons helped Treasuries achieve positive returns roughly two-thirds of the time at the highest levels of inflation (Table II-2). However, this consistency in returns came at a cost: very high inflation resulted in negative skew and high excess kurtosis. Therefore, while Treasuries provided frequent positive returns when inflation was very high, they were prone to violent selloffs.U.S. REITsWhile REITs had high risk-adjusted returns when inflation was rising but mild, much like equities they had subpar performance in every other quartile and particularly poor performance when inflation was high or very high (Chart II-3). These results confirm our previous research showing that REITs performance is very similar to that of equities.6The return consistency for REITs was generally poor in inflationary periods, with the second-lowest percentage of positive return of any asset class (Table II-3). Moreover, REIT returns had excess kurtosis and negative skew throughout all inflation quartiles.Commodity FuturesCommodities performed positively in every quartile, and did particularly well when inflation was mild (Chart II-4, top panel). However, total return and price return were very different due to the behavior of the roll and collateral return:Total risk-adjusted returns were lower than spot risk-adjusted returns when inflation was low and rising. This happened because during these periods, commodity supply was high relative to demand, as the economy was recovering from a deflationary shock. Thus, there was an incentive for producers to conserve inventories, making the futures curve upward-sloping (contango). Thus, roll return was negative (Chart II-4, bottom panel).When inflation was in the upper two quartiles, total risk-adjusted returns were much higher than risk-adjusted spot returns. This was because high inflation was the product of supply shocks. These supply shocks resulted in a downward-sloping futures curve (backwardation), which, in turn, resulted in a positive roll return. Additionally, high rates during these regimes contributed to a high collateral return.Commodities provided good return consistency during inflationary periods, with roughly 60% of positive return months in the upper two inflation quartiles (Table II-4). The skew of returns was neutral or positive in the top two quartiles. This means that although volatility was high for commodities, extreme return movements were normally positive.U.S. Inflation-Protected BondsWhile inflation-protected bonds provided meager returns when inflation was rising but in the mild range, they provided excellent performance at the highest levels of inflation (Chart II-5). Moreover, this high Sharpe ratio was not just simply the result of low volatility, since U.S. TIPS had excess returns of 4.6% when inflation was high and 5.7% when inflation was very high.7The return profile of inflation-protected bonds during inflationary periods was also attractive in our testing period. Average skew was positive, while kurtosis was relatively low (Table II-5). The percentage of positive months across all quartiles was also the highest of all asset classes, with a particularly high share of positive returns in the periods of highest inflation.Sub-Asset ClassesGlobal Equity SectorsFor the sector analysis, we looked at information technology, financials, energy, materials, utilities, healthcare, and telecommunications. We excluded industrials, consumer discretionary, and consumer staples given that they do not have adequate back data.Once again, we separate rising inflation periods into four quartiles, arriving at the following results:When inflation was low, information technology had the best excess returns while utilities had the worst (Chart III-1, panel 1). This matches our observations at the asset class level, as IT is highly responsive to changes in the valuation multiple.When inflation was mild, energy had the best performance, followed by information technology (Chart III-1, panel 2). Meanwhile, financials had the worst performance, as rates were normally rising in these periods.When inflation was high, sectors highly correlated with commodity prices such as energy and materials outperformed. Meanwhile, IT was the worst performer (Chart III-1, panel 3).When inflation was very high, every sector had negative excess returns. Overall, investing in energy minimized losses (Chart III-1, panel 4). However, this performance was in part attributable to the oil spikes of the 1970s. Alternatively, defensive sectors such as utilities, telecommunications, and healthcare also minimized losses. International vs U.S. EquitiesHow do equities outside of the U.S. behave when inflation is rising? While the high share of U.S. equities in the global index causes U.S. equities to be the main driver of global stock prices, is it possible to improve returns in inflationary environments by overweighting international equities?The answer once again depends on the level of inflation. When inflation was rising but low, U.S. stocks outperformed global ex-U.S. equities in both common currency and local currency terms (Chart III-2, panel 1). This was in part due to the inherent tech bias in U.S. stocks. Additionally, the low level of inflation was often accompanied by slowing global growth in our sample, helping the U.S. dollar.When inflation was mild, U.S. stocks once again outperformed international stocks in both local and common currency terms, though to a lesser degree (Chart III-2, panel 2). The dollar was roughly flat in this environmentU.S. stocks started to have negative excess returns when inflation was high (Chart III-2, panel 3). On the other hand international equities had positive excess returns in dollar terms, partly because of their energy and material bias and partly because the dollar was generally weak in this period.U.S. equities outperformed global ex-U.S. equities by a small margin when inflation was very high, given that defensive sectors such as telecommunication were over-represented in the U.S. index (Chart III-2, panel 4). The dollar was roughly flat in this period. Individual CommoditiesOur analysis above confirmed that commodities were one of the best assets to hold when inflation was rising. However, which commodity performed best?8Total return for every commodity was lower than spot return when inflation was low (Chart III-3, panel 1). This was due to the upward-sloping term structure of the futures curve (contango), resulting in a negative roll yield. In this range, energy had the best performance, followed by industrial metals. Precious metals had negative excess returns.When inflation was mild, energy had the best performance of any commodity by far (Chart III-3, panel 2). Precious and industrial metals had low but positive excess returns in this period.When inflation was high, industrial metals had the highest excess returns, followed by energy (Chart III-3, panel 3).We omit energy for the last quartile since there is not enough data available. Overall, when inflation was very high, both gold and silver had the highest excess returns (Chart III-3, panel 4). However, gold’s return volatility was much lower, while it also had positive returns  64% of the time compared to 52% for silver.Other AssetsU.S. Direct Real Estate Chart IV-1Direct Real Estate Is A Good Inflation Hedge Our asset-class analysis confirmed that public real estate (REITs) as an asset class offered poor risk-adjusted returns during inflationary periods. But how did direct real estate perform?We analyzed direct real estate separately from all other assets because of a couple of issues:Our return dataset is available only on a quarterly basis, versus a monthly basis for the rest of the assets in our sample. Even when annualized, volatility is not directly comparable when using data with different frequencies.The NCREIF Real Estate Index that we used is a broad aggregate, which is not investable. Individual property prices might differ from this aggregate.Finally, real estate returns are measured on an appraisal basis. Appraisal-based indices are not reflective of real transactions. Moreover, prices tend to be sticky. To attenuate this issue we unsmoothed the capital returns by removing return autocorrelation.Overall, the Sharpe ratio of direct real estate was solid throughout the first three quartiles of rising inflation (Chart IV-1, top panel). There is not enough data available for the fourth quartile. However, judging by the performance of U.S. housing in the 1970s from OECD, risk-adjusted returns when inflation was very high was likely positive (Chart IV-1, bottom panel). Cash Chart IV-2Very High Inflation Erodes The Value Of Cash Cash (investing in a 3-month U.S. Treasury bill) outperformed inflation over our sample. (Chart IV-2, top panel). Moreover, cash provided positive real returns when inflation was mild, or high, or when it was decreasing (Chart IV-2, bottom panel). However, cash was not a good inflation hedge at the highest inflation quartile, with an average annualized real loss of almost 2%. Juan Manuel Correa OssaSenior Analystjuanc@bcaresearch.com Footnotes1      Please see Carl E. Walsh, “October 6, 1979,” FRSBF Economic Letter, 2004:35, (December 3, 2004).2      Please see Global Investment Strategy Special Report, “1970s-Style Inflation: Could it Happen Again? (Part 1), ” dated August 10, 2018, available at gis.bcaresearch.com and Global Investment Strategy Special Report, “1970s-Style Inflation: Could it Happen Again? (Part 2),” dated August 24, 2018, available at gis.bcaresearch.com.3      We use a synthetic TIPS series for data prior to 1997. For details on the methodology, please see: Kothari, S.P. and Shanken, Jay A., “Asset Allocation with Inflation-Protected Bonds,” Financial Analysts Journal, Vol. 60, No. 1, pp. 54-70, January/February 2004. Jay A., “Asset Allocation with Inflation-Protected Bonds,” Financial Analysts Journal, Vol. 60, No. 1, pp. 54-70, January/February 2004.4      Excess returns are defined as asset return relative to a 3-month Treasury bill.5      Sector classification does not take into account GICS changes prior to December 2018. 6      Please see Global Asset Allocation Strategy Special Report "REITS Vs Direct: How To Get Exposure To Real Estate," dated September 15, 2016, available at gaa.bcaresearch.com.7      It is important to note that the synthetic TIPS series does not completely match actual TIPS series for the periods where they overlap. Specifically, volatility is significantly higher in the synthetic series. Thus, results should be taken as approximations.8      We decompose the returns into the same 4 quartiles to answer this question. However, due to lower data availability, we start our sample in 1978 instead of 1973. Moreover, our sample for energy is smaller beginning in 1983. This mainly reduces the amount of data available at the upper quartile.       

