Technical

In lieu of the next weekly report I will be presenting the quarterly webcast ‘Leaving The Euro Would Be MAD, But Mad Things Can Happen’ on Thursday 14 May at 10.00AM EDT (3.00PM BST, 4.00PM CEST, 10.00PM HKT). As usual, the webcast will take a TED talk format lasting 18 minutes, followed by live questions. Don’t miss it. Highlights For the time being, stick with the very successful strategies of: Overweighting higher yielding US T-bonds versus negative yielding German bunds and Swiss bonds. Overweighting technology and healthcare versus banks and materials. Overweighting growth versus value. Overweighting the S&P 500 versus the Eurostoxx 50. Overweighting Germany, France, and Switzerland in a European equity portfolio. The big caveat is that these strategies are highly correlated. Fractal trade: long euro area personal products versus healthcare. Feature Chart I-1Bond Yields And Commodity Prices Are Correlating To One Bond Yields And Commodity Prices Are Correlating To One Bond Yields And Commodity Prices Are Correlating To One Chatting with friends, family and clients it seems that our lives under lockdown and social distancing have lost much of their differentiation across time and space. Wherever in the world we live, whatever we do, our days and lives are correlating to one. Interestingly, the financial markets have experienced a similar loss of differentiation. In the coronavirus world, markets are also correlating to one. Financial Markets Are Not Complicated One of our abiding investment mantras is that: Financial markets are complex, but they are not complicated. The words complex and complicated are sometimes used synonymously, but they mean different things. Complex means something that is not fully predictable or analysable. Complicated means something that is made up of many parts. Financial markets are not complicated. The financial markets are not complicated because a few parts drive the relative prices of everything, though these parts themselves are complex. Identify and understand these few parts and you will get all your investment decisions right: asset allocation, sector allocation, style allocation, regional allocation, country allocation. This has become even more so this year as our response to the coronavirus has correlated all our lives and economic behaviour to one. One fundamental part is the bond yield. The collapse in commodity prices, more than any other real-time indicator, illustrates the demand destruction resulting from coronavirus-induced lockdowns and social distancing. Bond yields have plunged in lockstep with this demand destruction, given the implications for higher unemployment as well as lower inflation – the two key tenets that drive central bank policy (Chart of the Week). The plunging bond yield, in turn, has driven the underperformance of banks (Chart I-2), for two reasons. First, to the extent that a depressed bond yield reflects a low-growth economy, it also reflects a poorer outlook for bank credit growth, which effectively constitutes a bank’s ‘sales’. Second, a depressed bond yield means a flat or inverted yield curve, which squeezes bank net interest (profit) margins. Chart I-2Banks And Bond Yields Are Correlating To One Banks And Bond Yields Are Correlating To One Banks And Bond Yields Are Correlating To One Conversely, the plunging bond yield has signified an environment in which big tech and healthcare equities outperform (Chart I-3 and Chart I-4), also for two reasons. First, big tech and healthcare sales are more protected against a sudden dip in the economy. Second, their cashflows are weighted further into the future, and so their ‘net present values’ rise more when bond yields plunge. Chart I-3Tech (Inverted) And Bond Yields Are Correlating To One Tech (Inverted) And Bond Yields Are Correlating To One Tech (Inverted) And Bond Yields Are Correlating To One Chart I-4Healthcare (Inverted) And Bond Yields Are Correlating To One Healthcare (Inverted) And Bond Yields Are Correlating To One Healthcare (Inverted) And Bond Yields Are Correlating To One A declining bond yield also signifies an environment in which basic materials equities underperform, as our first chart powerfully illustrates. So, if you call the bond yield right, you will get your asset allocation between cash and bonds right, but you will also your equity sector allocation right. And if you get your equity sector allocation right you will automatically get your value versus growth style allocation right too. At an overarching level, the value versus growth allocation is nothing more than the performance of value sectors, like banks, versus growth sectors, like big tech and healthcare (Chart I-5). Chart I-5Value Versus Growth = Banks Versus Tech Value Versus Growth = Banks Versus Tech Value Versus Growth = Banks Versus Tech Furthermore, you will also get your regional and country allocation right. This is because each major stock market has distinguishing ‘long’ sectors in which it contains up to a quarter of its total market capitalisation, as well as distinguishing ‘short’ sectors in which it has a significant under-representation. The combination of this long sector and short sector gives each equity index its distinguishing fingerprint which drives relative performance (Table I-1): Table I-1The Sector Fingerprints Of Major Regional Stock Markets Markets Are Correlating To One Markets Are Correlating To One FTSE 100 = long financials and energy, short technology. Eurostoxx 50 = long financials, short technology and healthcare. Nikkei 225 = long industrials, short financials and energy. S&P 500 = long technology and healthcare, short materials. MSCI Emerging Markets = long financials, short healthcare. Specifically, the distinguishing fingerprints of the Eurostoxx 50 and the S&P 500 mean that the Eurostoxx 50 has a 12 percent over-representation to financials and materials at the expense of an 18 percent under-representation to technology and healthcare. It follows that if banks and materials underperform technology and healthcare, the Eurostoxx 50 must underperform the S&P 500. Everything else is irrelevant (Chart I-6). Chart I-6Euro Area Versus US = Banks Versus Tech Euro Area Versus US = Banks Versus Tech Euro Area Versus US = Banks Versus Tech The same principle applies to the stock markets within Europe. Relative performance comes from nothing more than the stock market’s long and short sector fingerprint combined with sector performance (Table I-2 and Table I-3). Table I-2The Sector Fingerprints Of Euro Area Stock Markets Markets Are Correlating To One Markets Are Correlating To One Table I-3The Sector Fingerprints Of Non Euro Area European Stock Markets Markets Are Correlating To One Markets Are Correlating To One For example, if healthcare outperforms then its overrepresentation in the stock markets of Switzerland and Denmark means that they must outperform too (Chart I-7 and Chart I-8). Likewise, if technology outperforms, then the technology-heavy Netherlands stock market must outperform (Chart I-9). Chart I-7Long Switzerland = Long Healthcare Long Switzerland = Long Healthcare Long Switzerland = Long Healthcare Chart I-8Long Denmark = Long Healthcare Long Denmark = Long Healthcare Long Denmark = Long Healthcare Chart I-9Long Netherlands = Long Tech Long Netherlands = Long Tech Long Netherlands = Long Tech All Investment Strategies Are Highly Correlated To repeat, financial markets are not complicated. If you get the over-arching decision(s) right, you will get everything right. The unfortunate corollary is that if you get the over-arching decision wrong you will get everything wrong. Asset allocation, sector allocation, style allocation, regional allocation, and country allocation are correlating to one. We really wish that financial markets were more complicated – because then asset allocation, sector allocation, style allocation, regional allocation and country allocation would be independent investment decisions which offered diversification at the total portfolio level. But the charts in this report should make it crystal clear that all these separate decisions are correlating to one. They are all really the same decision. Today, the decision on where bond yields are headed is particularly tough because they have already come down a lot in a very short space of time. Yet we do not foresee a sustained backup in yields for three reasons: First, even if governments ease lockdowns and reopen economies, demand will remain depressed. Most people are isolating themselves or socially distancing not because their governments are forcing them to, but because they fear infection. The easing of lockdowns, per se, will not remove that fear. And if workers are forced back into jobs when it is unsafe, then infection rates will start to rise again. Second, unless commodity prices rise sharply in the coming months the base effect of commodity prices will put downward pressure on 12-month inflation rates later in the summer (Chart I-10). To the extent that central banks focus on – and target – these totemic annual inflation rates, it will be very difficult to turn hawkish. On the contrary, there may be pressure to turn even more dovish. Chart I-10The Base Effect Will Weigh On Inflation Later This Year The Base Effect Will Weigh On Inflation Later This Year The Base Effect Will Weigh On Inflation Later This Year Third, our most trusted technical indicator is not flashing the red signal that bonds are dangerously overbought, as they were in January 2019, August 2019, and early-March 2020 (Chart I-11). Chart I-11Bonds Are Not Yet At A Technical Tipping Point Bonds Are Not Yet At A Technical Tipping Point Bonds Are Not Yet At A Technical Tipping Point So, for the time being, we are sticking with the very successful strategies of: Overweighting higher yielding US T-bonds versus negative yielding German bunds and Swiss bonds. Overweighting technology and healthcare versus banks and materials. Overweighting growth versus value. Overweighting the S&P 500 versus the Eurostoxx 50. Overweighting Germany, France, and Switzerland in a European equity portfolio. The big caveat is that these strategies are highly correlated. Fractal Trading System* With markets correlating to one, it is becoming more difficult to find trades which are not correlated with the over-arching driver. Hence, this week’s recommended trade is a pair-trade between two defensive sectors: long euro area personal products versus healthcare. The profit target is 7 percent, with a symmetrical stop-loss. The rolling 1-year win ratio now stands at 61 percent. Chart I-12Euro Area Personal Products Vs. Health Care Euro Area Personal Products Vs. Health Care Euro Area Personal Products Vs. Health Care When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. * For more details please see the European Investment Strategy Special Report “Fractals, Liquidity & A Trading Model,” dated  December 11, 2014, available at eis.bcaresearch.com.   Dhaval Joshi Chief European Investment Strategist dhaval@bcaresearch.com Fractal Trading System   Cyclical Recommendations Structural Recommendations Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations Indicators To Watch - Interest Rate Expectations

Highlights Why is the gap between the stock market and the economy so wide?: It is well established that stocks can diverge considerably from fundamentals in the near term, but lately it is as if the stock tables and the front-page headlines are from entirely different newspapers. It may be because the virus poses much less of a threat to the owners of equities than the general populace: More affluent households are more readily able to work from home and to practice social distancing. They also have access to better medical care. With the S&P 500 having hit technical resistance, however, the gap may be nearing its upper limit: Large-caps have run in place since retracing half of their peak-to-trough losses, and the next Fibonacci resistance level is only another 5% higher. Where are the shoddy loans?: During the expansion, corporations were able to borrow on prodigally easy terms. If banks aren't holding the loans, who is? Feature That’s New York’s future, not mine – “Hold On” (Reed) For someone who entered the business as a sell-side trader, it is a matter of course that prices can diverge from fundamentals. The trading desk had a one-day horizon, and the traders necessarily made their way on price signals while barely considering fundamentals. Though the junior traders had been exposed to dividend discount models at their fancy colleges, the ones who lasted recognized they weren’t relevant to the desk’s mission. Trading the daily flow required accepting that new news can have a dramatically larger effect on stocks in the here and now than it would on the lifetime stream of earnings available to common shareholders. Long-run fair value might solely turn on the fundamentals, but animal spirits hold sway over any given tick. The sudden stop imposed by stay-at-home orders has made backward-looking economic data nearly irrelevant, but the sizable upward surprises in unemployment claims should not be ignored. Our Global Investment Strategy colleagues showed last week just how difficult it is for even severe near-term shocks to materially alter the present value of aggregate future earnings.1 Furthermore, the market effects of negative earnings shocks are inherently self-limiting at the margin because they tend to be accompanied by lower interest rates, driving up the equity risk premium and making stocks more attractive relative to “safe” fixed income alternatives. Bear markets coincide with recessions, though, as near-term earnings expectations are revised lower and animal spirits droop (Chart 1). Given that the recession just begun is expected to be the worst since the Great Depression, one would expect that equities would be stumbling in search of a bottom as investors remained fearful of taking on risk. Chart 1Joined At The Hip Joined At The Hip Joined At The Hip They have instead been acting like the S&P 500 found that bottom on March 23rd, when the index completed a 35% peak-to-trough decline in just 23 sessions. It then proceeded to gain 28.5% over the next eighteen sessions. Some retracement is to be expected after a sudden, sharp move, and the S&P 500 has only recovered half of the ground that it lost. It certainly priced in a great deal of bad news on the way down, but the data have been worsening, and investors have been forced to give up on the notion of a swift economic recovery. Why are stocks rising when economic projections are being downwardly revised and good virus news has been few and far between? We ourselves have been barely glancing at backward-looking economic data releases that merely confirm the well-understood fact that draconian social distancing measures have wrung much of the life out of the economy. The degree to which job losses have outrun consensus forecasts stands out nonetheless. Aggregate initial unemployment claims over the last five weeks have exceeded consensus expectations by 5.5 million (Table 1). Even though the forecasts have caught up to the situation on the ground, the claims data suggest that unemployment is now pushing 20%, a worst-case-scenario level that is far above the first forecasts that incorporated the effects of stay-at-home orders. Claims may well have peaked, but they’re still an order of magnitude higher than normal, and they are not finished exerting upward pressure on the unemployment rate. Table 1Job Losses Have Been Worse Than Expected Dichotomy Dichotomy Meanwhile, COVID-19 data have yet to provoke much optimism. The rate of US infections has yet to come down to Italy’s level (Chart 2), and hopes that remdesivir might prove to be a wonder drug were dashed late last week. Clients are increasingly asking us why the stock market is traveling such a dramatically different path than the economy and the virus. How could stocks have plunged at a record rate as the coronavirus drew a bead on the United States, but surged after crippling social distancing measures were put in place? Chart 2The US Has Fallen Behind Italy's Pace Dichotomy Dichotomy A Tale Of Two Boroughs The simplest answer is that the Fed’s response was swifter and more far-reaching than expected. Ditto Congressional actions, and we expect that DC will continue to deploy its fiscal firepower to try to shield households and businesses from the worst of the effects of the anti-virus measures. We believe the monetary and fiscal efforts will make a difference, and do not think it’s a coincidence that equities turned around the week of March 23rd, which began with the Fed’s rollout of a formidable new arsenal and ended with the passage of the CARES Act. But the market action has not accounted for the shift from expectations of a V-bottom to talk of Us, Ls and Ws. Two articles published a week apart in The New Yorker vividly illustrated a demographic virus gap. The first looked at COVID-19 from the perspective of financial professionals at hedge funds and other sophisticated investment aeries.2 Although the views of the investors in the profile shifted with the tide of the incoming data, they were generally of the mind that the health threat was being dramatically overhyped. One retired hedge fund manager boasted about his and his family’s non-stop early March air travel between New York, London and a Wyoming ski resort. The second article followed an emergency room resident at Elmhurst, a publicly funded hospital in a working-class Queens neighborhood, which has been described as the epicenter of the outbreak in several local media reports.3 “‘It’s become very clear to me what a socioeconomic disease this is,’” he said. “‘Short-order cooks, doormen, cleaners, deli workers – that is the patient population here. Other people were at home, but my patients were still working. A few weeks ago, when they were told to socially isolate, they still had to go back to an apartment with ten other people. Now they are in our cardiac room dying.’” Stock ownership is largely reserved to the affluent, with the top percentile of households owning 53% of equities as of the end of 2019, and the rest of the top decile owning another 35% (Chart 3). For households in the top decile, maintaining a healthy distance from the virus isn’t that difficult. Knowledge workers equipped with a laptop and a reliable internet connection can work from anywhere, unlike the Elmhurst patients in low-skilled service positions who have to work onsite. The tonier precincts of Manhattan feel nearly deserted, with their residents having decamped for second homes in lower-density areas. Perhaps it's because the Fed's attempts to shore up the economy have far more personal relevance for investors than the spread of the virus. There are no comprehensive data series on virus infections and outcomes by zip code, which would facilitate analysis of the link between household wealth and COVID-19, but New York state reports age-adjusted fatality rates in