Highlights Global financial markets are currently dealing with a fresh round of uncertainty related to U.S.-China trade tensions. Yet while equities and government bond yields have fallen in response to the U.S. imposition of tariffs and escalation of the trade war with China, corporate bond markets in the developed economies have been relatively well-behaved (so far). Credit spreads have only widened modestly, which perhaps should not be surprising given central bankers’ increasingly dovish bias combined with early signs of a cyclical global growth rebound (Chart 1). Feature Chart 1Global Corporates: Shifting To A Friendlier Growth Backdrop? With that in mind, this week we are presenting the latest update of our Corporate Health Monitor (CHM) Chartbook. The CHMs are composite indicators of balance sheet and income statement ratios (using both top-down and bottom-up data) that are designed to assess the financial well-being of the overall non-financial corporate sectors in the major developed economies. A brief overview of the methodology is presented in Appendix 1 on page 15. The main conclusion from the latest readings on our CHMs is that slower economic growth over the past year has resulted in some erosion of overall global credit quality. The deterioration was most pronounced in the more economically fragile regions that have suffered the deepest pullbacks in growth: Europe and Japan. The CHMs are currently giving an overall “neutral” signal in the U.S., although there are some worrying trends developing within the sub-components like interest coverage and short-term liquidity. Meanwhile, the CHMs in the U.K. and Canada are showing modest cyclical deterioration from very strong levels. Broadly speaking, the CHMs support our main global corporate bond market investment recommendations: a tactical aggregate overweight versus global government bonds, with a regional bias favoring the U.S. over Europe, and a quality bias tilted towards U.S. high-yield (HY) over investment grade (IG). Renewed U.S.-China trade hostilities represent a threat to that pro-cyclical fixed income asset allocation, although we expect more aggressive responses from policymakers on both sides (more fiscal and monetary stimulus in China, a more dovish bias from the Fed) to offset any tariff-induced weakness in growth. U.S. Corporate Health Monitors: Cyclically OK, But Longer-Term Problems Are Brewing Our top-down U.S. CHM is sending a neutral message on credit quality, sitting right on the threshold separating “deteriorating health” from “improving health” (Chart 2). The indicator, however, has been trending in a direction showing improving credit metrics over the past year. From a fundamental perspective, the top-down U.S. CHM suggests that the U.S. credit cycle is being extended by the stubborn endurance of the U.S. business cycle.  The resilience of the U.S. economy, combined with the positive impact on U.S. profitability from the Trump corporate tax cuts, has put U.S. companies in a cyclically healthier position, even with relatively high leverage. The ratios directly related to corporate profits that go into the top-down CHM – return on capital, profit margins and interest coverage – have all gone up over the past year, generating the bulk of the directional improvement in the top-down CHM. From a fundamental perspective, the top-down U.S. CHM suggests that the U.S. credit cycle is being extended by the stubborn endurance of the U.S. business cycle. In other words, there are no immediate domestic pressures on U.S. corporate finances that should require significantly wider credit spreads to compensate for rising downgrade/default risk. That does not mean that all the news is good, however. The short-term liquidity ratio has fallen sharply and is now at levels last seen in the years leading up to the 2008 Financial Crisis. Similar deteriorations can be seen in the short-term liquidity ratios within the bottom-up versions of our U.S. CHMs for IG corporates (Chart 3) and HY companies (Chart 4). Coming at a time when interest coverage ratios have been steadily declining for IG, and are already at low levels for HY, declining short-term liquidity would leave U.S. corporates highly vulnerable during the next economic downturn. Chart 2Top-Down U.S. CHM: A Neutral Reading Chart 3Bottom-Up U.S. IG CHM: Modest Deterioration With Worrying Trends We see no reason yet to exit our tactical overweight stance on U.S. IG and HY corporates versus both U.S. Treasuries and non-U.S. corporates. For now, however, the message from our bottom-up U.S. CHMs is the same as that from our top-down U.S. CHM, with all hovering near the zero line suggesting no major deterioration in overall credit quality. We see no reason yet to exit our tactical overweight stance on U.S. IG and HY corporates versus both U.S. Treasuries and non-U.S. corporates (Chart 5). Our favored indicators continue to point to a rebound in global growth in the latter half of 2019, and the Fed currently has no desire to push the funds rate into restrictive territory, so the risk/reward over the next six months still favors staying overweight U.S. corporates. The medium-term outlook, however, is far more challenging given the growing body of evidence pointing to the advanced age of the U.S. credit cycle, such as falling interest coverage and liquidity. Chart 4Bottom-Up U.S. HY CHM: A Cyclical Improvement, Nothing More Chart 5U.S. Corporates: Stay Tactically Overweight IG & HY One final point – in Appendix 2 starting on page 17, we present bottom-up CHMs for the main industry sector groupings of companies that go into our overall U.S. IG CHM. Most of the sector CHMs are hovering near the zero line, but two industry groupings stand out as having a rising CHM that is now well within “deteriorating health” territory – Consumer Staples and Utilities. Euro Corporate Health Monitors: Worsened By Weaker Growth The message from our bottom-up CHMs for the euro area shows that there was some damage done to credit quality from last year’s growth slump, evidenced by lower profit margins and interest coverage ratios. Although overall credit quality remains fairly neutral (i.e. the CHMs remain near the zero line). For euro area IG, the gap between domestic and foreign issuers in the euro area corporate bond market continues to widen, with the former now slightly in the “deteriorating health” zone (Chart 6). Profit margins have fallen far more sharply for domestic issuers, reflecting the very rapid slowing of euro area growth over the latter half of 2019. Interest coverage for domestic issuers is also lower than for foreign issuers, while short-term liquidity ratios have weakened for both over the past year. For euro area HY, the signal from the bottom-up CHM is more consistently positive between domestic and foreign issuers (Chart 7). Leverage has declined, but profit-based metrics have worsened for both sets of issuers. Interest/debt coverage and liquidity, however, are far worse for domestic issuers. Chart 6Bottom-Up Euro Area IG CHMs: Weaker Growth Hitting Domestic Issuers Chart 7Bottom-Up Euro Area HY CHMs: Healthier Through Lower Leverage Within the euro area, our bottom-up IG CHMs for Core and Periphery countries have worsened over the past year, from healthy levels, and are now hovering just above the zero line (Chart 8). Interest coverage is considerably stronger for Core issuers, although profitability metrics are remarkably similar. Short-term liquidity ratios have also fallen for both regional groups over the past year. The spread tightening already seen in euro area credit is too extreme relative to the still sluggish pace of economic growth in the region. Despite the lack of a major overall negative signal from the euro area CHMs, we are only maintaining a neutral allocation to euro area corporates, even within our current overweight stance on overall global corporates (Chart 9). The spread tightening already seen in euro area credit is too extreme relative to the still sluggish pace of economic growth in the region. This will inhibit the ability for spreads to tighten further in the event of a pickup in growth, while also leaving spreads vulnerable to widening pressures if euro area growth continues to languish. Chart 8Bottom-Up Euro Area Regional IG CHMs: Trending In The Wrong Direction Chart 9Euro Area Corporates: Stay Tactically Neutral IG & HY Chart 10Relative Bottom-Up CHMs: Continue To Favor U.S. Over Europe In addition, we are sticking with our preference to favor U.S. corporates – both IG and HY – over euro area equivalents for two important reasons: stronger U.S. growth and better U.S. corporate health. The gap between the combined IG/HY bottom-up CHMs for the U.S. and euro area has been strongly correlated to the difference in credit spreads between euro area and U.S. issuers (Chart 10).1 The latest trends show a narrowing of the gap between the U.S. and euro area CHMs, suggesting relative corporate health favors U.S. names (middle panel). At the same time, the relatively stronger performance of the U.S. economy continues to support U.S. corporate performance versus euro area equivalents (bottom panel). U.K. Corporate Health Monitor: Brexit Uncertainty Is Not Helping Our top-down U.K. CHM remains in the “improving health” zone, although the indicator has been drifting towards “deteriorating health” over the past two years. Almost all of the components of the U.K. CHM have contributed to this worsening trend (Chart 11), with only short-term liquidity remaining in a powerful multi-year uptrend. Most worryingly, the interest and debt coverage ratios remain historically depressed, even as the Bank of England has keep interest rates at extraordinarily low levels for the past several years. The cyclical deterioration in the U.K. CHM components can be traced to the sluggish performance of the U.K. economy and corporate profits.   The cyclical deterioration in the U.K. CHM components can be traced to the sluggish performance of the U.K. economy and corporate profits. The persistent uncertainty from Brexit has weighed on business confidence and investment spending by U.K. firms, keeping growth at a below-trend pace. While the immediate deadline of “Brexit Day” came and went back in March, there is still a high degree of uncertainty over the U.K.’s future economic relationship with the European Union. With Prime Minister Theresa May now set to step down, an election will extend the period of politically-driven uncertainty in the U.K. We have maintained a moderate underweight recommendation on U.K. corporates in our model bond portfolio over the past year, despite the lack of an obvious negative signal from our U.K. CHM. Spread widening in 2018 has been followed by spread tightening in 2019 (Chart 12), but the latter has been driven by the global rally in risk assets rather than diminished perceptions of U.K. political risk. Chart 11U.K. Top-Down CHM: Modest Pullback From Healthy Levels Chart 12U.K. Corporates: Stay Modestly Underweight Although there has been some improvement in U.K. economic data of late, leading economic indicators continue to trend lower. In addition, the Bank of England continues to hint that any positive resolution to the Brexit uncertainty could result in a tightening of monetary policy (although that is less of a threat given the synchronized dovish turn by global central bankers over the past few months). Given all the uncertainties, the risk/reward balance continues to favor a modest underweight in U.K. corporates, particularly at current tight spread levels to Gilts. Japan Corporate Health Monitor: A Modest Cyclical Deterioration Our bottom-up Japan CHM has shown a worsening trend over the past year and now sits in the “deteriorating health” zone (Chart 13).2 Interestingly, all of the individual components have contributed to that move in the CHM, and not just the cyclical components (profit margins, return on capital, interest coverage) that reflect the recent slowing of economic growth in Japan. Leverage has increased (albeit from very low levels), while short-term liquidity has also weakened (albeit from very high levels). Strictly looking at the overall level of all the Japan CHM components, the message does not signal a major deterioration in Japanese corporate credit quality. Leverage, defined here as the ratio of total debt to the book value of equity, is still below 100%, well below the 100-140% range seen between 2006 and 2015. The same story applies to the return on capital, which at 5% is still high versus Japan’s history (although very low by global standards). Interest coverage and short-term liquidity both remain high relative to the past decade. The absolute level of Japanese corporate health remains solid, but there has been marginal deterioration from weaker economic growth. On that front, the cyclical momentum in Japan’s economy is not improving. According to the latest Tankan survey, Japanese firms reported that their business outlook was worse than previously expected. Declining confidence has damaged capital spending, as shown by the falling growth of domestic machinery and machine tool orders. Japan’s economy remains highly levered to global growth and export demand and their economy has taken a hit from the slower pace of global trade over the past year. Wage growth has also weakened after finally seeing some positive momentum in 2018, which is weighing on consumer confidence and spending. Japan’s corporate spread has widened slightly (+5bps) since the beginning of this year (Chart 14), in contrast to the spread tightening seen in other major developed economy corporate bond markets (the Bloomberg Barclays Global Corporates index spread has tightened by -33bps year-to-date). This is a sign that the markets have responded to the slowing growth momentum in Japan with a bit of a wider risk premium. Yet despite that widening, Japanese corporates with small positive yields continue to generate positive excess returns versus Japanese Government Bonds (JGBs) with yields held near zero by the Bank of Japan’s Yield Curve Control policy. Thus, we continue to recommend an overweight stance on Japanese corporates vs JGBs as a buy-and-hold carry trade, even with the softening in our Japan CHM. Chart 13Japan Bottom-Up CHM: Cyclical Deterioration Chart 14Japan Corporates: Stay Overweight Vs JGBs For Carry Canada Corporate Health Monitor: Still In Decent Shape Our top-down and bottom-up Canadian CHMs indicate an improving trend in Canadian corporate health, with both remaining in the “improving health” area over the past few years (Chart 15). The marginal moves have shown some modest deterioration in the cyclically-sensitive components (most notably, return on capital and profit margins for the top-down Canadian CHM). This should not be surprising given how rapidly Canadian economic growth slowed in the final quarter of 2018. There has also been some deterioration in the non-cyclical components. Leverage is high and rising, while the absolute levels of return on capital and debt/interest coverage are historically low. This may be building up risks for the next major Canadian economic downturn, but for now, Canadian companies look in decent shape. With so much of Canada’s economy (and its financial markets) geared to the performance of the energy sector, the recent recovery in global oil prices is a significant boost for the overall Canadian corporate market. Our commodity strategists see additional upside in oil prices over the next six months, which will further underpin the health of Canadian oil companies – and should also help support Canadian corporate bond performance. The Bank of Canada is now taking an extended pause from its rate-hiking cycle, with policy rates well below the central bank’s own estimate of neutral (2.25-3.25%). Accommodative monetary conditions and relatively low Canadian interest rates will continue to make Canadian corporates attractive, in an environment of decent growth and firm corporate health. Chart 15Canada CHMs: Still Healthy, Despite Slower Growth Chart 16Canadian Corporates: Stay Overweight Vs Canadian Govt. Debt We continue recommending an overweight position in Canadian corporate debt relative to Canadian government bonds as a carry trade. Spreads have been in a very stable range since the 2009 recession (Chart 16), ranging between 100-200bps even during periods when our CHMs were indicating worsening corporate health. To break out of that range to the upside, we would need to see a prolonged deterioration of Canadian economic growth or sharp monetary tightening from the Bank of Canada – neither outcome is likely over the next 6-12 months.   Robert Robis, CFA, Chief Fixed Income Strategist rrobis@bcaresearch.com Ray Park, CFA, Research Analyst ray@bcaresearch.com   Appendix 1: An Overview Of The BCA Corporate Health Monitors The BCA Corporate Health Monitor (CHM) is a composite indicator designed to assess the underlying financial strength of the corporate sector for a country. The Monitor is an average of six financial ratios inspired by those used by credit rating agencies to evaluate individual companies. However, we calculate our ratios using top-down (national accounts) data for profits, interest expense, debt levels, etc. The idea is to treat the entire corporate sector as if it were one big company, and then look at the credit metrics that would be used to assign a credit rating to it. Importantly, only data for the non-financial corporate sector is used in the CHM, as the measures that would be used to measure the underlying health of banks and other financial firms are different than those for the typical company. The six ratios used in the CHM are shown in Table 1 below. To construct the CHM, the individual ratios are standardized, added together, and then shown as a deviation from the medium-term trend. That last part is important, as it introduces more cyclicality into the CHM and allows it to better capture major turning points in corporate well-being. Largely because of this construction, the CHM has a very good track record at heralding trend changes in corporate credit spreads (both for Investment Grade and High-Yield) over many cycles. Table 1Definitions Of Ratios That Go Into The CHMs Top-down CHMs are now available for the U.S., euro area, the U.K. and Canada. The CHM methodology was extended in 2016 to look at corporate health by industry and by credit quality.3 The financial data of a broad set of individual U.S. and euro area companies was used to construct individual “bottom-up” CHMs using the same procedure as the more familiar top-down CHM. Some of the ratios differ from those used in the top-down CHM (see Table 1), largely due to definitional differences in data presented in national income accounts versus those from actual individual company financial statements. The bottom-up CHMs analyze the health of individual sectors, and can be aggregated up into broad CHMs for Investment Grade and High-Yield groupings to compare with credit spreads. In 2018, we introduced bottom-up CHMs for Japan and Canada. With the country expansion of our CHM universe, we now have coverage for 92% of the Bloomberg Barclays Global Aggregate Corporate Bond Index (Appendix Chart 1). Appendix 2: U.S. Bottom-Up CHMs For Selected Sectors       Footnotes 1 We only use the CHMs for euro area domestic issuers in this aggregate bottom-up CHM, as this is most reflective of uniquely European corporate credits. This also eliminates double-counting from U.S. companies that issue in the euro area market that are part of our U.S. CHMs. 2 We do not currently have a top-down CHM for Japan given the lack of consistent government data sources for all the necessary components. 3 Please see Section II of The Bank Credit Analyst, “U.S. Corporate Health Gets A Failing Grade”, dated February 2016, available at bca.bcaresearch.com. Recommendations The GFIS Recommended Portfolio Vs. The Custom Benchmark Index Duration Regional Allocation Spread Product Tactical Trades Yields & Returns Global Bond Yields Historical Returns