four racial/ethnic categories. In New York state ex-New York city, which has lesser extremes of wealth than the city itself, the cross-category disparities are striking (Chart 4). Race/ethnicity is far from an ideal proxy for inequality, but it is fair to conclude that financial market participants have a sound basis for being more sanguine about the virus than the overall population. Assuming that more affluent households will be able to remain out of the virus’ reach, the dichotomy can persist for as long as the economic impacts do not become so bad that investors cannot reasonably look through them. Chart 3Demographics Drive Stock Ownership ... Dichotomy Dichotomy Chart 4... And COVID-19 Fatalities Dichotomy Dichotomy Technical Resistance Back on the trading desk, technical analysis was the go-to tool for traders pricing large blocks of stock in real time. Following sizable moves, the Fibonacci sequence provided a popular method for assessing how far a stock might retrace its steps before resuming its course. The most widely used Fibonacci retracement levels are 38% and 62%, and 50%, a round number exactly between the two, has also become an anticipated stopping point. From the February 19 closing high of 3,386.15 to the March 23 closing low of 2,237.40, the S&P 500 lost 1,148.75 points. The 38%, 50% and 62% retracement levels are 2,673.93, 2,811.78 and 2,949.63, respectively. The S&P paused at the 38% level for just two days before breaking through it decisively, but it’s had more trouble making its way through 2,812, failing to hold above it for more than a day or two at a time (Chart 5). Should it escape 2,812, the 2,950 level waits just 5% higher. Chart 5Fibonacci Retracement Levels For The S&P 500 Fibonacci Retracement Levels For The S&P 500 Fibonacci Retracement Levels For The S&P 500 We are fundamental investors who do not get hung up on technical levels, though they can become self-fulfilling prophecies if enough participants are following them. Given the popularity of Fibonacci retracement, it is possible that a critical mass of short-term investors may view 2,812 and 2,950 as preferred levels for exiting long positions in the S&P. Our bigger near-term concern is that it is hard to see US equities making much more headway while the virus and ongoing distancing measures have the potential to cause investors to revise their fundamental expectations lower and/or lose a little bit of their policy-fueled nerve. Who's Left Holding The Bag? Multiple commentators have expressed alarm at the post-2008 increase in corporate debt, especially given anecdotal reports that lending covenants had been loosened dramatically. If the banks don’t hold the debt, as we’ve argued, who does, and could a wave of virus-inspired defaults cause larger problems in the financial system? The Fed’s fourth quarter Flow of Funds report, published last month, provides some clues, but does not answer the question definitively. As we saw in higher frequency data on aggregate banking system exposures, bank loans to nonfinancial corporations grew modestly (3.2% annualized) since December 31, 2008. Nonfinancial corporations borrowed in the bond market at double that rate (6.2% annualized). Foreign loans, powered by near doubling in 2017 and 2018, grew at an annualized 13.4% pace, and are four times as large as they were at the end of 2008. Finance company loans have shrunk, and trade payables grew at a modest 2% rate. (Chart 6). Chart 6Debt Risks Are Pretty Well Diffused Dichotomy Dichotomy Publicly available data from Preqin on the capital raised by direct lending funds suggests that their impact has been modest, accounting for only about a quarter of outstanding bank loans if every dollar they’ve raised is currently deployed. Demand for leveraged loans, senior floating-rate debt issued to high-yield borrowers, was occasionally intense as investors sought protection from rising rates. The desire for duration protection has faded as rates have plunged to new lows, but ETFs and CLOs were eager buyers at points during the last expansion. In a Special Report published last summer, our US Bond Strategy and Global Fixed Income Strategy services concluded that the ownership of leveraged loans is diffuse enough that credit strains are unlikely to pose a systemic threat. They were also encouraged that leveraged loans and high yield corporate bonds act as substitutes, keeping one another in check as investor preferences for fixed and floating instruments wax and wane. They also noted that leveraged loan lending standards had tightened last year, with a reduced share of covenant-lite loans being issued, though standards have eased again since they published their report (Chart 7). Chart 7Covenant Protections Have Eroded Covenant Protections Have Eroded Covenant Protections Have Eroded Chart 8Diverse Corporate Bond Ownership Will Help Mitigate The Effect Of Defaults Dichotomy Dichotomy There is no way around the fact that high yield corporate bondholders (Chart 8), owners of CLO tranches rated below AAA and leveraged loan holders face elevated credit losses as the broad economic shutdown provokes a wave of defaults in instruments without Fed support. We expect that the default losses will be spread out across enough constituents that they will not become worryingly concentrated, but they may contribute to a further erosion of risk appetites.       Doug Peta, CFA Chief US Investment Strategist dougp@bcaresearch.com Footnotes 1 Please see the April 23, 2020 Global Investment Strategy Weekly Report, "Could The Pandemic Actually Raise Stock Prices?" available at gis.bcaresearch.com. 2 Paumgarten, Nick. "The Price of a Pandemic." The New Yorker, April 20, 2020, pp. 20-24. The article, relaying traders’ conversations, contains some profanity. 3 Galchen, Rivka. "The Longest Shift." The New Yorker, April 27, 2020, pp. 20-26. The article, relaying ER conversations, contains some profanity.

Highlights Please note that we published a Special Report early this week titled Brazilian Banks: Falling Angels, and an analysis on India. Please also note that we are publishing an analysis on Indonesia below. Given uncertainty over the depth and duration of the unfolding global recession, a sustainable equity bull run is now unlikely. It is still early to lift EM equity and EM credit allocations from underweight to overweight within global equity and global credit portfolios, respectively. EM currencies and EM fixed-income markets will remain under selling pressure. Feature The question investors now face is whether the recent rebound will endure for a few months or it will just be a bear market rebound that is already fading. BCA’s Emerging Market Strategy service believes it is the latter. EM and DM share prices will likely make new lows.  A Tale Of Two Charts Chart I-1and I-2 overlay the current S&P 500 selloff with the market crashes of 1987 and 1929, respectively. The speed and ferocity of the current selloff is on a par with both. In 1987, following the 33% crash, share prices rebounded 14% but then relapsed without breaking below previous lows (Chart I-1). That was a hint that US share prices were entering a major bull market that indeed ensued. We do not know if the S&P 500 will make a lower low, but a retest of the recent lows is very likely. In 1929, US share prices collapsed by 36% over several weeks. Then, the overall index staged an 18% rebound within a couple of weeks, rolled over and plunged to new lows. The magnitude of the second downleg was 27% (Chart I-2). Chart I-1S&P 500: Now Versus 1987 S&P 500: Now Versus 1987 S&P 500: Now Versus 1987 Chart I-2S&P 500: Now Versus 1929 S&P 500: Now Versus 1929 S&P 500: Now Versus 1929   Fast forward to today, the S&P 500 plummeted 34% in a matter of only four weeks and then staged a 17.5% rebound in only a few days. We do not know if the S&P 500 will make a lower low, but a retest of the recent lows is very likely. In fact, we are assigning a higher probability to share prices in EM and DM breaking down to new lows than for the recent lows to hold. Chart I-3S&P 500: Now Versus 1929-32 S&P 500: Now Versus 1929-32 S&P 500: Now Versus 1929-32 Readers may question why we are comparing the current episode with the 1929 bear market. The argument against this comparison stresses that policymakers made numerous mistakes between 1929 and 1932, refusing to ease policy even after the crisis commenced. That led to debt deflation and a banking crisis, which in turn produced a vicious equity bear market of 85% lasting 3 years. At present, authorities around the world have reacted swiftly, providing enormous fiscal and monetary stimulus. We agree with this reasoning, but our point is as follows: Due to the US’s ongoing aggressive and timely policy response, stocks will avoid the protracted second phase of the 1930-‘32 bear market when share prices plummeted by another 80% (Chart I-3). Nonetheless, the US equity market could still repeat what occurred in the initial part of the 1929 bear market, as illustrated in Chart I-2 and Chart I-3. The Fundamentals The basis for our expectations of continued weakness in share prices is as follows: The selloff in the S&P 500 began from overbought and expensive levels (Chart I-4). The duration of the selloff so far has been only four weeks. We doubt that such a short, albeit vicious, selloff was enough to clear out valuation and positioning excesses. For example, even though by March 24 net long positions in US equity futures had dropped significantly, they were still above their 2011 and 2015/16 lows (Chart I-5). Chart I-4S&P 500: Correcting From Expensive Levels S&P 500: Correcting From Expensive Levels S&P 500: Correcting From Expensive Levels Chart I-5Net Long Positions In US Equity Indexes Futures Net Long Positions In US Equity Indexes Futures Net Long Positions In US Equity Indexes Futures   Besides, US equity valuations are still elevated. The cyclically adjusted P/E ratio for the S&P 500 – based on operating profits – is 25 compared with its historical mean of 16.5, as demonstrated in the top panel of Chart I-4. While this valuation model does not take into account interest rates, our hunch is as follows: facing such high uncertainty over the profit outlook, investors will require higher than usual risk premiums to invest in equities. In short, the ongoing profit collapse and the extreme uncertainty over the cyclical outlook heralds a higher risk premium. The discount rate – which is the sum of the risk-free rate and risk premium – presently should not be lower than its average over the past 20 years. We are experiencing a sort of natural disaster, and there is little policymakers can do amid lockdowns. Natural disasters require time to play out, and financial markets are attempting to price in this downturn.  Most stimulus measures taken worldwide to boost demand will only gain traction after the lockdowns are over. At the moment, global output and demand remain in freefall. The recovery will be hesitant and is unlikely to be V-shaped for two reasons: (1) social distancing measures will be eased only gradually; and (2) the lost household income and corporate profits from weeks and months of shutdowns will continue to weigh on consumer and business sentiment and their spending patterns for several months. China’s economy is a case in point. Both manufacturing and services PMIs for March posted readings in the 50-52 range. These are rather underwhelming numbers. Following stringent lockdowns in February when the level of economic output literally collapsed, only 52% of companies surveyed reported an improvement in their business activity/new orders in March relative to February. Chart I-6Our Reflation Confirming Indicator Is Downbeat Our Reflation Confirming Indicator Is Downbeat Our Reflation Confirming Indicator Is Downbeat If true, these PMI readings imply a level of output and demand in China that is still well below March 2019 levels. It seems China has not been able to engineer a V-shaped recovery in demand and output. Therefore, the odds are that, outside China, economic activity will come back only slowly. This entails that some businesses will not reach their breakeven points anytime soon, and that their profits will be contracting for some time to come. We do not think this is reflected in today’s asset prices.       Finally, our Reflation Confirming Indicator – which is composed of equally-weighted prices of industrial metals, platinum and US lumber – is pointing down (Chart I-6). Bottom Line: This bear market has been ferocious, but too short in duration. It is unlikely that share prices have already bottomed, given uncertainty over the depth and duration of the unfolding global recession. EM Versus DM: Stay Underweight Chart I-7EM Versus DM: Relative Equity Prices EM Versus DM: Relative Equity Prices EM Versus DM: Relative Equity Prices EM stocks have failed to outperform DM equities in the recent rebound. As a result, EM versus DM relative share prices are testing new lows (Chart I-7). Odds are that EM will underperform DM in the coming weeks or months. Outside North Asian economies (China, Korea and Taiwan), EM countries have less capacity to deal with the COVID-19 pandemic than advanced countries. First, health care systems in developing countries are far less equipped to deal with the pandemic than DM ones. Chart I-8 shows the number of hospital beds per 1,000 people in India, Indonesia, Brazil and Mexico are significantly lower than in Europe and the US. Chart I-8Many EMs Have Poor Health Infrastructure Downside Risks Prevail Downside Risks Prevail Second, EM ex-North Asian economies lack both the social safety net of Europe and the US’s capacity to inject large amounts of fiscal and monetary stimulus into the system. With the US dollar being the world reserve currency, the US has no problem monetizing its public debt and fiscal deficits. The same is true for the European Central Bank (ECB). If current account-deficit EM countries following in the footsteps of the US and monetize fiscal deficits/public debt, their currencies will likely depreciate. Last week, the South African central bank announced that it will buy local currency government bonds to cap their yields and inject liquidity into the system. This is of little help to foreign investors in domestic bonds because the rand has continued to sell off, eroding the US dollar value of their government bond holdings. Hence, the foreign investor exodus from the local currency bond market will likely continue. The same would be true for many other EM countries if they contemplate QE-type policies. Most stimulus measures taken worldwide to boost demand will only gain traction after the lockdowns are over. Third, unlike the Fed and the ECB, EM ex-North Asia central banks have limited capacity to alleviate funding stress for their companies. The Fed is also purchasing investment-grade corporate bonds and is setting up structures to channel credit to companies. All of this will marginally help ease financial and credit stress in the US. In contrast, central banks in EM ex-North Asia are unlikely to adopt similar policies on a comparable scale as the US. While DM countries do not mind seeing their currencies depreciate, authorities in many developing countries are fearful of further depreciation. The latter will inflict more stress on EM companies and banks that have large foreign currency debt. We will publish a report on EM foreign currency debt next week. Further, corporate bonds in DM are issued in local currency, allowing their central banks to purchase corporate bonds in unlimited quantities by creating money “out of thin air.” Chart I-9EM Performance Correlates With Commodities EM Performance Correlates With Commodities EM Performance Correlates With Commodities In contrast, outside of China and Korea, the majority of EM corporate bonds are issued in US dollars. This means that to bring down their corporate US borrowing costs, central banks in developing countries need to spend their finite US dollar reserves. Finally, commodities prices are critical to EM financial markets’ absolute and relative performance (Chart I-9). The outlook for commodities prices remains dismal. As the global economy has experienced a sudden stop, demand for raw materials and energy has literally evaporated. Liquidity provisions by the Fed and other key central banks may at a certain point help financial assets but will not help commodities. The basis is that demand for equities and bonds is entirely driven by investors, but in the case of commodities a large share of demand comes from the real economy. In bad times like these, central banks’ liquidity provisions can at a certain point persuade investors to look through the recession and begin buying financial assets before the real economy bottoms. In the case of commodities, when real demand is collapsing, financial demand will not be able to revive commodities prices. Bottom Line: It is still early to lift EM equity and EM credit allocations from underweight to overweight within global equity and global credit portfolios, respectively. Technicals: Old Support = New Resistance? Calling tops and bottoms in financial markets is never easy. When formulating investment strategy it is helpful to examine both market price actions and other subtle clues that financial markets often provide. The global equity index and global industrial stocks have rebounded to levels that acted as supports during previous selloffs. We have detected the following patterns that suggest the recent rebound is facing major resistance, and new lower lows are likely: The global equity index and global industrial stocks have rebounded to levels that acted as supports during previous selloffs (Chart I-10). Unless these equity indexes decisively break above these lines, the odds favor retesting their recent lows or even falling to new lows. Many other equity indexes and individual stocks are also displaying similar technical patterns. The Korean won versus the US dollar as well as silver prices exhibit a similar technical profile (Chart I-11). Chart I-10Ominous Technical Signals Ominous Technical Signals Ominous Technical Signals Chart I-11New Lows Ahead New Lows Ahead New Lows Ahead   Global materials have decisively broken below their long-term moving average that served as a major support in 2002, 2008 and 2015 (Chart I-12). The same multi-year moving average is now likely to act as a resistance. Hence, any rebound in global materials stocks – that extremely closely correlate with EM share prices – is very unlikely to prove durable until this support-turned-resistance level is decisively breached. US FAANGM (FB, AMZN, APPL, NFLX, GOOG, MSFT) equally-weighted stock prices have dropped below their 200-day moving average that served as a major support in recent years (Chart I-13). They did rebound but have not yet broken above the same line. Odds are that this line will become a resistance. If true, this will entail new lows in FAANGM stocks. Chart I-12Global Materials Broke Below Their Long-Term Defense Line Global Materials Broke Below Their Long-Term Defense Line Global Materials Broke Below Their Long-Term Defense Line Chart I-13FAANGM: Previous Support Has Become New Resistance FAANGM: Previous Support Has Become New Resistance FAANGM: Previous Support Has Become New Resistance   Bottom Line: Various financial markets are exhibiting technical patterns consistent with retesting recent lows or making lower lows. Stay put. Arthur Budaghyan Chief Emerging Markets Strategist arthurb@bcaresearch.com   Indonesia: A Fallen Angel Chart II-1Indonesian Equities Are In Freefall In Absolute & Relative Terms Indonesian Equities Are In Freefall In Absolute & Relative Terms Indonesian Equities Are In Freefall In Absolute & Relative Terms Indonesian stock prices are in freefall - both in absolute terms and relative to EM - with no visible support (Chart II-1). We recommend that investors maintain an underweight position in both Indonesian equities and fixed-income and continue to short the rupiah versus the US dollar. We explain the reasoning behind this recommendation below. First, the key vulnerability of Indonesian financial markets is that they had been supported by massive foreign inflows stirred by falling US interest rates, despite deteriorating domestic fundamentals and falling commodities prices. We discussed this at length in our previous reports. However, the COVID-19 pandemic has brought these weak fundamentals to light. The latter have overshadowed falling US interest rates (Chart II-2) triggering an exodus of foreign portfolio capital and a plunge in the exchange rate. Currency depreciation has in turn mounted foreign investors losses resulting in a vicious feedback loop. As of the end of February, foreigners held about 37% of local currency bonds. Meanwhile, they held 56% of equities as of last week. Ongoing currency weakness and continued jitters in global financial markets will likely generate more foreign capital outflows.                    Second, the Indonesian economy - both domestic demand and exports - were already weak even before the breakout of COVID-19 occurred (Chart II-3).  Chart II-2Indonesia: Falling US Rates Stopped Mattering Indonesia: Falling US Rates Stopped Mattering Indonesia: Falling US Rates Stopped Mattering Chart II-3Indonesia: Domestic Demand Was Weak Before COVID-19 Outbreak Indonesia: Domestic Demand Was Weak Before COVID-19 Outbreak Indonesia: Domestic Demand Was Weak Before COVID-19 Outbreak   Chart II-4Indonesia: Struggling Under High Lending Rates Indonesia: Struggling Under High Lending Rates Indonesia: Struggling Under High Lending Rates With imposition of social distancing measures, output and nominal incomes will contract (Chart II-4). Third, the nation’s very underdeveloped health care system makes it more vulnerable to a pandemic compared to other mainstream EM countries. For example, the number of hospital beds per 1000 people - at 1.2 - is among the lowest within the mainstream EM universe. We discuss this issue for EM in greater detail in our most recent weekly report. In brief, it will take a longer time for this nation to overcome the pandemic and get its economy back on track. Fourth, Indonesia - as with many EM countries - is short on both social safety programs and fiscal stabilizers that are available in North Asian countries, Europe and the US. Moreover, the country lacks the administrative system needed to promptly execute fiscal stimulus. Besides, the economic stimulus announced by the Indonesian authorities is so far insufficient to meaningfully moderate the economic blow. The government announced a fiscal stimulus that barely amounts to 1% of GDP. This will do little to counter the recession that the nation’s economy is now entering. On the monetary policy front, though the central bank has been cutting policy rates and injecting local currency liquidity into the system, this will only help reduce liquidity stress. It will not directly aid ailing households and small businesses suffering from an income shock. Critically, prime lending rates have not dropped despite dramatic cuts in policy rates (Chart II-4). Chart II-5Bank Stocks - Last Shoe To Drop - Are Unraveling Now Bank Stocks - Last Shoe To Drop - Are Unraveling Now Bank Stocks - Last Shoe To Drop - Are Unraveling Now Meanwhile, the government’s decision to grant a debt servicing holiday to borrowers will only help temporarily. These borrowers will still need to repay their debts at some point down the line. Given the magnitude and uncertain duration of their income loss, there is no guarantee they will be in a position to service their debt after the pandemic is over. Eventually, Indonesian commercial banks will experience a large increase in non-performing loans (NPLs). Overall, the plunge in domestic demand combined with the fall in global trade and commodities prices entails that Indonesia is heading into its first recession since 1998. Given Indonesia has for many years been one of the darlings of EM investors, a recession in Indonesia and global flight to safety herald continued liquidation in its financial markets. Both local government bond yields and corporate US dollar bonds yields are breaking out. Rising borrowing costs amidst the recession will escalate the selloff in equities. Remarkably, non-financial stocks and small-caps have already fallen by 40% and 55% in US dollar terms, respectively (Chart II-5, top two panels). It was banks stocks – which comprise 35% of total market cap – that were holding up the overall index (Chart II-5, bottom panel). Given banks will likely experience rising defaults as discussed above, their share prices have more risk to the downside. Bottom Line: Absolute return investors should stay put on Indonesian risk assets for now. We maintain our short position on the rupiah versus the US dollar. EM-dedicated equity investors should keep underweighting Indonesian equities within an EM equity portfolio. Meanwhile, EM-dedicated fixed income investors should continue to underweight Indonesian local currency bonds as well as sovereign and corporate credit. Ayman Kawtharani Editor/Strategist ayman@bcaresearch.com   Footnotes Equities Recommendations Currencies, Credit And Fixed-Income Recommendations

Feature An analysis on Singapore is available below. The plunge in global risk assets is occurring at such a breathtaking pace that any economic analysis is pointless at this time. Economic growth forecasts have been reduced to moving targets. In our latest report published two days ago, we argued that we are witnessing the unravelling of the policy put. For now, monetary stimulus – both rate cuts and QE programs – are unlikely to halt the market riot. Fiscal stimulus is forthcoming but its actual impact on the real economy will not materialize until another several months. The only thing that investors can use to gauge market downside as of now are valuations and market technicals. This report presents the most important technical and valuations indicators that we are currently monitoring. All market prices are updated as of the close of Thursday, March 12, 2020. We are in a liquidation phase where fundamentals do not matter and markets often undershoot. Such indiscriminate liquidation also leads to major buying opportunities. We will book profits on the short EM stocks position when the MSCI EM equity index in USD hits 800. On Thursday March 12, the MSCI EM equity index closed at 880. Possibly, we will recommend accumulating EM stocks and will reverse our bearish bias on EM currencies and fixed-income markets if the EM MSCI Index reaches this level. Remarkably, the top chart on page 2 shows that major EM bear markets – in 1998, 2002, 2008 and 2015-16 – all bottomed when EM share prices hit their 24-year exponential moving average. This technical support for the MSCI EM stock index is currently 780, about 10% below yesterday’s close. Stay tuned. Arthur Budaghyan Chief Emerging Markets Strategist arthurb@bcaresearch.com EM Stocks Are Approaching A Major Defense Line EM Stocks Are Approaching A Major Defense Line EM Stocks Are Approaching A Major Defense Line Global Material Stocks Are At A Long-Term Technical Support Line Global Material Stocks Are At A Long-Term Technical Support Line Global Material Stocks Are At A Long-Term Technical Support Line A Long-Term Perspective On Brazilian Stocks Technical And Valuation Charts That Matter Technical And Valuation Charts That Matter The Brazilian Real Is Not Yet Very Cheap The Brazilian Real Is Not Yet Very Cheap The Brazilian Real Is Not Yet Very Cheap Cyclically-Adjusted P/E Ratio For EM Equities Cyclically-Adjusted P/E Ratio For EM Equities Cyclically-Adjusted P/E Ratio For EM Equities Cyclically-Adjusted P/E (CAPE) Ratio For US Stocks Cyclically-Adjusted P/E Ratio For US Stocks Cyclically-Adjusted P/E Ratio For US Stocks Three Technical Support Levels For S&P 500 Three Technical Support Levels For S&P 500 Three Technical Support Levels For S&P 500 An Equal-Weighted Aggregate Stock Price Of Facebook, Apple, Amazon, Netflix, Google And Microsoft An Equal-Weighted Aggregate Stock Price Of Facebook, Apple, Amazon, Netflix, Google And Microsoft An Equal-Weighted Aggregate Stock Price Of Facebook, Apple, Amazon, Netflix, Google And Microsoft Is FAANGM A Bubble That Has Reached A Top? Is FAANGM A Bubble That Has Reached A Top? Is FAANGM A Bubble That Has Reached A Top? US Market Cap As % Of GDP Was Record High Last Month US Market Cap As % Of GDP Was Record High Last Month US Market Cap As % Of GDP Was Record High Last Month Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies   Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies Global Stock-To-Bond Ratio, Commodities And EM Currencies   Singapore: Zero Interest Rates Ahead   Risk Of Debt Deflation… Singaporean businesses and consumers have been deleveraging in the past six years. That, along with the ongoing export slump1  and collapse in tourism revenues – 50% and 5% of GDP, respectively – have likely pushed real and nominal GDP into contraction in Q1 2020. Negative income growth risks turning this gradual deleveraging into debt deflation. Debt deflation occurs when prices fall and the real value of debt rises. Given the private sector is still heavily leveraged, deflation will trigger defaults. This scenario would be disastrous for Singapore’s credit sensitive property and banking sectors – the two key pillars of this economy. Singapore is not far from this tipping point as core and trimmed-mean consumer prices inflation measures as well as GDP deflator are flirting with deflation (Chart II-1). In order to ensure that this ongoing deleveraging does not enter a debt deflation spiral, both monetary and fiscal authorities need to stimulate more aggressively than they already have. Specifically, they should reduce interest rates to zero and provide substantial fiscal stimulus. … Warrants Zero Interest Rates Even though Singapore households and companies have been deleveraging, they remain highly indebted - total non-financial private sector credit stands at 173% of GDP (Chart II-2, top panel). Chart II-1Singapore: Deflation Is At The Door Singapore: Deflation Is At The Door Singapore: Deflation Is At The Door Chart II-2Singapore: Companies & Households Are Deleveraging Singapore: Companies & Households Are Deleveraging Singapore: Companies & Households Are Deleveraging   The middle and bottom panels on Chart II-2 illustrate company and household leverage, defined as the ratio of Singaporean banks domestic loans to non-financial businesses and households relative to corporate profits and employee compensation, respectively. Corporate profits and employee compensation are better measures because they are incomes available to corporates and households, while nominal GDP is not.  In brief, these measures gauge companies and households liabilities relative to their proper income. Critically, nominal GDP growth has dropped well below prime lending rates which stand at 5.25%. Besides, the prime lending rate in real (in inflation-adjusted) terms has risen as inflation dropped (Chart II-3). This is dangerous and nominal income growth is falling below the nominal interest rate, worsening borrowers’ ability to service their debt. Chart II-4 shows that the private sector’s interest rate payments on debt are elevated relative to GDP. This risks pushing the level of non-performing loans (NPLs) at commercial banks much higher. Chart II-3Singapore: Real Lending Rates Are High Singapore: Interest Payments Are Elevated Singapore: Interest Payments Are Elevated Chart II-4Singapore: Interest Payments Are Elevated Singapore: NPL Provisions And Bank Stocks Singapore: NPL Provisions And Bank Stocks   The non-performing loan (NPL) ratio at Singaporean commercials banks is bound to rise from the low NPL ratio of 2%. Moreover, the ratio of special-mention loans - loans that are stressed but are not yet officially recognized as non-preforming - are also set to climb meaningfully from 2%. Chart II-5Singapore: NPL Provisions And Bank Stocks Singapore: Rates Are Heading To New Lows Singapore: Rates Are Heading To New Lows Furthermore, Singaporean banks have extended a non-negligible amount of loans to Chinese and ASEAN businesses. With the indebted mainland economy struggling following the COVID-19 epidemics and ASEAN companies strained by weakness in their domestic demand, Singaporean banks will have to deal with rising NPLs emanating from China and ASEAN. Singapore’s commercial banks will be forced to raise their provisioning levels significantly, which will hurt their profits. Provisions of the three large MSCI-listed commercial banks  have been already rising. This has been historically negative for bank share prices2 (Chart II-5). As banks boost their provisioning, shareholders will push them to curtail credit origination to control risks. This will dampen economic and income growth. Without bold actions by the authorities, the banking sector and the real economy are facing a dire outlook. Interest Rates Are Heading To Zero Although the monetary and fiscal authorities have provided stimulus, it remains inadequate to fend off rising risks of debt deflation. The MAS (Monetary Authority of Singapore) conducts monetary policy by guiding the trade-weighted exchange rate. The MAS depreciates the trade-weighted SGD when it wants to ease and vice versa. Given the economy has become much more leveraged and, thereby, more sensitive to credit and interest rates, depreciating currency is not always sufficient to create a swift turnaround in domestic demand. This is especially true when global trade is shrinking, as it is today. The Singaporean economy needs much lower lending rates and a significant fiscal boost to avoid entering painful debt deflation. The odds are high that Singaporean bond yields and swap rates are heading to zero. In brief, currency depreciation will only augment the market share of exporters in world trade even though their exports will continue shrinking in absolute terms. Hence, currency depreciation will not promptly boost income and employment in the export industries amid the ongoing global trade contraction. At the current juncture, currency depreciation without a substantial decline in borrowing costs will have little spillover to domestic demand. Chart II-6 illustrates that Singapore’s central bank has already been injecting liquidity in the banking system in order to bring interbank/money market rates lower. However, interest rates remain relatively elevated compared with the US, the euro area and Japan (Chart II-7), as well as relative to what this indebted economy needs. Chart II-6Singapore: Rates Are Heading To New Lows Singapore: Real Lending Rates Are High Singapore: Real Lending Rates Are High Chart II-7Singapore Interest Rates Are Above G3 Singapore Interest Rates Are Above G3 Singapore Interest Rates Are Above G3     On the fiscal side, the government budget will barely turn expansionary this year: expenditures will rise from 3% currently to just 7%, which translates to a 1% rise relative to GDP. This will not do much to boost overall growth. If the pace of domestic loan growth drops from 2.4% to 1.4% (by 100 basis points), that would generate a negative 1.8% credit impulse of GDP, more than offsetting the rise in the fiscal spending impulse. Chart II-8Singapore: Cyclical Sectors Are Contracting Singapore: Cyclical Sectors Are Contracting Singapore: Cyclical Sectors Are Contracting Confirming the lingering growth downtrend, economic conditions were dire even before the COVID-19 outbreak. Manufacturing production volume is shrinking and sea cargo handled has been dropping (Chart II-8). Electronic exports are contracting from a year ago (Chart II-8, bottom panel). Finally, corporate profits are not growing. Consumer spending is extremely weak. Retail volume sales excluding vehicle sales are contracting 2% from last year (Chart II-9). The excess-mired property sector is slowing down anew. Housing loans are contracting which will trigger a material drop in residential property sales (Chart II-10, top panel). As the latter transpires, construction activity will also shrink (Chart II-10, bottom panel). Chart II-9Singapore: Consumer Are Not Spending Singapore: Consumer Are Not Spending Singapore: Consumer Are Not Spending Chart II-10Singapore Property Sector Is Struggling Singapore Property Sector Is Struggling Singapore Property Sector Is Struggling Bottom Line: The Singaporean economy needs much lower lending rates and a significant fiscal boost to avoid entering painful debt deflation. The odds are high that Singaporean bond yields and swap rates are heading to zero. Investment Recommendations The MAS will continue injecting more liquidity into the banking system to bring down interest rates further and devalue the currency. Exactly for these reasons, since June 8, 2018 we have been recommending shorting the SGD versus the JPY. This trade has so far produced a 7.3% gain with very low volatility (Chart II-11). Our target for this SGDJPY position is 70. Today we are booking profits on the short Hong Kong property developers / long Singapore property developers position because the Fed is about to cut rates to zero, which will reduce downside potential in Hong Kong real estate stocks. This recommendation has produced 21.5% profit since March 22, 2017 (Chart II-12). Chart II-11Stay With Short SGD / Long JPY Trade Stay With Short SGD / Long JPY Trade Stay With Short SGD / Long JPY Trade Chart II-12Book Profits On Our Long Singapore / Short Hong Kong Property Stocks Position Book Profits On Our Long Singapore / Short Hong Kong Property Stocks Position Book Profits On Our Long Singapore / Short Hong Kong Property Stocks Position   As to the overall stock market, we continue recommending a neutral allocation to Singapore within an EM dedicated equity portfolio. Ayman Kawtharani Editor/Strategist ayman@bcaresearch.com   Footnotes 1   Domestic exports, excluding re-exports. 2   DBS Bank, Overseas-Chinese Banking, United Overseas Bank.