Highlights Duration: We see current bond market behavior as very similar to mid-2016, when heightened political uncertainty obscured the economy’s true strength and kept bond yields lower for longer than was justified by the economic fundamentals. The correct strategy at that time was to sell into the bond market’s strength, and we advocate a similar strategy today. China: Any attempt by the Chinese government to retaliate in the trade war by selling U.S. Treasury securities would be either self-defeating or ineffective, depending on the exact strategy employed. In either case, U.S. Treasury yields will be unaffected. Fed: At least part of the Fed’s dovish turn might represent a desire to send the labor share of national income higher. We introduce a new data series for Fed Watchers to track. Feature The Trump Administration fired the latest salvo in the trade war two weeks ago, expanding tariffs to a broader swathe of Chinese imports. Then last week, the escalation of tensions spilled over to the bond market, sending global yields abruptly lower. Chart 1Flight To Safety The 10-year U.S. Treasury yield bounced off 2.35% last Thursday and has since settled at 2.39% (Chart 1). Meanwhile, the overnight index swap curve is now priced for 44 bps of Fed rate cuts over the next 12 months (Chart 1, bottom panel). It is possible, and even likely, that geopolitical tensions will keep yields low during the next month or two. In fact, our Geopolitical Strategy service places the odds of a complete breakdown in trade negotiations by the end of June at 50%.1  But we would encourage investors to sell into rallies, positioning for higher yields on a 6-12 month horizon. To see why, we return to a Weekly Report from early April where we walked through different factors that would be useful in the creation of a macroeconomic model for the 10-year U.S. Treasury yield.2 We consider what has changed during the past six weeks and what those developments mean for bond yields going forward. Back In The Bond Kitchen In early April, we ran through four different factors that should be included in any bond model and suggested macroeconomic indicators that best capture the trends in each. The four factors are: Global Growth: Best proxied by the Global Manufacturing PMI and Bullish Dollar Sentiment Policy Uncertainty: Best proxied by the Global Economic Policy Uncertainty Index Output Gap: Best proxied by Average Hourly Earnings Sentiment: Best proxied by the U.S. Economic Surprise Index We consider each factor in turn. Global Growth Chart 2Monitoring Global Growth The Global Manufacturing PMI, our preferred series for tracking global growth, ticked down during the past month, continuing the free-fall that has been in place since the end of 2017 (Chart 2). At 50.3, it is now only slightly above the 50 boom/bust line and is close to where it was in mid-2016, when the 10-year yield hit its cyclical low. But on a positive note, several leading indicators have hooked up in recent months, suggesting that the Global PMI could soon trough and move higher in the second half of the year. Specifically, the ZEW survey of global economic sentiment is off its lows, as is the BCA Global Leading Economic Indicator (LEI). Meanwhile, the Global LEI Diffusion Index has surged, indicating that 74% of the 23 countries in our sample are seeing improvement in their LEIs. Historically, the Global LEI Diffusion Index leads changes in both the Global LEI and the Global Manufacturing PMI (Chart 2, panel 3). Financial market prices that are highly geared to global growth had been singing a similar tune, but they rolled over as trade tensions flared during the past two weeks. For example, cyclical equity sectors recently started to underperform defensive sectors (Chart 2, bottom panel), and the important CRB Raw Industrials index took a nosedive. We place particular importance on the CRB Raw Industrials index as a timely indicator of global growth, because the ratio between the CRB index and gold correlates nicely with the 10-year Treasury yield (Chart 3).3 Unsurprisingly, the ratio’s recent dip coincides with last week’s drop in the 10-year. Several leading indicators have hooked up in recent months, suggesting that the Global PMI could soon trough and move higher in the second half of the year.  In addition to the Global Manufacturing PMI, we recommend including a survey of bullish sentiment toward the U.S. dollar in any bond model. More bullish dollar sentiment coincides with lower Treasury yields, and vice-versa. Our preferred survey shows that dollar sentiment remains elevated, but hasn’t changed much since April (Chart 4). The dollar itself, however, has begun to appreciate during the past two weeks (Chart 4, bottom panel). Chart 3A Falling CRB/Gold Ratio... Chart 4...And The Greenback Is On The Rise Bottom Line: The coincident global growth indicators that correlate best with bond yields – the Global Manufacturing PMI and Dollar Bullish Sentiment – are sending a similar message as in April. Meanwhile, leading economic indicators continue to suggest that we should expect improvement in the second half of the year. The biggest change from April is that global growth indicators derived from financial market prices – cyclical versus defensive equities, the CRB Raw Industrials index and the trade-weighted dollar – have responded negatively to heightened political risk. If this weakness persists and eventually infects the economic data, then it could prevent a second-half rebound in global growth, keeping Treasury yields low for even longer.   Policy Uncertainty Spikes in the monthly Global Economic Policy Uncertainty Index often cause capital to seek out the safety of U.S. Treasuries, and we recommend including this index in any macroeconomic bond model (Chart 5A). Spikes in the monthly Global Economic Policy Uncertainty Index often cause capital to seek out the safety of U.S. Treasuries. While there have been no updates to the monthly index since the trade war’s recent escalation, one of its components – a daily index that tracks the number of relevant news stories – has surged during the past two weeks (Chart 5B). This clearly illustrates that a sharp increase in political uncertainty has been the catalyst for the bond market rally. Investors are obviously concerned that an ongoing and intensifying trade war might derail the economic recovery, and they are seeking out Treasuries as a hedge. Chart 5AGlobal Uncertainty Set To Spike Chart 5BMarkets Are Concerned In such situations, the traditional playbook is to fade any purely uncertainty-driven rally, on the view that markets tend to overreact to headline risk. This strategy worked well following the mid-2016 Brexit vote. The uncertainty shock from the vote sent the 10-year quickly down to 1.37%, but it then increased in the second half of the year when it became apparent that the economic recovery would continue. While higher tariffs will certainly be a drag on growth going forward, accommodative Fed policy and a probable increase in Chinese economic stimulus will mitigate the impact, keeping the economic recovery intact.4 Output Gap Chart 6Wages Are Headed Higher The output gap is a concept that represents where the economy is operating relative to its peak capacity, and its progress during the past three years is the main reason why bond yields will not re-test 2016 lows. We have found that wage growth is the most reliable way to measure the output gap: higher wage growth signals less spare capacity, and less spare capacity coincides with higher bond yields. We recommend Average Hourly Earnings as the best wage measure to include in any bond model. Since April, average hourly earnings growth has been roughly flat, but leading indicators suggest that further acceleration is highly likely in the coming months (Chart 6). While the Fed is keen to let wage growth accelerate, rising wage growth also makes a rate cut difficult to justify. The combination of rising wage growth and an on-hold Fed should put a rising floor under long-maturity bond yields. Sentiment The final factor that should be included in any bond model is sentiment. In April, we suggested that the U.S. Economic Surprise Index is the best measure of sentiment. When the surprise index has been deeply negative for a long time, it usually means that investors are downbeat on the economy and that the bar for a positive surprise is low. This has actually been the case in recent months, and our simple auto-regressive model suggests that the surprise index is biased higher (Chart 7). Positioning data confirm this message, and in fact show that investors are taking as much duration risk as they were when yields troughed in mid-2016 (Chart 8). Chart 7Low Bar