Highlights Duration: It is too soon to call the bottom in bond yields. To help make that call we will be looking for when: daily new COVID-19 infections reach zero, global growth indicators improve, US economic indicators worsen, technical indicators signal a reversal. Fed: Low inflation expectations mean that the Fed is unconstrained when it comes to easing policy. Rate cuts will continue until either the funds rate reaches zero, or financial markets signal that enough stimulus has been delivered. Spread Product: Investors with 12-month investment horizons should neutralize allocations to spread product versus Treasuries, including high-yield where the recent oil supply shock will weigh heavily on returns. Investors should also downgrade exposure to MBS with the goal of re-deploying into corporate credit once the current risk-off episode runs its course. Feature Risk off sentiment prevailed in financial markets again last week, as COVID-19 continues to spread throughout the world. Most recently, the city of Milan has been placed under quarantine and New York state has declared a state of emergency. It is difficult to have much certainty about the virus’ ultimate economic impact, but the prospect of US recession looms larger and larger. In bond markets, the 10-year Treasury yield has fallen to 0.54% and the yield curve is pricing-in 91 bps of Fed rate cuts over the next 12 months (Chart 1). If those expectations are met, it would bring the funds rate down to 0.18%, only slightly above the zero-lower-bound. Chart 1Market Priced For A Return To The Zero-Lower-Bound Market Priced For A Return To The Zero-Lower-Bound Market Priced For A Return To The Zero-Lower-Bound On the bright side, there is ample evidence that global economic growth was trending up before the virus struck in late January, and we remain confident that a large amount of pent-up demand will be unleashed once its impact fades. However, we have no clarity on how much longer COVID-19 might weigh on growth. For this reason, we recommend a much more defensive US bond portfolio allocation, even for investors with 12-month horizons. Specifically, investors should keep portfolio duration close to benchmark and reduce spread product allocations to neutral. The market is sending the message that more rate cuts are needed. We will be quick to re-initiate a below-benchmark duration recommendation when we think that bond yields are close to bottoming. In the below section titled “How To Call The Bottom In Yields”, we discuss the factors that will help us make that decision. A State Of Monetary Policy Emergency The Fed took quick action last week, delivering an inter-meeting 50 basis point rate cut as the stock market tumbled on Tuesday morning. Alas, the market is sending the message that those 50 bps won’t be enough. Fed funds futures are pricing-in another 82 bps of easing by the end of next week’s FOMC meeting, followed by further cuts in April (Table 1). Table 1Expectations Priced Into The Fed Funds Futures Curve When And Where Will Bond Yields Trough? When And Where Will Bond Yields Trough? Of course, easier monetary policy is not the solution to what ails the global economy. At his press conference last week, Fed Chair Powell justified the emergency cut by saying that it will help “avoid a tightening of financial conditions which can weigh on activity, and it will help boost household and business confidence.” This is a fair assessment of what monetary policy can hope to accomplish in the current environment. At most, monetary policy can limit the damage in financial markets, which is a worthwhile goal given the strong historical correlation between financial conditions and economic growth (Chart 2). Chart 2Fed Must Do Its Best To Support Financial Conditions Fed Must Do Its Best To Support Financial Conditions Fed Must Do Its Best To Support Financial Conditions What’s more, with inflation expectations at very low levels – as we go to press the 10-year TIPS breakeven inflation rate is a mere 1.03% – there is no reason for the Fed to resist easing policy, even if the expected benefits from easing are small. Chart 3Markets Demand More Easing Markets Demand More Easing Markets Demand More Easing From our perch, the only possible reason for the Fed to refrain from cutting rates quickly all the way back to zero would be to preserve some monetary policy ammunition for when it is needed most. The Fed probably doesn’t see things this way. In conventional economic models it is the level of interest rates that influences economic activity. Therefore, the way to get the most bang for your stimulus buck is to cut rates to zero as quickly as possible. However, if monetary policy is primarily influencing the economy via its impact on financial conditions and investor sentiment, as Chair Powell claimed, then it would be advisable to only deliver rate cuts when financial conditions are tightening rapidly. That is, don’t cut rates if the stock market is rebounding, save your ammo for when equities are in free fall and panic is widespread. We can’t know for certain what the Fed will do between now and the next FOMC meeting. But we can say that, with inflation pressures low, there are no constraints against cutting rates back to the zero bound. The safest takeaway for bond investors is to assume that rate cuts will continue until either (i) the fed funds rate hits zero or (ii) we see signs that the markets and economy are no longer calling for further stimulus. Those signs would be (Chart 3): Yield curve steepening, particularly at the short end. Stocks outperforming bonds. A rising gold price. A falling US dollar. Bottom Line: More rate cuts are coming, and they won’t stop until either the fed funds rate hits zero or financial markets signal that sufficient stimulus has been delivered. We can’t be certain whether that will occur with more or less than the 91 bps of rate cuts that are currently priced for the next 12 months. As such, we recommend keeping portfolio duration close to benchmark. How To Call The Bottom In Yields The US economy is on the cusp of entering a downturn of uncertain duration that will likely be followed by a rapid recovery. Given that outlook, the next big call to make is: When will bond yields put in a bottom? We identify four catalysts that we will monitor to make that call. 1. Virus Panic Abates This is the most important catalyst that could lead us to re-initiate a below-benchmark duration recommendation. The pattern of past viral outbreaks is that bond yields tend to fall until the number of daily new cases reaches zero. This is precisely what happened during the 2003 SARS epidemic (Chart 4A). As for COVID-19, the number of daily new cases looked like it was approaching zero a few weeks ago, but then reversed course as the virus moved on from China to the rest of the world (Chart 4B). One ray of hope is that the number of new cases in China is approaching zero. This suggests that it will also be possible for other countries to contain the virus, but right now it is unclear how long that will take. Chart 4AYields Will Bottom When New Cases Reach Zero Yields Will Bottom When New Cases Reach Zero Yields Will Bottom When New Cases Reach Zero Chart 4BNew COVID-19 Cases Still ##br##Rising New COVID-19 Cases Still Rising New COVID-19 Cases Still Rising   In sum, we will keep tracking the global daily number of new cases and will shift to a below-benchmark duration recommendation as it approaches zero. 2. Global Economic Data Improve (Especially China) Chart 5Waiting For A Global Growth Rebound Waiting For A Global Growth Rebound Waiting For A Global Growth Rebound China is where the COVID-19 outbreak started and it is also where we are now seeing the impact in the economic data. The Global Manufacturing PMI dropped from 50.4 to 47.2 in February, due in large part to the plunge in China’s index from 51.1 to 40.3 (Chart 5). In order to call the bottom in US bond yields we will need to see evidence that China can come out the other side of the economic downturn. This means seeing an improvement in the Chinese and Global Manufacturing PMIs. We would also like to see improvement in other global growth indicators such as the CRB Raw Industrials index (Chart 5, panel 2) and the relative performance of cyclical versus defensive equity sectors (Chart 5, bottom panel). Aggressive Chinese stimulus (both monetary and fiscal) might help speed this process along. China’s credit impulse is on the rise (Chart 5, panel 2), and our China Investment Strategy service observed that recently announced policy initiatives related to infrastructure, housing and the automobile sector resemble those that led to a V-shaped Chinese economic recovery in 2016.1  We will be inclined to shift back to below-benchmark portfolio duration when the Global Manufacturing PMI, CRB Raw Industrials index and the relative performance of cyclical versus defensive equities move higher. 3. The US Economic Data Worsen Chart 6Waiting For Weaker US Data Waiting For Weaker US Data Waiting For Weaker US Data While the Global and Chinese economic data are currently in the doldrums, we still haven’t seen COVID’s impact on the US economy. The US ISM Manufacturing PMI is in expansionary territory and the Services PMI is at a healthy 57.3 (Chart 6). Meanwhile, US employment growth has averaged +200k during the past 12 months (Chart 6, panel 2) and the US Economic Surprise Index is above 60 (Chart 6, bottom panel)! Until the US economic data take a hit, another downleg in US bond yields is likely. Looking ahead, if the Global and Chinese economic data are improving as the US data are weakening, financial markets will extrapolate from the Chinese experience and start to price-in an eventual US recovery. Therefore, bond yields will probably start to move higher while the US economic data are still weak. For this reason, one catalyst for us to re-initiate below-benchmark portfolio duration will be when the US economic data weaken. 4. Technical Signals Table 2The 3-Month Golden Rule When And Where Will Bond Yields Trough? When And Where Will Bond Yields Trough? We don’t recommend relying on technical trading rules when forming a 12-month investment view, but technical signals can help add discipline to investment strategies, especially when calling tops and bottoms. One framework with a decent track record is our Golden Rule of Bond Investing applied to a shorter 3-month investment horizon.2 While this 3-month rule doesn’t work as well as when it is applied to a 12-month horizon, we still find that if you correctly predict whether the Fed will deliver a hawkish or dovish surprise relative to market expectations during the next three months, you will make the right duration call 63% of the time (Table 2). The 3-month Golden Rule worked better for dovish surprises than for hawkish surprises in our sample but delivered solid results in both cases. The median 3-month excess Treasury index return versus cash was -1.09% (annualized) when there was a hawkish Fed surprise, compared to +2.56% (annualized) when there was a dovish Fed surprise. For context, the median annualized 3-month excess Treasury index return versus cash during our sample period was +1.79%. Until the US economic data take a hit, another downleg in US bond yields is likely. The overnight index swap curve is currently priced for 94 bps of rate cuts during the next three months, which would essentially take the funds rate back to the zero bound. As of now, we cannot rule out this possibility and are therefore not inclined to look for higher yields during the next 3 months. Momentum, Positioning & Sentiment Other technical signals can also help call tops and bottoms in bond yields. One such signal comes from our Composite Technical Indicator, an indicator that is based on yield changes, investor sentiment surveys and positioning in bond futures markets. Right now, the indicator is sending a strong “overbought” signal with a reading below -1 (Chart 7). Chart 7Technical Treasury Signals Technical Treasury Signals Technical Treasury Signals In isolation, an overbought signal from our Composite Technical Indicator is not a strong reason to call for higher yields. We found that, historically, a reading below -1 from our indicator precedes a 3-month move higher in the 10-year Treasury yield only 53% of the time (Table 3). Table 3Technical Treasury Indicator Performance (1995 – Present) When And Where Will Bond Yields Trough? When And Where Will Bond Yields Trough? One reason for the Composite Technical Indicator’s mediocre performance is that, even at low levels, the market can always become more overbought. But we can partially control for this by combining the overbought signal from our indicator with simple momentum measures that might signal a trend reversal. For example, a reading below -1 from our Composite Technical Indicator combined with a 1-week increase in the 10-year yield precedes a higher 10-year yield during the next three months 58% of the time. If we wait for a 2-week increase in the 10-year yield the rule’s success rate rises to 60%, and it rises to 71% if we wait for the 10-year yield to break above its 4-week moving average. At present, our Composite Technical Indicator shows that Treasuries are extremely overbought, but momentum measures are sending no signals about an imminent trend change (Chart 7, bottom 3 panels). Bottom Line: It is too soon to call the bottom in bond yields. To help make that call we will be looking for when: daily new COVID-19 infections reach zero, global growth indicators improve, US economic indicators worsen, technical indicators signal a reversal. Some Quick Notes On TIPS, MBS And Spread Product Allocations Along with raising recommended portfolio duration to benchmark on a 12-month horizon, we also recommend neutralizing exposure to spread product in US bond portfolios. This includes reducing exposure to high-yield corporate bonds. High-yield remains attractively valued but will continue to sell off as long as risk-off market sentiment prevails. The looming oil price war will also weigh heavily on the sector, which is highly exposed to the US shale energy space. Once again using the SARS epidemic as a comparable, we see that – like Treasury yields – junk excess returns bottomed when the number of daily new cases approached zero (Chart 8). We could still be relatively far from this point, so taking risk off the table makes sense.  New all-time lows in Treasury yields will drag mortgage rates lower and lead to a spike in refinancing activity. We also recommend moving MBS allocations to underweight. New all-time lows in Treasury yields will drag mortgage rates lower and lead to a spike in refinancing activity. This spike is not yet fully reflected in MBS spreads, which remain relatively tight (Chart 9) Chart 8Too Soon To Call For Peak Junk Spreads Too Soon To Call For Peak Junk Spreads Too Soon To Call For Peak Junk Spreads Chart 9Downgrade MBS Downgrade MBS Downgrade MBS . Going forward, even after the economic fallout from COVID-19 has passed and it is time to increase exposure to spread product, we will likely continue to recommend an underweight allocation to MBS because better opportunities will be available in investment grade and high-yield corporate bonds where spreads will be much more attractive. On TIPS, last weekend’s oil supply shock – combined with the demand shock from COVID-19 – will conspire to keep long-maturity TIPS breakeven inflation rates well below their “fundamental fair value” for some time yet. But for investors with longer time horizons we see exceptional value in TIPS relative to nominal Treasuries. Even before yesterday’s big drop in oil, the 10-year TIPS breakeven inflation rate was 52 bps cheap relative to the fair value reading from our Adaptive Expectations Model (Chart 10).3 Chart 10TIPS Offer A Ton Of Long-Run Value TIPS Offer A Ton Of Long-Run Value TIPS Offer A Ton Of Long-Run Value Investors with 12-month investment horizons should continue to favor TIPS over nominal Treasuries, but those with shorter horizons may be advised to stand aside and wait for the daily number of new COVID-19 cases to reach zero before re-initiating the position.   Ryan Swift US Bond Strategist rswift@bcaresearch.com Footnotes 1 Please see China Investment Strategy Weekly Report, “China: Back To Its Old Economic Playbook?”, dated February 26, 2020, available at cis.bcaresearch.com 2  For more details on our Golden Rule of Bond Investing please see US Bond Strategy Special Report, “The Golden Rule of Bond Investing", dated July 24, 2018, available at usbs.bcaresearch.com 3 For more details on our Adaptive Expectations Model please see US Bond Strategy Weekly Report, “How Are Inflation Expectations Adapting?”, dated February 11, 2020, available at usbs.bcaresearch.com Fixed Income Sector Performance Recommended Portfolio Specification

Highlights Building on a previous special report focused on the investable market, in this report we construct and present models designed to predict the odds of Chinese domestic equity sector outperformance. BCA Research's China Investment Strategy service will aim to use our newly developed sector outperformance probability models to better understand the drivers of performance at any given moment, and to make more active equity sector recommendations in the future. Episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) than has been the case for the investable market, suggesting that periods of “abnormal” relative sector performance may occur more frequently than in the investable universe. Among the predictors included in our model, our Li Keqiang leading indicator (based on monetary conditions, money, and credit growth) has been the most important. Our base case view argues in favor of domestic cyclicals over defensives over the coming year, but recent sector performance suggests that domestic consumer discretionary and tech should be favored within a cyclical equity portfolio over energy, materials, and industrials barring a surge in oil prices or a capitulation by Chinese policymakers in favor of “flood irrigation-style” stimulus. Over the long-term, we argue that investors have a good reason to favor domestic defensives over cyclicals until the latter demonstrates meaningfully better earnings performance. Feature We examined China’s investable equity sector performance in detail in our October 30 Special Report,1 with a particular emphasis on understanding the specific macroeconomic or equity market factors that have historically predicted relative sector performance. In today’s report, we extend our approach to China’s A-share market. Our research focused on constructing and presenting models that quantify a checklist-based approach to determining the odds of equity sector performance. The aim is to use these models to better understand the drivers of performance at any given moment, and to make more active equity sector recommendations in the future. These recommendations will not mechanically follow the models; rather, we plan to use them as a stand in for what typically would be expected given the macro and financial market environment, and as a basis to investigate “abnormal” relative performance. We find that episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) that has been the case for the investable market, suggesting that periods of “abnormal” relative sector performance may occur more frequently than in the investable universe. Among the macroeconomic and equity market factors that we found to be important predictors, our Li Keqiang leading indicator was the most significant. This confirms that China’s domestic market is more sensitive to monetary conditions, money, and credit growth than its investable peer. We also note the sharp difference in the relative performance of cyclicals versus defensives in the domestic market compared with the investable market, and what this means for investors over the coming 6-12 months. Finally, we argue that investors should maintain a structural bias towards defensive stocks in the domestic market until cyclicals demonstrate meaningfully better earnings performance, and point to an existing position in our trade book for investors interested in strategically allocating to the A-share market. Detailing Our Approach In our effort to better understand historical periods of domestic sector performance, we have chosen to model the probability of outperformance of each level 1 GICS sector (plus banks) based on a set of macro and equity market variables. Specifically, we use an analytical tool called a logistic regression, which forecasts the probability of a discrete event rather than forecasting the value of a dependent variable. We utilized this approach when building our earnings recession model for China (first presented in our January 16 Special Report).2 The “events” that we modeled are historical periods of individual Chinese investable sector outperformance from 2010 to 2018, relative to the MSCI China index (the “broad market”). We find that episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) than has been the case for the investable market. Chart I-1A and Chart I-1B illustrate these periods with shading in each panel. We then attempt to explain these episodes of outperformance with the following macro predictors: Chart I-1AThis Report Builds Models ##br##Aimed At... Chart 1A This Report Builds Models Aimed At… This Report Builds Models Aimed At… Chart I-1B...Predicting The Shaded Regions Of These Charts Chart IB …Predicting The Shaded Regions Of These Charts …Predicting The Shaded Regions Of These Charts Periods of accelerating economic activity, represented by our BCA's China Activity Index Periods of rising leading indicators of economic activity, represented by our BCA Li Keqiang (LKI) Leading Indicator Episodes of tight monetary policy, defined as periods where China’s 3-month interbank repo rate is rising Periods of accelerating inflation, measured both by headline and core inflation We also include several equity market variables: uptrends in relative sector earnings, periods of rising broad market stock prices, uptrends in broad market earnings, and episodes of extreme technical conditions and relative over/undervaluation for the sector in question. In the case of energy stocks, we also include oil prices as a predictor. Chart I-2A and Chart I-2B illustrate these periods as well as the macro & market variables that we have included as predictors. Chart I-2AWe Use These Macroeconomic And Equity Market Factors... Chart 2A We Use These Macroeconomic And Equity Market Factors… We Use These Macroeconomic And Equity Market Factors… Chart I-2B...To Predict Periods Of Equity Sector Outperformance Chart 2B …To Predict Periods Of Equity Sector Outperformance …To Predict Periods Of Equity Sector Outperformance Our approach also accounts for the existence of any leading or lagging relationships between the macro and market variables we have used as predictors and sector relative performance. In most cases the predictors lead relative sector performance, but in some cases it is the opposite. In the case of the latter, we have limited the lead of any variable in our models to three months in order to reduce the need to forecast. Finally, our approach also limits the extent to which we consider a leading relationship between our predictors and relative sector performance, in order to avoid picking up overlapping economic cycles. This issue, and the evidence supporting the existence of a 3½-year credit cycle in China, is detailed in Box I-1 of our October 30 Special Report (please see footnote 1). Key Drivers Of Sector Performance: Domestic Versus Investable Pages 11-22 present the results of each sector’s outperformance probability model, along with a list of factors that were found to be useful predictors and a summary of the results. The importance of the factors included in the models is shown in each of the tables at the top right of pages 11-22 by a score of 1-3 stars, (loosely representing key levels of statistical significance) as well as each factor’s optimal lead or lag. A minus sign shows that the predictor leads sector relative performance, whereas a plus sign shows that it lags. Following a review of our domestic equity sector outperformance models, differences in the results from those presented in our previous report can be organized into three distinct elements: 1) the breadth of macro & equity market factors in predicting sector performance, 2) the relative importance of our LKI leading indicator, and 3) the difference between domestic/investable cyclical versus defensive performance. The Breath Of Predictive Factors Chart I-3In The Domestic Market, The Breadth Of Predictive Factors Is Narrower Chart 3 In The Domestic Market, The Breadth Of Predictive Factors Is Narrower In The Domestic Market, The Breadth Of Predictive Factors Is Narrower Compared with the models for investible sector performance that we detailed in our previous report, our work modeling domestic equity sector performance highlights that the breadth of predictive factors is narrower, particularly among cyclical sectors (Chart I-3). Our model for domestic materials (shown on page 12) is one exception to this rule, but we found that our models for energy, industrial, and consumer discretionary relative performance were all focused on fewer predictors than is the case for the investable market. In addition, our domestic utilities model has considerably worse predictive power than our model for investable utilities. The case of industrials is particularly notable: our model for investable industrials highlighted the importance of tight monetary policy, rising core inflation, rising broad market stock prices & earnings, and overbought and oversold technical conditions in explaining past periods of industrial sector outperformance. By contrast, our domestic industrials model is quite simple: the sector has been more likely to outperform, with a lag, when our BCA China Activity Index and LKI leading indicator have been rising, and underperform following periods of extreme overvaluation. One of the core conclusions of our previous report was that investors should view the relative performance of investable industrials versus consumer staples as a reflationary barometer, given the strong sensitivity of both sectors to tight monetary policy. We explained this sensitivity by pointing to the substantial difference in corporate health between the two sectors: industrial firms are heavily debt-laden and thus experience deteriorating operating performance and an environment of rising interest rates. In comparison, food and beverage firms appear to have the strongest balance sheets among the sub-sectors that we have examined, suggesting that they would benefit less from easier monetary conditions than firms in other industries. Our leading indicator for Chinese economic activity has been considerably more important in predicting domestic equity sector outperformance than in the investable market. However, these dynamics appear to be completely absent in influencing performance in China’s domestic equity market. Not only has domestic industrial sector relative performance not been negatively linked to periods of tight monetary policy, but our model for consumer staples (shown on page 15) highlights that periods of staples performance have been driven by two simple factors: the relative trend in staples EPS  (positive sign), and the trend in broad market EPS (negative sign). The Relative Importance Of Monetary Conditions, Money, And Credit Growth Chart I-4 summarizes the significance of the factors in predicting sector performance in general, by summing up each predictor’s number of stars across all of the models. The chart shows that our LKI leading indicator is the most important signal of sector performance that emerged from our analysis, followed by rising core inflation, rising broad market stock prices, rising economic activity, and oversold technical conditions. The ranking of results shown in Chart I-4 is fairly similar to those that we listed for the investable market, with two exceptions. First, for the domestic market, periods of tight monetary policy were considerably less important than in the investable market as an important predictor of relative sector performance. Instead, our LKI leading indicator was by far the most important predictor, which underscores a point that we have made in previous reports: domestic stocks appear to be much more sensitive to the trend in monetary conditions, money, and credit growth than for the investable market. This increased sensitivity has helped explain the difference in performance this year between the investable and domestic market, underscoring that the former has more catch-up potential than the latter in a trade truce scenario. Chart I-4Monetary Conditions, Money, & Credit Growth Drive A-Share Performance Chart 4 Monetary Conditions, Money, & Credit Growth Drive A-Share Performance Monetary Conditions, Money, & Credit Growth Drive A-Share Performance Second, in the investable market, episodes of significant overvaluation had essentially no power to predict future episodes of equity market underperformance. But this factor was an important or very important contributor to our domestic industrials, health care, and tech models. This finding is consistent with our May 23 Special Report, which noted that value stocks have outperformed in China’s domestic equity market over the past five years and underperformed in the investable market (Chart I-5). Chart I-5Value Has Been A More Successful ##br##Factor In The Domestic Market Chart 5 Value Has Been A More Successful Factor In The Domestic Market Value Has Been A More Successful Factor In The Domestic Market   Major Differences In The Performance Of Cyclicals Versus Defensives The results of our models for domestic equity sector performance did not change the cyclical & defensive labels that we applied in our previous report. The signs of the predictors shown in the tables on pages 11-22 clearly highlight that the domestic energy, materials, industrials consumer discretionary, and information technology sectors are cyclical sectors, and that consumer staples, health care, financials, telecom services, utilities, and real estate are defensive. What is striking, however, is that there is a major difference in the relative performance of equally-weighted domestic cyclicals versus defensives compared with what has occurred in the investable market over the past decade. Chart I-6A and Chart I-6B illustrate the different relative performance trends, along with their corresponding trends in relative P/E and relative EPS. Whereas the relative performance of investable cyclicals versus defensives has had somewhat of a stable mean over the past decade, domestic cyclicals have badly underperformed since early-2011. The charts also make it clear that this underperformance has been driven by a downtrend in relative EPS, not due to trend differences in relative valuation. Chart I-6ACyclicals/Defensives Somewhat Mean-Reverting In The Investable Market... Chart 6A Cyclicals/Defensives Somewhat Mean-Reverting In The Investable Market… Cyclicals/Defensives Somewhat Mean-Reverting In The Investable Market… Chart I-6B...But Not So In The Domestic##br## Market Chart 6B …But Not So In The Domestic Market …But Not So In The Domestic Market Digging further, it appears that this discrepancy can be largely explained by the significant difference in performance between investable and domestic tech over the past decade (Chart I-7). Whereas the former has outperformed the overall investable index by roughly 4-5 times since 2010, the relative performance of the latter has only very modestly risen. In effect, Charts I-6 and I-7 highlight that Chinese cyclical sectors have been structurally impaired over the past decade and have only been “saved” in the investable market by massive outsized outperformance of the tech sector. The fact that investable tech sector performance itself has been largely driven by 2 extremely successful firms underscores how narrowly based the investible cyclical versus defensives performance trend has been. Chart I-7A Huge Gap In Tech Explains Domestic Cyclical Underperformance Chart 7 A Huge Gap In Tech Explains Domestic Cyclical Underperformance A Huge Gap In Tech Explains Domestic Cyclical Underperformance Investment Conclusions There are three conclusions that investors can draw from our analysis. First, our research shows that episodes of domestic equity sector outperformance over the past decade appear to be more idiosyncratic (or sector specific) that has been the case for the investable market. This does not mean that domestic sector performance is not significantly impacted by macro and top down equity market factors, but it suggests that periods of “abnormal” relative sector performance may occur more frequently than in the investable universe. As such, investors should be prepared to include episode-specific investigation of abnormal performance as a regular part of their domestic equity sector allocation decisions. Investors should favor domestic cyclicals over the coming year, with exposure focused on consumer discretionary and tech. Second, the fact that our LKI leading indicator is in an uptrend suggests that investors should favor domestic cyclicals over defensives over the coming year, with a caveat. We have noted in several previous reports that our indicator is in a shallow uptrend, and the slower pace of money and credit growth than during previous economic upswings suggests that the bar may be higher for some cyclical sectors to outperform. We would advise investors to watch closely over the coming 3-6 months for signs of a technical breakout in all cyclical sectors. But sector performance in Q1 of this year, when the overall A-share market rose sharply versus global stocks, suggests that domestic consumer discretionary and tech should be favored within a cyclical equity portfolio over energy, materials, and industrials barring a surge in oil prices or a capitulation by Chinese policymakers in favor of “flood irrigation-style” stimulus (Chart I-8). Within resources, we prefer the investable energy sector to its domestic peer, due to a sizeable valuation advantage. Chart I-8Favor Select Domestic Cyclical Sectors Over The Coming Year Chart 8 Favor Select Domestic Cyclical Sectors Over The Coming Year Favor Select Domestic Cyclical Sectors Over The Coming Year As a third and final point, abstracting from our bullish outlook for select cyclical sectors over the coming year, Charts 6 and 7 clearly argue for investors to maintain a structural bias towards defensive stocks in the domestic market until cyclicals demonstrate meaningfully better earnings performance. In the May 23 Special Report that we referred to above, we noted that an A-share portfolio formed of industry groups with above-median return on equity and below-median ex-post beta has significantly outperformed over the past decade. Table I-1 presents the current industry group weights of this portfolio, and shows that overweight exposure is concentrated in the health care, consumer staples, and real estate sectors (all of which are defensive), and a heavy underweight towards industrials. Table I-1Current High ROE / Low Beta Factor Industry Group Portfolio Weights* Table 1 Current High ROE / Low Beta Factor Industry Group Portfolio Weights* Current High ROE / Low Beta Factor Industry Group Portfolio Weights* For clients who are interested in strategically allocating to the A-share market, we maintain a long position in this portfolio relative to the MSCI China A Onshore index in our trade book, and plan to continue to update the performance of the trade on a weekly basis. Energy Chart II-1 Chart II-1 Energy Energy Table II-1 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Similar to the investable energy sector, periods of domestic energy sector outperformance are strongly positively related to rising oil prices and rising headline inflation in China. We noted in our previous report that this is a behavioral relationship, rather than a fundamental one. Domestic energy stocks are negatively associated with rising broad market stock prices, unlike their investable peers. This largely reflects the fact that the relative performance of domestic energy stocks has been in a structural downtrend over the past decade. From 2010 to mid-2016, this decline was caused by a persistent underperformance in earnings. Since mid-2016, domestic energy sector EPS have been rising in relative terms, meaning that more recent underperformance has been due to multiple contractions. While not as relatively cheap as their investable peers, domestic energy stocks are heavily discounted versus the broad domestic market based on both the price/earnings ratio and the dividend yield. Consequently, it is possible that domestic