For Positive Surprises Chart 8Similar Positioning As In Mid-2016 The overall message is that bond investors have a very dim view of the economy, and it will not take much positive news to send yields higher. Investment Strategy We see current bond market behavior as very similar to mid-2016, when heightened political uncertainty obscured the economy’s true strength and kept bond yields lower for longer than was justified by the economic fundamentals. The correct strategy at that time was to sell into the bond market’s strength, and we advocate a similar strategy today. Timing when the next move higher in bond yields will occur is difficult, but we take some comfort in the fact that the flatness of the yield curve makes it less costly than usual to carry below-benchmark duration positions. In fact, the average yield on the Bloomberg Barclays Cash index is 7 bps higher than the average yield on the Bloomberg Barclays Treasury Master Index. Bond investors have a very dim view of the economy, and it will not take much positive news to send yields higher. To further mitigate the cost of keeping duration low, we advocate taking duration-neutral positions that are short the belly (5-year & 7-year) part of the yield curve and long the very long and very short ends of the curve. Such trades are also provide a positive yield pick-up, and will earn capital gains when Treasury yields move higher.5 A Quick Note On China’s Treasury Purchases Chart 9Do Not Expect Treasuries To Be Used As A Weapon In This War The trade war’s recent escalation has led some to speculate that China could retaliate against higher tariffs by dumping U.S. Treasury securities onto the open market. The speculation only increased when the TIC data revealed that Chinese net Treasury purchases totaled -$24 billion in March, the most deeply negative figure since October 2016 (Chart 9).   We see low odds that China will employ this tactic in the trade war, and no meaningful impact on Treasury yields in any case. To see why, let’s consider two possible scenarios. In the first scenario, China sells a large amount of U.S. Treasury securities and keeps the proceeds from the sales in its domestic currency. Assuming the amounts in question are sufficiently large, these transactions would cause the RMB to appreciate and lead to a tightening of Chinese monetary conditions. Tighter monetary conditions are exactly what the Chinese government does not want as it seeks to counteract the negative economic impact from tariffs. In fact, China is much more likely to engineer a further easing of monetary conditions, much like in 2015/16 (Chart 9, bottom panel). In the second scenario, China could sell U.S. Treasuries and purchase other foreign bonds (German bunds, for example). This would nullify any impact on Chinese monetary conditions, but it would not have much impact on U.S. Treasury yields. With Chinese money still flowing into global bond markets, the re-balancing would only push other investors out of non-U.S. bond markets and into U.S. Treasuries. Without changing the overall demand for global bonds, it is difficult to envision much of an impact on U.S. yields. Bottom Line: Any attempt by the Chinese government to retaliate in the trade war by selling U.S. Treasury securities would be either self-defeating or ineffective, depending on the exact strategy employed. In either case, U.S. Treasury yields will be unaffected. A New Data Series For Fed Watchers: Rich’s Ratio A number of recent Fed speeches have referred to the time series plotted in Chart 10: The share of national income going to labor, as opposed to corporate profits. Chart 10Introducing Rich's Ratio Vice-Chair Richard Clarida brought this analysis to the Fed, and the data series was actually once dubbed “Rich’s Ratio” by Clarida’s old PIMCO colleague Paul McCulley. The idea behind Rich’s Ratio is that while some late-cycle wage gains are passed through to prices, a portion also eat into corporate profits. Notice in Chart 10 that Rich’s Ratio has a tendency to rise late in the economic recovery. Based on his past writings, we would not be surprised if at least part of the Fed’s recent dovish turn represents a desire to send Rich’s Ratio higher, even if that goal might entail a modest overshoot of the Fed's 2 percent inflation target. We will have more to say about Rich’s Ratio in the coming weeks. For now, we simply want to make Fed Watchers aware that they have a new series to track. Stay tuned. Ryan Swift, U.S. Bond Strategist rswift@bcaresearch.com Footnotes 1 Please see Geopolitical Strategy Weekly Report, “How Trump Became A War President”, dated May 17, 2019, available at gps.bcaresearch.com 2 Please see U.S. Bond Strategy Weekly Report, “Bond Kitchen”, dated April 9, 2019, available at usbs.bcaresearch.com 3 The rationale for why the CRB/Gold ratio tracks the 10-year Treasury yield is found in U.S. Bond Strategy Weekly Report, “The Search For Aaa Spread”, dated March 12, 2019, available at usbs.bcaresearch.com 4 Please see Global Investment Strategy Weekly Report, “Tarrified”, dated May 16, 2019, available at gis.bcaresearch.com 5 Please see U.S. Bond Strategy Weekly Report, “Paid To Wait”, dated February 26, 2019, available at usbs.bcaresearch.com Fixed Income Sector Performance Recommended Portfolio Specification

Highlights We’ve searched in vain for imminent domestic weakness in the U.S. economy, … : Much of our work this spring has focused on trying to poke holes in our view that the equilibrium fed funds rate remains above the target fed funds rate, but we haven’t found any evidence of overheating in the real economy, or worrisome excesses in financial markets. … but an exogenous shock could well precipitate a recession if it were serious enough: The U.S. is a comparatively closed economy, but there’s no such thing as full-on decoupling. The U.S. may react more slowly than other major economies to what’s going on in the rest of the world, but it’s not immune to it. A trade war would threaten global growth, … : U.S.-China trade negotiations have taken center stage over the last couple weeks, and escalating tension between the world’s two largest standalone economies will surely cast a pall over the global outlook. … but there are other potential threats that bear monitoring: Tensions with Iran could be the catalyst for an oil price shock, while a significant rollback of globalization could crimp corporate profit margins. Either would hasten the end of the equity bull market and the expansion. Feature Tight monetary policy is a necessary, if not sufficient, condition for a recession. We deem policy to be tight if the fed funds rate exceeds our estimate of the equilibrium fed funds rate, and easy if it is below our estimate of equilibrium. Over the six decades for which we compute an estimate of the equilibrium fed funds rate, the U.S. has only ever experienced recessions when the fed funds rate has exceeded our estimate of equilibrium (Chart 1). Tight policy isn’t always tantamount to a recession – nothing came of tight settings in 1984 or 1995 – but recessions don’t occur without it. Chart 1Recessions Only Occur When Monetary Conditions Are Tight We currently estimate that the equilibrium fed funds rate, a.k.a. the neutral rate, is about 3⅛%, and we continue to project that it will be around 3⅜% by the end of the year. Those estimates leave the Fed with plenty of headroom before it materially slows the economy. If our estimate is on the money, it will take four more rate hikes to induce an inflection in the business cycle. We have not seen anything in the ongoing flow of macro data, or evidence of excesses in the financial markets, that would suggest a recession is already under way or is lurking around the corner. Internal dynamics should continue to support the expansion, but threats from outside the U.S. are growing. We therefore conclude that the next recession may well not arrive for another two years, in the absence of a significantly adverse exogenous event. This week, we extend our focus beyond the U.S. to try to uncover the external threats that could stop the U.S. economy, and the bull markets in risk assets, in their tracks. Beyond the tariff fireworks, we also contemplate the possibility that conflict with Iran could lead to an oil price shock, and the impact of a significant rollback of globalization. It is not our base case that any of the various external threats will tip the U.S. into a recession, but investors should keep tabs on the biggest ones. Tariffs The U.S.-China trade saga has unfolded in three pairs of moves and counter-moves (Diagram 1). While the aggregate $50bn worth of Chinese goods tariffed in the first two salvos mostly targeted industrial equipment and machinery, the third installment, covering $200bn worth of imports, extended the tariffs’ reach to consumer products. Major categories included not only commodities such as base metals, chemical products and mineral fuels and oils, but also a broad swath of foods, textiles, electronics, vehicles and spare parts. After a three-month cease-fire, the developments of the last two weeks arguably marked the most significant escalation of tensions on both sides. The U.S. is now threatening to levy tariffs on the remaining $325bn of Chinese goods that have so far been spared. Diagram 1Anything You Can Do Our colleagues at BCA’s Geopolitical Strategy service suggest that recent foreign policy initiatives indicate that the White House does not feel any particular pressure to minimize economic risk this far ahead of the election. The risk of market-disruptive measures has therefore increased, and they see a 50-50 chance that the U.S. and China will fail to reach an accord (Table 1). Although the administration has delayed any action on autos and auto parts for now, Europe could be the next trade partner in its cross hairs. The odds that Section 232 (national-security-threat) tariffs will be levied on European auto imports is rising (Chart 2). Table 1U.S.