energy stocks may at some point begin to outperform in a rising broad equity market environment. For now, our model argues for an underweight stance towards domestic energy due to the lack of a clear uptrend in oil prices. As a pure value play, investable energy stocks maintain a dividend yield of nearly 6.5%, and are thus more attractive than their domestic peers. Materials Chart II-2 Chart II-2 Materials Materials Table II-2 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our model for the domestic materials highlights that the sector’s performance has been related to strengthening economic activity and strongly related to a rising Li Keqiang leading indicator. Among the equity market variables that we tested, materials outperformance has been positively associated with rising relative EPS, rising broad market EPS, and prior oversold technical conditions. Similarly, the investable materials sector, these results show that domestic materials are a strong play on accelerating Chinese economic activity. The factors included in our domestic materials sector model are similar to those included in our investable material, except that relative material earnings have also been a significant predictor of sector relative performance. In addition, the macro & equity market predictors included in our domestic materials model have done a better job of leading material sector performance. The odds of domestic materials outperformance rose twice above the 50% mark this year according to our model, without any corresponding improvement in relative stock prices. The spikes in the model occurred largely because domestic materials became significantly oversold; technical conditions for the sector have only twice been weaker over the past decade. This underscores that investors should be watching domestic materials closely in Q1 of next year for signs of a relative rebound. Industrials Chart II-3 Chart II-3 Industrials Industrials Table II-3 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance The results of our model for domestic industrial sector outperformance are interesting, as they imply that the drivers of performance are different between the domestic and investable markets. In the investable index, we found that industrials were heavily sensitive to monetary policy, rising core inflation, relative sector earnings, and periods of rising broad market stock prices. Our domestic model is considerably simpler: industrials outperform, with a lag, when our activity index and Li Keqiang leading indicator are rising. Periods of strong overvaluation have also been significant in predicting future episodes of domestic industrial sector underperformance. It is not clear to us why the drivers of relative performance for domestic industrials have been different than in the investable equity index, But the good news is that the relative simplicity of the model makes the investment decision making process for domestic industrials considerably easier. Today, domestic industrials are significantly undervalued, and our Li Keqiang leading indicator is in a shallow uptrend. This suggests that domestic industrials are likely to begin outperforming at some point in early-2020 following a bottoming in Chinese economic activity, unless policymakers are quick to tighten once activity begins to improve (which would be contrary to our expectations). Consumer Discretionary Chart II-4 Chart II-4 Consumer Discretionary Consumer Discretionary Table II-4 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our domestic consumer discretionary model highlights that the sector’s relative performance is positively associated with a rising Li Keqiang leading indicator, rising core inflation, and rising broad market stock prices. Similar to its investable peers, domestic consumer discretionary stocks are cyclical, and positive relationship with core inflation may reflect improved pricing power for the sector. Unlike investable consumer discretionary, the domestic consumer discretionary has not been meaningfully impacted by the December 2018 changes to the global industry classification standard. Hence, our model does not exclude the internet & direct marketing retail sector as we did in our previous report on investable sectors. For now, our model suggests that the domestic consumer discretionary sector is likely to continue to underperform, given decelerating core inflation and the lack of a clear uptrend in the broad domestic equity index. However, as a cyclical sector, we will be watching closely for an upside breakout in domestic consumer discretionary performance in the first quarter as a signal to increase exposure to the sector. Consumer Staples Chart II-5 Chart II-5 Consumer Staples Consumer Staples Table II-5 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our domestic consumer staples model is significantly different than that shown in our previous report for investable staples. This reflects sizeable differences in investable/domestic staples relative performance over the past decade, particularly from mid-2015 to late-2017 (where domestic staples outperformed significantly and investable staples languished). Of the two predictors found to be significant in explaining historical periods of domestic staples performance, a negative relationship with the trend in broad market EPS has been the most important. This underscores that staples are defensive sector. The trend in staples relative earnings has closely followed in importance, showing that the tremendous outperformance in domestic consumer staples over the past several years has, at least in part, been driven by fundamentals. Still, domestic consumer staples are currently priced at 34x earnings per share, compared with 15x for the overall domestic market. While our model currently argues for continued staples outperformance, the risk of a valuation mean reversion next year, against the backdrop of an improving economy, is above average. Over the coming 6-12 months, investors should be closely monitoring domestic staples for signs of waning earnings momentum and/or a major technical breakdown as potential signals to reduce domestic staples exposure. Health Care Chart II-6 Chart II-6 Health Care Health Care Table II-6 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Over the past decade, periods of domestic health care outperformance have been negatively associated with rising economic activity, rising core inflation, and rising broad market stock prices. Oversold technical conditions and periods of overvaluation have also helped predict future episodes of health care relative performance. These factors clearly point to the defensive nature of domestic health care, similar to health care stocks in the investable index. However, one clear difference between investable and domestic health care is that the former appears to have leading properties and the latter does not. We noted in our previous report that periods of investable health care underperformance appeared to lead, on average, our BCA Activity Index, periods of rising core inflation, and uptrends in the broad investable index. By contrast, domestic health care lags the Activity Index and core inflation by just over a year, and also lags the trend in broad market EPS. Our model points to further health care outperformance, but we would expect domestic health care stocks to underperform at some point next year following an improvement in economic activity and a resumed uptrend in broad domestic EPS. Financials Chart II-7 Chart II-7 Financials Financials Table II-7 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our outperformance probability model for domestic financials highlights that the sector is countercyclical: periods of outperformance have been negatively related to our LKI leading indicator, rising core inflation, and rising broad market stock prices. Similar to the case of the investable index and unlike the case globally, financials are clearly defensive. Investable financials have exhibited atypical performance this year according to the model presented in our previous report. By contrast, domestic financials have performed in line with what our model has suggested: our LKI leading indicator is in a shallow uptrend, and the relative performance of domestic financials has trended flat-to-down since late-2018. Barring a major shift by the PBoC towards a hawkish stance in the coming year (which we do not expect), our base case view for the Chinese economy implies that domestic financials are likely to continue to underperform. Banks Chart II-8 Chart II-8 Banks Banks Table II-8 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our model for domestic banks is similar to that of financials, with some important differences. In addition to being sensitive to our LKI leading indicator, domestic bank performance is negatively related to our Activity Index. Oversold technical conditions have also been quite important in predicting future episodes of domestic bank outperformance. The model is currently forecasting domestic bank underperformance, although it was late in predicting the selloff in bank stocks that began late last year. Similar to the case for domestic financials, our baseline view for the Chinese economy implies that domestic bank are likely to continue to underperform over the coming year. Information Technology Chart II-9 Information Technology Information Technology Table II-9 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our model for the domestic technology sector is different than that of investable tech, which reflects the vast difference in performance between the two sectors. While the relative performance of domestic tech has trended sideways over the past decade, investable tech stock prices have risen fourfold relative to the broad investable index. This difference is largely accounted for by the absence of the BAT stocks (Baidu, Alibaba, Tencent) from the domestic market. Similar to investable tech, domestic technology stocks are negatively related to tight monetary policy, and positively linked with a pro-cyclical economic variable (a rising LKI leading indicator). However, strangely, domestic tech has been strongly and negatively related to rising headline inflation, a finding with no clear fundamental basis. The model has been less successful in predicting domestic tech performance over the past year than in the past, which appears to be linked to the inclusion of headline inflation in the model. Rising headline inflation has been clearly associated with three major episodes of domestic tech underperformance since 2010, but over the past year domestic tech has outperformed as headline inflation accelerated. For now we would advise investors to focus on the other factors in the model: the lack of overvaluation, and our view that policy will remain easy on a measured basis, supports an overweight stance towards domestic tech over the coming year. Telecom Services Chart II-10 Telecom Services Telecom Services Table II-10 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Our domestic telecom services relative performance model highlights that the sector is defensive like its investable peer, but the factors driving performance are somewhat different. The only similarity between the two models is that periods of outperformance are negatively related to rising broad market stocks prices for both investable and domestic telecom services, with domestic telecom stocks responding with a lag. Among the macro factors included in the model, periods of domestic telecom services outperformance are negatively and coincidently related to our LKI leading indicator, and positively related to tight monetary policy (with a slight lead). Oversold technical conditions have also proven to help predict future episodes of outperformance. The model failed to predict a brief period of outperformance in mid-2018, but has generally accurately predicted underperformance of domestic telecom stocks since early-2017. Barring a collapse in the US/China trade talks or considerably weaker near-term economic conditions than we expect, domestic telecom services will likely continue to underperform until the specter of tighter monetary policy emerges. This is unlikely to occur until the middle of 2020, at the earliest. Utilities Chart II-11 Utilities Utilities Table II-11 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Overall, our domestic utilities model has considerably worse predictive power than our model for investable utilities. The model shows that the performance of domestic utilities is negatively related to rising core inflation (with a lag) and rising broad market EPS, but these relationships are not particularly strong. We noted in our June 19 Special Report that domestic utilities ranked highly on the impact that relative EPS had on predicting relative stock prices , yet relative sector earnings did not register as a significant predictor in our model. This apparent discrepancy is resolved by differences in the time horizon between these two approaches. The analysis that we presented in our June 19 Special Report examined the relationship between earnings and stock prices over the entire sample period (2011-2018), meaning that it examined the predictive power of earnings over the long-term. The models built in this report have focused strongly on explaining periods of outperformance over a 6-12 month time horizon, there have been enough deviations in the trend between the relative performance of utilities and relative utilities earnings that the relationship between the two was not sufficiently strong to show up in the model. In other words, the long-term link between utilities relative earnings and stock prices is strong, but the short-term link is fairly weak. Real Estate Chart II-12 Real Estate Real Estate Table II-12 A Guide To Chinese Domestic Equity Sector Performance A Guide To Chinese Domestic Equity Sector Performance Similar to investable real estate, our model shows that domestic real estate is a counter-cyclical sector in that it is negatively related to periods of rising economic activity, a rising LKI leading indicator, tight monetary policy, and rising core inflation. Overbought technical conditions have also aided in predicting future episodes of domestic real estate underperformance. Our model for domestic real estate stocks has performed quite well on average, but its predictive success since late-2017 has been mixed. This period of atypical underperformance has coincided with a considerably weaker rebound in residential floor space sold than has occurred in previous recoveries in the real estate market. This suggests that domestic real estate stocks are more susceptible to trends in housing sales than their investable peers (which appear to be mostly sensitive to rising house prices). We noted in our November 6 Weekly Report that floor space sold is picking up , but it still remains weak when compared with history. This, in combination with our view that the Chinese economy will improve over the coming year, suggests that investors should avoid domestic real estate exposure relative to the overall domestic equity market. Footnotes 1  Please see China Investment Strategy Special Report "A Guide To Chinese Investable Equity Sector Performance," dated October 30, 2019, available at cis.bcaresearch.com 2  Please see China Investment Strategy "Six Questions About Chinese Stocks," dated January 16, 2019, available at cis.bcaresearch.com 3  Please see China Investment Strategy Special Report "Chinese Equity Sector Earnings: Predictability, Cyclicality, And Relevance," dated June 19, 2019, available at cis.bcaresearch.com 4  Please see China Investment Strategy Weekly Report "China Macro And Market Review," dated November 6, 2019, available at uses.bcaresearch.com Cyclical Investment Stance Equity Sector Recommendations