-China Trade War: Probabilities Of A Deal By End Of June 2019 These heightened trade tensions may delay the global growth recovery that we were expecting to bloom in the summer, and they may also allow the dollar to keep advancing. The greenback is a countercyclical currency, moving inversely with global activity (Chart 3), and a bump in the road for global growth would likely extend its upward run. Chart 3The Countercyclical Dollar Although a strong dollar would be a headwind for exporters, the U.S. economy is comparatively closed. Tariffs are likely to exert the greatest pressure on the economy via softer consumption and investment. So far, the available evidence suggests that U.S. consumers and corporations have borne the brunt of higher tariffs in the form of higher retail prices and lower profit margins.1 Iran Our geopolitical strategists contend that investors have underrated conflict with Iran as a market risk for a while. Now that the contentiousness of U.S.-Iran relations has ratcheted higher upon the administration’s decision not to extend the import waivers on Iranian oil, the issue is back in the spotlight. Our strategists caution that managing the dispute may require more delicacy than the more hawkish elements of the administration realize. In their view, the potential for a misstep increases the odds of a recession and poses a significant risk to the equity bull market. In a joint Special Report by our Commodity and Energy Strategy and Geopolitical Strategy services at the beginning of the month, our in-house experts stressed that there are multiple moving parts driving the supply-demand balance in the global oil market.2 Investors should realize that the world faces the prospect of the loss of Venezuelan production (approximately 600,000 barrels per day (b/d)) and significant outages in Libya (~600,000 to 800,000 b/d), in addition to our strategists’ base-case estimate of 700,000 b/d from Iran’s current 1.3 million b/d output. BCA does not expect that all of that output will be lost, but the key point is that Iran is not the only potential source of a supply shortfall. Our energy strategists believe that OPEC 2.0 – the producer coalition led by Saudi Arabia and Russia, and supported by Saudi Arabia’s OPEC allies – has the capacity to make up for even their larger shortfall scenarios (Chart 4). The problem is that OPEC 2.0 may not have the will to do so in a timely fashion. Saudi Arabia and the rest of the OPEC 2.0 coalition were caught completely off guard by the administration’s issuance of import waivers in November, after they had ramped up production at its request to limit the market disruptions that would have ensued when Iran’s output was taken off the market. The last-minute waiver decision caused oil prices to crater in the wake of a supply glut that OPEC 2.0 has been working to sop up ever since (Chart 5). Chart 5... But The Oil Market Is Pretty Tight   OPEC 2.0’s members may feel that they were badly used last fall, and may not be inclined to move proactively now. Russia is managing its own low-grade conflict with the U.S., and all of the coalition should bear in mind that the U.S. could release over a million b/d from its Strategic Petroleum Reserve (SPR) for a solid six to nine months, according to our energy team’s estimates. If rising oil prices are often viewed as a tax on American consumers, a late summer/early fall release of holdings could be viewed as an election rebate, courtesy of the skilled economic managers in the White House. Our team expects that OPEC 2.0 will likely guard against an oversupply-driven swoon in oil prices by managing its production on something akin to a just-in-time inventory strategy. Our energy and geopolitical strategists caution that there are two other ways the administration may overplay its hand. First, it might overestimate U.S. shale drillers’ ability to export their production. While new pipeline construction will relieve the transportation bottleneck limiting the Permian Basin output that reaches the Gulf of Mexico, oil exports from the Gulf are limited by a shortage of deep-water harbor facilities. If global trade tensions do worsen, both the dollar and U.S. equities may attract safe-haven flows. There is also the possibility that Iran might strike at Iraq, putting some of its 3.5 million b/d output at risk. It could also make good on its repeated threat to close the Straits of Hormuz, through which nearly a fifth of global oil supplies travel daily. Either of these options would dramatically escalate the conflict, but a desperate Iran might pursue them if it felt cornered. The bottom line is that the probability of an oil price shock is not negligible. Brinkmanship with Iran could upset a delicate supply-demand balance in global oil markets, and a delicate geopolitical balance in the Middle East. If the Volcker double-dip is treated as a single event, a surge in oil prices has preceded every recession in the last 45 years, except for the 2001 recession precipitated by the bursting of the dot-com bubble (Chart 6). Chart 6Oil Price Spikes Often Precede Recessions Significant Rollback Of Globalization Our Geopolitical Strategy and Global Asset Allocation services have cited peak globalization as an important long-term investment theme for the last several years. The tariff tensions between the U.S. and its trading partners would seem to have borne out their predictions, especially if one views them as having been inspired by unskilled workers’ losses from globalization. Taking on foreign exporters is likely to play well in the electorally decisive Rust Belt states, where manufacturing job losses have hit especially hard. We fully subscribe to the theory of comparative advantage as formulated by David Ricardo in the early 19th century. By allowing individual countries to specialize in what they do best, free trade increases the size of the global economic pie. Empirical evidence suggests that globalization also re-slices the pie, however. In the developed world, outsourcing manufacturing has operated to the benefit of investors and the detriment of less-skilled workers. For U.S.-based multinationals, tariffs are a minor irritant compared to the prospect of having to reroute supply chains around China. The modest headwinds to globalization observed before the U.S. began engaging in serial bilateral trade conflicts did not undermine corporate profit margins in any material way. A bigger anti-globalization push that forced global supply chains to be rerouted or partially unwound would have much more negative effects. The U.S. is a comparatively closed economy, but the multinationals that dominate equity market capitalization rely heavily on interactions with the rest of the world. Unwinding the global supply chains that have been carefully constructed over the last 30 years would be disruptive and costly. The worst-case scenario envisioned by our geopolitical strategists, in which U.S.-China relations dramatically worsen and the tariff back-and-forth escalates in a major way, would hit equities hard, especially if supply chains had to be rebuilt. As a proxy for what globalization has meant for investors’ and blue-collar workers’ share of the pie, we consider the path of real wages relative to productivity over the last 50 years. From 1970 through 2001, U.S. wages generally kept pace with productivity gains, observing a fairly narrow, well-defined range (Chart 7). Once China entered the WTO (as denoted by the vertical line on the chart), productivity-adjusted wages fell precipitously, and even their periodic bounces have fallen well short of the level that marked the lower end of the previous range. Chart 7The Pie Has Grown, But Unskilled Labor's Slice Has Shrunk Bottom Line: Temporary barriers to free trade, implemented as a negotiating tactic, are not a big deal for equities. A significant rollback of globalization would be, however, and a need to divert global supply chains away from China could stop the bull market in its tracks. Investment Implications Along with our Global Investment Strategy colleagues, we are somewhat more sanguine than our Geopolitical Strategy service that a worst-case outcome between the U.S. and China can be averted. We therefore continue to believe that the U.S. expansion, and the bull markets in risk assets, will persist until the Fed tightens monetary conditions enough to spark the next recession. We reiterate our recommendations that investors should maintain at least an equal weight position in equities and spread product. Enough is at stake in the conflicts with China and Iran, however, that a worsening of either could cause us to change our view, and we will be watching developments on each front closely. Doug Peta, CFA Chief U.S. Investment Strategist dougp@bcaresearch.com Jennifer Lacombe Senior Analyst, Global ETF Strategy jenniferl@bcaresearch.com   Footnotes 1      Mary Amiti, Stephen J. Redding, and David E. Weinstein, “The Impact of the 2018 Trade War on U.S. Prices and Welfare,” NBER Working Paper No. 25672, (March 2019). 2      Please see Commodity & Energy Strategy/Geopolitical Strategy Special Report, “U.S.-Iran: This Means War?,”dated May 3, 2019, available at ces.bcaresearch.com.

Highlights U.S. Bond Strategy: U.S. Treasury yields are already priced for rate cuts and lower inflation, even as U.S. (and global) growth indicators are improving and U.S. realized inflation has ticked up. Maintain a below-benchmark stance on U.S. duration, even in the face of the current U.S.-China trade tensions. Stay overweight U.S. corporates versus Treasuries as well, with global growth indicators improving and U.S. monetary policy not yet restrictive. European Bond Strategy: Government bond yields in core Europe are too low relative to tentative signs that growth has bottomed out. At the same time, tight euro area corporate bond spreads already discount better economic momentum. Stay below-benchmark on euro area duration exposure, but maintain only a neutral weighting on euro area corporate bonds. Feature Monetary & Fiscal Policy Is More Important Than Trade Policy Chart 1Government Bonds Are Overvalued The old market bugaboo from 2018, “global trade uncertainty”, returned last week after the U.S. and China failed to reach a trade deal by last Friday’s deadline. The Trump Administration followed through on its threat to raise the tariff rate on $200 billion of Chinese exports to the U.S. from 10% to 25%, effective immediately. China retaliated by announcing fresh tariffs on $60 billion of U.S. exports to China, effective June 1st. Global equities have responded negatively, with the S&P 500 down -5% since President Trump first Tweeted his threat to increase tariffs on May 5. Global bond yields have declined in a standard risk-off move. The 10-year U.S. Treasury yield dropped -13bps over the past week - despite higher-than-expected April CPI and PPI inflation releases – and now sits at 2.40%. Meanwhile, the 10-year German Bund has dipped back into negative territory despite recent data releases showing an unexpected pickup in German industrial activity in March, and a sharp increase in Euro Area core inflation in April. Despite the greater uncertainty, we do not see a case for making any changes to our recommended pro-growth medium-term fixed income recommendations on duration (below-benchmark) or asset allocation (overweight corporates versus government debt). The BCA Global Fixed Income Strategy Duration Indicator continues to climb, indicating cyclical pressures for higher global bond yields (Chart 1). Yet at the same time, the deeply negative term premium component of yields in the U.S. and Europe (and most other developed markets) suggests that there is a lot of pessimism on growth and inflation (and a big safe-haven bid from investors) embedded in the current level of yields. Despite the greater uncertainty, we do not see a case for making any changes to our recommended pro-growth medium-term fixed income recommendations on duration (below-benchmark) or asset allocation (overweight corporates versus government debt). Our colleagues at BCA Geopolitical Strategy now believe that the odds of a trade agreement being reached this year are a 50/50 coin flip. If the talks do break down completely, however, China’s policymakers will almost certainly ramp up additional stimulus measures to offset the hit to growth from the U.S. tariffs. As a reminder, China’s exports to the U.S. only account for around 3.5% of China’s GDP (Chart 2), so U.S. tariffs matter far less than domestic stimulus via fiscal and monetary easing. Thus, any additional stimulus will help sustain the current blossoming rebound in global growth, which has been fueled in part by improved economic sentiment and a pickup in Chinese credit growth (Chart 3). In addition, Chinese import demand has ticked higher, our global leading economic indicator (LEI) is bottoming out, the ZEW surveys of economic sentiment are climbing higher and even the OECD LEI for China is starting to perk up. Chart 2China-U.S. Trade Is A Small Part Of The Two Economies Dovish central banks will also help limit the damage from increased trade uncertainty. In particular, the Fed will not rock the boat and stay “patient” by keeping rates on hold for longer. Chart 3A Consistent Message On A Global Growth Recovery Although given the inflationary implications of higher tariffs and the FOMC’s belief that the recent dip in core PCE inflation was “transitory”, the current market pricing for Fed easing appears too optimistic. Dovish central banks will also help limit the damage from increased trade uncertainty. We did get our first post-tariff read on the Fed’s thinking last Friday, and it did not sound like rate cuts were on the way. Atlanta Fed president Raphael Bostic noted that the most recent CPI and PPI inflation readings suggest that “price pressures are a little hotter” and that the U.S. is “almost to the cusp where we are going to see prices move”.1 He also noted that U.S. businesses are far more likely to pass on a higher 25% tariff on Chinese imports to consumer prices, where previously they had been more willing to absorb the higher cost of the smaller 10% tariff. Of course, an even bigger near-term selloff in global equity and credit markets is possible, if the current impasse between D.C. and Beijing persists without any indication of fresh negotiations. BCA Global Investment Strategy has recommended a tactical hedge to the overall overweight allocation to global equities in our House View matrix by shorting the S&P 500 index.2 However, we do not see the need to make any similar recommendations on the U.S. fixed income side – both the below-benchmark duration stance and the overweight corporate credit tilt - for the following reasons (Chart 4): Our Fed Monitor continues to signal that no rate cuts are required in the U.S., while -31bps of cuts over the next year are already discounted in the U.S. Overnight Index Swap curve. U.S. financial conditions have only tightened modestly on last week’s moves – after the substantial easing seen year-to-date – and still point to above-trend GDP growth over the rest of 2019. U.S. inflation expectations have dipped back to recent lows, even as realized inflation has hooked up; TIPS breakevens are now 40-50bps below levels consistent with the Fed hitting its 2% PCE inflation target. The Treasury market is now very overbought from a momentum perspective, while duration positioning is now very long according to the JPMorgan Client Survey. The reaction of U.S. corporate credit spreads to the trade headlines has been relatively muted to date (Chart 5), less than what was seen last December when the market feared a hawkish Fed policy mistake – over the medium-term, monetary policy matters more than trade policy for credit markets. Chart 4Stay Below-Benchmark U.S. Duration Chart 5A Modest Reaction (So Far) To The Tariffs In other words, U.S. Treasury yields now discount a lot of bad news and, thus, have limited downside even in the event of a further breakdown of U.S.-China trade talks. On the other hand, any positive news on fresh U.S.-China negotiations could send both equities and bond yields substantially higher and tighten credit spreads. On a risk/reward basis, a below-benchmark U.S. duration stance and overweight tilt on U.S. corporates are still warranted, even with the more elevated uncertainty on U.S.-China trade. Bottom Line: U.S. bond yields are already priced for rate cuts and lower inflation, even as U.S. (and global) growth indicators are improving and U.S. realized inflation has ticked up. Maintain a below-benchmark stance on U.S. duration, even in the face of the current U.S.-China trade tensions. Stay overweight U.S. corporates versus Treasuries as well, with global growth indicators improving and U.S. monetary policy not yet restrictive. European Bond Markets – Too Much Bad News In Yields, Too Much Good News In Credit Spreads With markets now focused on the U.S.-China trade squabble, the European economic situation is garnering few headlines. Investors may be missing out on a good story, with euro area data now more frequently surprising to the upside (Chart 6). The ZEW measures of economic sentiment have been picking up in the past few months, most notably in Germany and France, even with current conditions still perceived to be soft. Improved sentiment is where economic upturns begin, however, and it looks like better days lie ahead for European growth. Investors may be missing out on a good story, with euro area data now more frequently surprising to the upside. The 2018 downturn in euro area GDP growth was a result of a sharp downturn in exports that fed into large pullbacks in industrial production. The most recent data, however, shows that exports have started growing again, and production growth is stabilizing (Chart 7). Credit growth has also hooked up in Germany and France, while the credit contraction in Italy and Spain is bottoming out. Chart 6Upside Growth Surprises In Europe? Chart 7Starting To Reverse The 2018 Downturn The improvement in global leading indicators, such as the China credit impulse and our global LEI diffusion index, points to a rebound in euro area export growth over the latter half of the year (Chart 8). The escalation in the U.S.