Please note that analysis on India is published below. Highlights This report reviews several financial market-based indicators and price signals from various corners of global markets that are pertinent to the global business cycle, and hence to EM risk assets. The overwhelming message from these indicators and price actions is that the global industrial cycle remains in the doldrums, and a recovery is not imminent. As such, global cyclical segments, commodities, and EM assets are all at risk of plunging. Beware of reigning complacency in EM sovereign and corporate credit markets. Various indicators point to wider EM credit spreads. Feature EM risk assets appear to be on the brink of a breakdown. This week we review various market-based indicators that are telegraphing a relapse in both EM risk assets and commodities. The relative performance of EM versus global stocks leads turning points in the global manufacturing cycle by about six months. As always, we monitor economic data extremely closely. However, one cannot rely solely on economic data to predict directional changes in financial markets. Turning points of economic indicators and data often lag those of financial markets. In fact, one can make reliable economic forecasts based on the performance of financial markets. For example, the relative performance of EM versus global stocks leads turning points in the global manufacturing cycle by about six months (Chart I-1). Chart I-1EM Stocks Signal No Improvement In Global Industrial Cycle EM Stocks Signal No Improvement In Global Industrial Cycle EM Stocks Signal No Improvement In Global Industrial Cycle Over the years, we have devised and tracked several market-based indicators that have a good track record of identifying trends in EM risk assets. In addition, we constantly monitor price signals from various corners of financial markets that are pertinent to the global business cycle, and hence to EM risk assets. The overwhelming message from these market-based indicators is that the global industrial cycle remains in the doldrums, and a recovery is not imminent. As such, global cyclical segments, commodities and EM are all at risk of plunging. Our Reflation Indicator Our Reflation Indicator is calculated as an equal-weighted average of the London Industrial Metals Price Index (LMEX), platinum prices and U.S. lumber prices. The LMEX index is used as a proxy for Chinese growth, while U.S. lumber prices reflect cyclical growth conditions in the American economy. We use platinum prices as a global reflation proxy; this semi-precious metal is sensitive to the global industrial cycle in addition to benefitting from easy U.S. dollar liquidity. The Reflation Indicator has failed to advance above its long-term moving average and has broken down. Chart I-2Our Reflation Indicator Presages No Reflation Our Reflation Indicator Presages No Reflation Our Reflation Indicator Presages No Reflation Chart I-2 illustrates that the Reflation Indicator has failed to advance above its long-term moving average and has broken down. Typically, such a technical profile is worrisome and is often followed by a significant drop. In addition, the Reflation Indicator rolled over at its previous highs last year, another bearish technical signal. Investors should heed signals from this indicator as it correlates well with EM share prices in U.S. dollar terms as well as EM sovereign and corporate credit spreads (Chart I-3). EM credit spreads are shown inverted in the middle and bottom panels. An examination of the individual components of the Reflation Indicator reveals the following: Industrial metals prices in general and copper prices in particular have formed a classic head-and-shoulders pattern (Chart I-4, top panel). As and when the neckline of this pattern is broken, a major downward gap is likely to ensue. Platinum prices have reverted from their key technical resistance levels (Chart I-4, middle panel). This constitutes a bearish technical configuration, and odds are that platinum prices will be in freefall. Finally, lumber prices have failed to punch above their 200-day moving average and have broken below their 3-year moving average (Chart I-4, bottom panel). Chart I-3Reflation Indicator And EM Reflation Indicator And EM Reflation Indicator And EM Chart I-4Beware Of Breakdowns In Commodities Prices Beware Of Breakdowns In Commodities Prices Beware Of Breakdowns In Commodities Prices These technical signals are in accordance with our qualitative assessment of global growth conditions. The global industrial cycle remains very weak, and a recovery is not yet imminent. Meanwhile, the U.S. is the least exposed to the ongoing global trade recession because manufacturing and exports each represent only about 12% of the U.S. economy. Remarkably, economic weakness in Asian export-dependent economies has so far been driven by retrenching demand in China – not the U.S. As Chart I-5 reveals, aggregate exports to China from Korea, Japan, Taiwan and Singapore were still contracting at a 9% pace in April from a year ago, while their shipments to the U.S. grew at a respectable 7% rate. Chart I-5Asian Exports To China And To U.S Asian Exports To China And To U.S Asian Exports To China And To U.S Chart I-6Global Steel And Energy Stocks Are Breaking Down Global Steel And Energy Stocks Are Breaking Down Global Steel And Energy Stocks Are Breaking Down Commodities: Hanging By A Thread? Some commodity-related markets are also exhibiting configurations that are consistent with a breakdown. Specifically: Global steel stocks as well as oil and gas share prices have formed a head-and-shoulders pattern, and are breaking below their necklines (Chart I-6). Such a technical configuration foreshadows major downside. Shares of Glencore – a major player in the commodities space – have dropped below their three-year moving average which has served as a support a couple of times in recent years (Chart I-7). Crucially, this stock has also exhibited a head-and-shoulders formation, and has nose-dived below its neckline. Kennametal (KMT) – a high-beta U.S. industrial stock – leads U.S. manufacturing cycles, and has formed a similar configuration to Glencore’s (Chart I-8). This raises the odds that the U.S. manufacturing PMI will drop below the 50 line. Chart I-7A Head-And-Shoulders Pattern In Glencore Stock... A Head-And-Shoulders Pattern In Glencore Stock... A Head-And-Shoulders Pattern In Glencore Stock... Chart I-8...And In Kennametal (High-Beta U.S. Industrial Stock) ...And In Kennametal (High-Beta U.S. Industrial Stock) ...And In Kennametal (High-Beta U.S. Industrial Stock) Finally, three-year forward oil prices are breaking below their three-year moving averages (Chart I-9). A drop below this technical support will probably mark a major downleg in crude prices. Bottom Line: Commodities and related equity sectors appear vulnerable to the downside. Meanwhile, the U.S. dollar is exhibiting a bullish technical pattern and will likely grind higher, as we discussed in last week’s report titled, The RMB: Depreciation Time? (Chart I-10). Chart I-9Forward Oil Prices Are Much Weaker Than Spot Forward Oil Prices Are Much Weaker Than Spot Forward Oil Prices Are Much Weaker Than Spot Chart I-10The U.S. Dollar Is Heading Higher The U.S. Dollar Is Heading Higher The U.S. Dollar Is Heading Higher EM Equities: A Make-It-Or-Break-It Moment Chart I-11EM Stock Indexes: Sitting On Edge Of A Cliff EM Stock Indexes: Sitting On Edge Of A Cliff EM Stock Indexes: Sitting On Edge Of A Cliff The MSCI EM Overall Equity Index is at an important technical support level (Chart I-11, top panel). If this support is violated, a major downleg will likely ensue. In addition to the above indicators, the following observations also suggest that this support level will be broken and that a gap-down phase will transpire. Both the EM small-cap and equal-weighted equity indexes have been unable to advance above their respective three-year moving averages and are now breaking down (Chart I-11, middle and bottom panels). This could be a precursor for the overall EM stock index to tumble through defense lines, and drop well below its December lows. Our Risk-On/Safe-Haven Currency ratio also points to lower EM share prices (Chart I-12). This indicator is constructed using relative total returns of commodity related (cyclical) currencies such as the AUD, NZD, CAD, BRL, CLP and ZAR against safe-haven currencies such as the JPY and CHF. Importantly, as with EM stocks, this market-based indicator has failed to break above highs reached over the past 10 years. This is in spite of negative interest rates in both Japan and Switzerland that have eroded the latter’s total returns in local currency terms. This ratio has also formed a head-and-shoulders pattern, and may be on the edge of breaking below its neckline. A move lower will spell trouble for EM financial markets. EM corporate profits are shrinking in U.S. dollar terms, and the pace of contraction will continue to deepen through the end of the year. The U.S.-China confrontation is not the only reason behind the EM selloff. In fact, the EM equity rebound early this year was not supported by improving profits. Not surprisingly, the EM equity rebound has quickly faded as investor sentiment deteriorated in response to rising trade tensions. Global semiconductor share prices have made a double top and are falling sharply. Importantly, prices for semiconductors (DRAM and NAND) have not recovered since early this year. The ongoing downdraft in the global semiconductor industry will continue to weigh on the emerging Asian Equity Index. Finally, the relative performance of emerging Asian equities versus DM ones has retreated from its major resistance level (Chart I-13). Odds are that it will break below its recent lows. Chart I-12Risk-On/Safe-Haven Currency Ratio And EM Equities bca.ems_wr_2019_05_30_s1_c12 bca.ems_wr_2019_05_30_s1_c12 Chart I-13Emerging Asian Stocks Versus Developed Markets Emerging Asian Stocks Versus Developed Markets Emerging Asian Stocks Versus Developed Markets Bottom Line: EM share prices are sitting on the edge of a cliff. Further weakness will likely lead to investor capitulation and a major selloff. EM Credit Markets: Reigning Complacency? One asset class in the EM space that has so far held up relatively well is sovereign and especially corporate credit. EM sovereign bonds’ excess returns correlate with EM currencies and industrial metals prices, as shown in Chart I-14. So far, material EM currency depreciation and a drop in industrial metals prices have generated only a mild selloff in EM sovereign credit. Lower commodities prices, EM currency depreciation and weaker global growth are all negatives for cash flows of both sovereign and corporate issuers. Excess returns on EM corporate bonds track the global business cycle closely (Chart I-15). The current divergence between EM corporates’ excess returns and the global manufacturing PMI is unprecedented. Chart I-14EM Sovereign Credit Market Is Complacent... EM Sovereign Credit Market Is Complacent... EM Sovereign Credit Market Is Complacent... Chart I-15...As Is EM Corporate Credit Market ...As Is EM Corporate Credit Market ...As Is EM Corporate Credit Market Our expectation that EM credit spreads will widen is not contingent on a massive default cycle unravelling across the EM credit space. However, lower commodities prices, EM currency depreciation and weaker global growth are all negatives for cash flows of both sovereign and corporate issuers. Chart I-16 illustrates that swings in cash flow from operations (CFO) among EM ex-financials and technology companies correlate with other global business cycle indicators such as Germany’s IFO manufacturing index. Chart I-16EM Corporate Cash Flow Fluctuates With Global Manufacturing Cycle bca.ems_wr_2019_05_30_s1_c16 bca.ems_wr_2019_05_30_s1_c16 Chart I-17EM Corporate Spreads Are Too Narrow Given Their Financial Health EM Corporate Spreads Are Too Narrow Given Their Financial Health EM Corporate Spreads Are Too Narrow Given Their Financial Health The lingering weakness in the global business cycle will likely lead to shrinking CFOs among EM companies, and hence warrants wider corporate credit spreads. Concerning valuations, EM corporate bonds are not cheap at all when their fundamentals are taken into account. Chart I-17 demonstrates two vital debt-servicing ratios for EM ex-financials and technology companies: interest expense-to-CFO and net debt-to-CFO. Both measures have improved only marginally in recent years, yet corporate spreads are not far from their all-time lows (Chart I-17, bottom panel). We are aware that with DM bond yields at very low levels - and in many cases even negative - the appeal of EM credit markets has risen. We are also cognizant that some investors are expecting to hold these bonds to maturity and earn a reasonable yield. Such a strategy has largely paid off in recent years. Nevertheless, if the selloff in EM financial markets escalates – as we expect – EM credit markets will be hit hard as well. To this end, it makes sense to step aside and wait for a better entry point. For dedicated fixed-income portfolios, we continue to recommend underweighting EM sovereign and corporate credit versus U.S. investment-grade credit. Finally, to identify relative value within EM sovereign credit spreads, we plot, each country’s foreign debt obligations as a share of annual exports on the X axis against sovereign spreads on the Y axis (Chart I-18). Chart I-18 This scatter plot reveals that Russia and Mexico offer the best relative value in the EM sovereign space. As such, we are reiterating our high-conviction overweight position in these sovereign credit markets as well as in Hungary, Poland, Chile and Colombia. South Africa and Brazil appear attractive as well, but we are underweight these two sovereign credits. The basis for our pessimistic outlook is due to the unsustainable public debt dynamics in these two countries, as we discussed in our Special Report from April 23. Other underweights within the EM sovereign credit space include Indonesia, the Philippines, Malaysia, Turkey and Argentina.   Arthur Budaghyan Chief Emerging Markets Strategist arthurb@bcaresearch.com     India: How Sustainable Is A 2.0 Modi Rally? Prime Minister Narendra Modi, and his party – the Bharatiya Janata Party – have won a strong majority in the Indian general election this month. Indian stocks surged in the past month as evidence was emerging that Modi was in the lead. Chart II-1Facing Resistance? Facing Resistance? Facing Resistance? Yet this Modi 2.0 rally is unlikely to last for too long. First, as EM stocks continue selling off, Indian share prices will not defy gravity and will fall in absolute terms. Interestingly, the Indian stock market has hit its previous highs – levels at which it failed to break above in the past 12 years (Chart II-1, top panel). We expect this resistance line to hold this time around too. Likewise, we are still reluctant to upgrade this bourse on a relative basis as it has reached its previous highs. This level will likely prove to be a hindrance, at least for the time being (Chart II-1, bottom panel). The basis for betting against a break out in Indian equity prices in both absolute terms and relative to the EM benchmark over the next couple of months is because of the following: Domestic Growth Weakness: India’s domestic growth has been decelerating sharply. The top two panels of Chart II-2 illustrate that manufacturing and intermediate goods production as well as capital goods production growth are all either contracting or on the verge of shrinking. Similarly, domestic orders-to-inventories ratio for businesses is pointing to a further growth slump according to a survey conducted by Dun & Bradstreet (Chart II-2, bottom panel). Furthermore, sales growth of all types of vehicles are either contracting or have stalled (Chart II-3). Chart II-2Business Cycle Is Weak Business Cycle Is Weak Business Cycle Is Weak Chart II-3Domestic Demand Is Fragile Domestic Demand Is Fragile Domestic Demand Is Fragile Regarding the financial sector, Indian banks – encouraged by a more permissive and forbearing central bank on the recognition of non-performing loans – have recently lowered provisions to boost their earnings (Chart II-4). Share prices should not normally react to such accounting changes. Banks either do carry these NPLs or do not. Therefore, the stock price of a bank should not fluctuate much if a central bank is forcing it to recognize those NPLs or if the latter is relaxing recognition and provisioning standards. Chart II-4Less Provisions = More Paper Profit Less Provisions = More Paper Profit Less Provisions = More Paper Profit Chart II-5Very Weak Equity Breadth Very Weak Equity Breadth Very Weak Equity Breadth In brief, we are skeptical about the sustainability of the current rally in bank share prices based on the relaxation of some accounting rules. Unfavorable Technicals & Valuations: Technicals for India’s stock market are precarious. Participation in this rally has been very slim. Indian small cap stocks have not rallied much, lagging dramatically behind large-cap stocks (Chart II-5, top panel). Our proxy for market breadth – the ratio of equal-weighted stocks to market-cap weighted stocks – has also been deteriorating and is sending a very bearish signal for the overall stock market (Chart II-5, bottom panel). Finally, the Indian stock market is overbought and vulnerable to a general selloff in EM stocks. Namely, foreign investors have rushed into Indian equities as of late. This raises the risk of a pullout as foreign investors become disappointed by India’s dismal corporate earnings and outflows from EM funds leads them to pare their holdings. As for valuations, the Indian stock market is still quite expensive both in absolute and relative terms. Oil Prices: Although oil prices will likely drop,1 Indian stocks could still underperform the EM equity benchmark in the near term. Chart II-6India Versus EM & Oil Prices India Versus EM & Oil Prices India Versus EM & Oil Prices The rationale for this is that Indian equities have brushed off the rise in oil prices since the beginning of the year and outperformed the majority of other EM bourses (Chart II-6). By extension, Indian equities could ignore lower oil prices for a while and underperform the EM benchmark in the near term. Beyond near term underperformance, however, India will likely resume its outperformance. First, sustainably lower oil prices will begin to help the Indian stock market later this year. Second, the growth impact of ongoing fiscal and monetary easing will become visible toward the end of this year. Meanwhile, food prices are starting to pickup and this will support rural income and spending. Finally, the Indian economy is much less vulnerable to a slowdown in global trade because Indian exports make only 13% of the country's GDP. Bottom Line: We are maintaining our underweight stance in Indian equities for tactical considerations, but are putting this bourse on an upgrade watch-list. Ayman Kawtharani, Editor/Strategist ayman@bcaresearch.com     Footnotes   1 The view on commodities of BCA’s Emerging Markets Strategy service is different from BCA’s house view due to the difference on the view on the global business cycle and Chinese demand. Equity Recommendations Fixed-Income, Credit And Currency Recommendations

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 Chart 1 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 Beautiful Simulation, Ugly Reality Beautiful 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 Demystifying Risk Parity Demystifying Risk Parity 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) Demystifying Risk Parity Demystifying Risk Parity 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) Demystifying Risk Parity Demystifying Risk Parity 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 Demystifying Risk Parity Demystifying Risk Parity 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? Does Risk Parity Outperform In The Long Run? Does 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 U.S. Risk Parity* Vs. 60/40 U.S. Risk Parity* Vs. 60/40 Chart 4BU.S. Risk Parity* Vs. Stocks U.S. Risk Parity* Vs. Stocks U.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? Does A Rising Bond Yield Hurt Risk Parity? Does 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? Demystifying Risk Parity Demystifying Risk Parity 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 Commodity Impact On U.S. Risk Parity Commodity Impact On U.S. Risk Parity Chart 6BCommodity Impact On Global Risk Parity Commodity Impact On Global Risk Parity Commodity 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 Risk Contributions Risk 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 True Risk Diversification Works Better True Risk Diversification Works Better Chart 9Why Does True Risk Diversification Work Better? Why Does True Risk Diversification Work Better? Why 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.  