-China trade dispute is a potential source of concern but, as discussed earlier in this report, Chinese policymakers will likely provide additional stimulus measures to offset any hit from U.S. tariffs. This will help boost European exports to China, especially if Chinese citizens are forced to divert demand away from tariffed U.S. goods towards tariff-free European products. The likely result is that a recovery in net exports will help boost overall euro area GDP growth to an above-trend pace over the next few quarters, which could generate some surprising upside pressures on inflation. Overall euro area inflation remains well below the European Central Bank (ECB) target of “just below” 2%. Looking ahead, faster rates of inflation are more likely over the next 6-12 months (Chart 9). The early “flash” estimate for April headline HICP inflation was 1.7%, but the lagged impact of higher oil prices and a soft euro should provide a lift towards Q4/2019, boosted by faster year-over-year comparisons versus the 2018 plunge in global oil prices. The flash estimate for April also showed that core HICP inflation jumped from 1% to 1.3%. That is a large move even for a data series that has always been volatile, and there may be more signal than noise this time with wage growth also accelerating. Chart 8Exports Set To Boost European Growth Chart 9A Whiff Of Inflation? In terms of bond investment strategy, the benchmark 10yr German Bund yield looks too low according to most valuation components (Chart 10): Inflation expectations are too low relative to the rising trend in euro-denominated oil prices, and with actual inflation stabilizing. Our estimate of the term premium component of the Bund yield is also depressed, within 25bps of the deeply negative levels seen during 2015/16, when inflation was near zero and the ECB was most aggressively buying government bonds in its Asset Purchase Program. Our proxy for the market’s expectation of the real neutral short-term interest rate in the euro area - the 5-year EUR Overnight Index Swap rate, 5-years forward minus the 5-year EUR CPI swap rate, 5-years forward – is now down to -0.6%. Even allowing for modest potential growth rates in the euro area, and the persistent problems of weak profitability for European banks, such deeply negative real rate expectations discount a lot of pessimism. Similar to the story for U.S. Treasury yields laid our earlier in this report, the medium term risk/reward tradeoff for German Bund yields points to a below-benchmark duration stance as most appropriate. The upside in yields will likely come almost entirely from the inflation expectations component initially, as the ECB will maintain a dovish bias until they are convinced that the economy is indeed accelerating. Thus, we continue to recommend owning inflation protection in the euro area, either through inflation-linked bonds or CPI swaps. Similar to the story for U.S. Treasury yields laid our earlier in this report, the medium term risk/reward tradeoff for German Bund yields points to a below-benchmark duration stance as most appropriate. For spread product, a combination of improving growth, moderate inflation and stable monetary policy should be ideal for the performance of credit. Unfortunately, the robust rally in euro area corporate bonds so far in 2019 has tightened spreads to levels consistent with an accelerating economy (Chart 11). In other words, European corporate credit already discounts the faster growth that is likely to be seen later this year. Just looking at the relationship between credit and the euro area manufacturing PMI, the current level of spreads is more consistent with a PMI several points above the current soft reading that is still below the expansionary 50 line. Chart 10Stay Below-Benchmark ##br##Euro Area Duration Chart 11Stay Neutral European Corporates & Underweight BTPs We continue to recommend only a neutral allocation to euro area corporates (both investment grade and high-yield), given the competing forces of cyclical improvement but stretched valuation. As for our other major tilt in Europe, we continue to recommend a cautious, below-benchmark, stance on Italian government bonds. The indicators for the Italian economy are lagging the signs of life seen in other large euro area nations, amidst ongoing fiscal squabbles with the EU. We continue to recommend a below-benchmark stance on Italian government bonds until there is more decisive evidence of a rebound in Italian growth, signaled by a rising OECD LEI for Italy (which has been negatively correlated to Italy-German spreads over the past decade). Bottom Line: Government bond yields in core Europe are too low relative to tentative signs that growth has bottomed out. At the same time, tight euro area corporate bond spreads already discount better economic momentum. Stay below-benchmark on euro area duration exposure, but maintain only a neutral weighting on euro area corporate bonds.   Robert Robis, CFA, Chief Fixed Income Strategist rrobis@bcaresearch.com Footnotes 1https://www.bloomberg.com/news/articles/2019-05-09/fed-s-bostic-warns-consumers-may-feel-hit-on-china-tariff-boost 2 Please see BCA Global Investment Strategy Special Alert, “Stay Cyclically Overweight Global Equities, But Hedge Near-Term Downside Risks From An Escalation Of A Trade War”, dated May 10th 2019, available at gis.bcareseach.com. Recommendations Duration Regional Allocation Spread Product Tactical Trades Yields & Returns Global Bond Yields Historical Returns

Special Report

We continue to recommend being overweight global equities and other risk assets over a horizon of 12 months. However, the apparent failure of trade talks between China and the U.S. to gain much traction poses near-term downside risks to our bullish thesis. At this point, our geopolitical team feels that the conclusion of an actual trade agreement this year is a 50/50 prospect. It is easy to envision a scenario where the Trump Administration pursues its “maximum pressure” doctrine in the hopes of wrangling out more concessions. For their part, the Chinese, rather than making sweeping reforms to their legal system as the Trump Administration is insisting, could simply choose to bide their time in the hopes that Joe Biden, an avowed free trader, becomes the next U.S. president. Ultimately, as discussed in this week’s Global Investment Strategy report, in a worst-case scenario where the trade talks break down completely, the combination of aggressive Chinese stimulus and a still-dovish Fed will likely preclude a major global economic downturn. Nevertheless, a 5% correction in global equities from current levels is entirely possible, especially in light of the strong rally since the start of the year. With this in mind, we are putting on a hedge to short the S&P 500 index. We will remove the hedge if stocks fall 5% or trade talks shift in a more positive direction. Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com

Special Report

We continue to recommend being overweight global equities and other risk assets over a horizon of 12 months. However, the apparent failure of trade talks between China and the U.S. to gain much traction poses near-term downside risks to our bullish thesis. At this point, our geopolitical team feels that the conclusion of an actual trade agreement this year is a 50/50 prospect. It is easy to envision a scenario where the Trump Administration pursues its “maximum pressure” doctrine in the hopes of wrangling out more concessions. For their part, the Chinese, rather than making sweeping reforms to their legal system as the Trump Administration is insisting, could simply choose to bide their time in the hopes that Joe Biden, an avowed free trader, becomes the next U.S. president. Ultimately, as discussed in this week’s Global Investment Strategy report, in a worst-case scenario where the trade talks break down completely, the combination of aggressive Chinese stimulus and a still-dovish Fed will likely preclude a major global economic downturn. Nevertheless, a 5% correction in global equities from current levels is entirely possible, especially in light of the strong rally since the start of the year. With this in mind, we are putting on a hedge to short the S&P 500 index. We will remove the hedge if stocks fall 5% or trade talks shift in a more positive direction. Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com

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.