Highlights Portfolio rebalancing is the process of realigning portfolio weights back to their strategic allocations. Frequent rebalancing is essentially a counter-cyclical, or value, strategy. In effect, investors buy low and sell high. Infrequent rebalancing is a momentum-factor investing strategy. Maximizing risk-adjusted return is the reason investors should rebalance, not maximizing return per se. We find that calendar, deviation, or a combination of both methods of rebalancing, can all improve risk-adjusted return compared to a non-rebalanced portfolio. Feature What Do We Mean By Rebalancing? The first step of portfolio construction is strategic asset allocation. Simply put, it is determining a set of asset weights that best suits the investor’s return target, risk appetite, capabilities, and other considerations. Once a portfolio is constructed, divergent returns among asset classes cause the weights of the portfolio to shift. Portfolio rebalancing is therefore, the process of realigning portfolio weights back to their strategic allocations. Chart 1Rebalancing Can Imply Style Rebalancing Can Imply Style Rebalancing Can Imply Style Rebalancing is a means of reducing portfolio risk rather than increasing returns, and is necessary to maintain the desired risk exposure over time. Frequent rebalancing can be viewed as value investing: a style in which investors “buy low and sell high” (Chart 1). Given the mean-reverting nature of asset performance, buying the undervalued asset and selling the overvalued should imply that future returns would be higher than past returns. Through this process, investors are hoping to obtain a “rebalancing premium”. It is crucial to recognize that rebalancing works best at inflection points. Hence, that premium is gained when the rebalancing frequency is similar to the frequency of the mean-reversion feature of assets. Rebalancing also allows a portfolio to be consistent with the investor’s risk appetite in order to avoid a particular asset class dominating. However, this is easier said than done. An investor’s intuition usually acts in the opposite direction, pushing him or her to follow momentum rather than cut back the weight of a “winning” asset. The question that this Special Report aims to answer is not whether investors should rebalance or not, but rather what kind of rebalancing they should do. We discuss three different conventional rebalancing methods that investors can use, illustrating the risk-return characteristics of a simple two-asset-class (60% equity/40% bonds) portfolio since 1973. In doing so, we rebalance the portfolio back to its 60/40 strategic weights. Rebalancing is a means of reducing portfolio risk rather than increasing returns, and is necessary to maintain the desired risk exposure over time. It is important to note that rebalancing is no free lunch. Costs vary depending on the method used. Costs include trading and transaction costs, operational costs (trade lags, labor, and time to monitor the portfolio), and tax costs (capital gains on appreciated assets). In this paper, we do not consider the operational and tax costs (as they differ from investor to investor). Rather, we examine portfolio returns given: (1) zero trading costs, and (2) a variable cost of 10 bps dependent on trade size. Additionally, frequent rebalancing can introduce “negative convexity”, a return profile in which large divergences in asset performance exceed the rebalancing premiums investors obtain.1 Throughout our explanations, we show two tables for each method: Table A illustrates the returns given zero costs, while Table B illustrates the returns given the variable costs. It is key to note however that there is no one-size-fits-all rebalancing method. The important thing to realize is that rebalancing, done correctly, must find an optimal balance between cost minimization and managing portfolio risk. As a benchmark, we examine how an unbalanced portfolio, which we will refer to as a “drift portfolio”, comprised of 60% equities and 40% bonds in 1973, would have evolved over the past 46 years. Given that equities outperform bonds over the long run due to their riskier nature, the drift portfolio ends with an 86% allocation to equities, and a maximum allocation of 87% over the period (Chart 2). Chart 2 Chart 3Broken Equity/Bond Correlation Broken Equity/Bond Correlation Broken Equity/Bond Correlation   Before describing how each methodology performed, we need to highlight a key point in understanding the results that follow: the equity/bond correlation underwent a step-change around 1998. Between 1975 and 1998, the correlation between equities and bonds averaged about 0.4. However, declining inflation expectations led to a reversal of this relationship. Since 1998, the equity/bond correlation averaged -0.3 (Chart 3, top panel). It is key to note however that there is no one-size-fits-all rebalancing method. The important thing to realize is that rebalancing, done correctly, must find an optimal balance between cost minimization and managing portfolio risk. How does this affect the results? A positive correlation between equities and bonds means that asset-class returns moved together, reducing the advantages of rebalancing. Therefore, between the start of our sample period, 1973, and 1998, rebalanced portfolios only slightly outperformed a non-rebalanced portfolio. It is crucial to recognize that rebalancing portfolios should continue to be most advantageous during times when asset returns exhibit negative correlation. Portfolio Rebalancing can take place in different ways2 (Table 1). Table 1Conventional Methods Of Rebalancing Rebalancing: How Often? How Far? Rebalancing: How Often? How Far? Rebalancing Methodologies Time-Only Rebalancing The most common rebalancing methodology used by investors is on a simple calendar basis. A survey conducted by the Financial Planning Association showed that 48%, 36%, and 14% of financial planners rebalance quarterly, annually, and monthly respectively; 1% of respondents said they rebalanced based on a client’s request.3 This form of rebalancing involves bringing the asset-class weights back to the agreed-upon benchmark at the end of a specified period. Periods can range from daily (which is rare) to multiple years. Several academic papers and practitioners call for investors to rebalance at least annually. For the purpose of this report, we look at monthly, quarterly, semi-annual, annual, and bi-annual rebalancing.4 Rebalancing not only increases return at the margin, but also reduces portfolio risk and hence improves risk-adjusted returns. The risk-adjusted return increases as the rebalancing frequency decreases. Bi-annual rebalancing had a risk-adjusted return of 1.016 versus 0.895 for a non-rebalanced portfolio and 0.985 for a monthly-rebalanced portfolio over our entire sample period (Tables 2A and 2B). All calendar-rebalancing dates outperformed a non-rebalanced portfolio on a risk-adjusted basis due to lower volatility. The same results persist even when costs are factored in. Chart Chart Rebalancing too frequently not only increased costs, but also limited upside potential. That is noticeable from the number of rebalancing events for a monthly-rebalanced portfolio versus an annually or a bi-annually rebalanced portfolio. Unsurprisingly, we found that all rebalanced portfolios on average underperformed the drift portfolio during equity bull markets, and outperformed in the period leading up to recessions and equity corrections (Chart 4). Given that stocks peak on average six to 12 months before a recession, the higher weighting in bonds at the start of a correction explains the outperformance of a frequently rebalanced portfolio versus a drift portfolio during recessions and equity market corrections. To put this into context, the drift portfolio’s equity weight at the time of the S&P 500’s peak in the dot-com bubble was 84%, versus an average of 61% across the rebalanced portfolios. Similarly, at the peak before the latest market selloff starting on October 3, 2018, the drift portfolio had an 87% equity allocation versus a 61% average allocation for the frequently rebalanced portfolios. Chart 5 shows that rebalancing reduces downside risk relative to a drift portfolio during downturns and recessions. Chart 4Calendar Rebalancing: Relative Performance Calendar Rebalancing: Relative Performance Calendar Rebalancing: Relative Performance Chart 5Calendar Rebalancing: Lower Drawdown Calendar Rebalancing: Lower Drawdown Calendar Rebalancing: Lower Drawdown Threshold-Only Rebalancing Threshold rebalancing allows asset-class weights to be readjusted back to their target weights once they deviate away by a certain percentage. This can be set in terms of either a percentage-point or a percent deviation. Given that, in this paper, we illustrate our findings using just a two-asset class portfolio with relatively large weights in each asset, percentage-point deviations are more appropriate. However, percent deviations should be used when a certain asset class has only a small weight within a portfolio, for example, a 20% deviation away from the 5% target weight of an asset class. A key benefit of threshold-only rebalancing over calendar rebalancing in a multi-asset portfolio is lower transaction costs. Unlike calendar-only rebalancing where all asset classes are brought back to target weights, only the assets that have moved away from benchmark by the set deviation have to be bought and sold. For example, in a five-asset class portfolio, it could be the case that only the best and worst performers have hit their thresholds and have to be adjusted, whereas the other asset classes do not. Tables 3A and 3B show the risk-return characteristics of rebalanced portfolios based on 1, 5, 10, and 20 percentage-point deviations. Similarly to calendar rebalancing, the wider the threshold, the better the risk-adjusted return. The rebalanced portfolio with a 20-percentage point threshold outperforms all other deviations on both a return and risk-adjusted basis. All rebalanced portfolios led to better risk-adjusted returns than the drift portfolio, even after costs are factored in. Chart Chart Also similar to calendar rebalancing, threshold deviation rebalancing also outperforms during recessions and market corrections (Charts 6 & 7). Chart 6Threshold Rebalancing: Relative Performance Threshold Rebalancing: Relative Performance Threshold Rebalancing: Relative Performance Chart 7Threshold Rebalancing: Lower Drawdown Threshold Rebalancing: Lower Drawdown Threshold Rebalancing: Lower Drawdown The table also illustrates that picking the right threshold is crucial. A threshold set too wide will miss all turning-points and hence turn into a drift portfolio. Whereas, thresholds set too narrow will produce only a small improvement in return at the expense of more rebalancing events, and therefore higher costs. Time-And-Threshold Rebalancing A time-and-threshold rebalancing combines the merits of both strategies. The portfolio is rebalanced only when an asset class has deviated from its target allocation by a set threshold on the date of rebalancing. Assuming, for example, monthly rebalancing with a 10% deviation, a portfolio would be rebalanced on the next monthly date only if it had deviated by more than 10 percentage points. Otherwise, the portfolio would not be rebalanced. This implies that two decisions have to be made: a threshold band and a rebalancing frequency. We present the results of this method in a slightly different way. In this case, we show each metric (annualized return (Tables 4A & 5A), annualized volatility (Tables 4B & 5B) and risk-adjusted return (Tables 4C & 5C)) separately under assumptions of both zero costs and variable costs. Chart Chart Chart Chart Chart Chart   The highest risk-adjusted return of 1.023 was achieved with quarterly rebalancing and a 20 percentage point deviation. This resulted in only three rebalancing events throughout the 46-year period. However, this was not as good as simply relying on a 20 percentage point threshold deviation. Investors wanting to keep a tighter control over their portfolio could use a tighter band with a more frequent rebalancing. As noted earlier, rebalancing is a way to maximize risk-adjusted return rather than maximize return. To simply maximize return, annual rebalancing with a 10-percentage point threshold, which had an annualized return of 9.80%, would be the best combination. However, that came at the expense of high volatility and a higher average equity allocation. Having fewer rebalancing events does not necessarily mean lower costs. In fact, we noted that the fewer the rebalancing events, the higher the annualized cost per trade5 (Tables 6 and 7). Given that our variable cost was dependent on trade size, a rebalancing method that relied on wider bands would incur higher costs per trade relative to narrower bands. Table 6Time-And-Threshold Rebalancing: Rebalancing Events Rebalancing: How Often? How Far? Rebalancing: How Often? How Far? Table 7Time-And-Threshold Rebalancing: Cost Per Trade (Bps) Rebalancing: How Often? How Far? Rebalancing: How Often? How Far? Beyond The Conventional Methods New rebalancing strategies have evolved that rely on different metrics. These include timing rebalancing events using tracking error or risk deviation, absolute momentum, or analyzing the stage of the economic cycle. A recent paper published by Northern Trust discussed the merits of risk-based tracking-error rebalancing as a superior method to traditional strategies. The paper concluded that risk-based tracking had outperformed most other rebalancing strategies while requiring fewer rebalancing events. Within the core strategies mentioned, several adjustments could be made to obtain better results from rebalancing events. Some argue that rebalancing back to a tolerance band, rather than to the precise allocation target, could improve risk-adjusted returns. That band is usually set at half of the deviation threshold band, but can vary at the investor’s discretion. Given costs that vary based on trade size, it might be cheaper for an investor to use tolerance bands. However, relying on such a method can easily rack up costs if the investor is going against momentum prior to its end, since relying on tolerance bands would require more frequent rebalancing. Bottom Line Rebalancing is a means of maximizing risk-adjusted return, rather than increasing absolute return. Rebalancing is no free lunch. Investors must take various associated costs into account before considering how and when to rebalance. The added benefit of rebalancing might seem small in annualized returns. However, on average, rebalancing led to an annualized decrease in volatility in excess of 1% over the 46-year period. It might be best for investors to use a time-and-threshold rebalancing to find a balance between cost minimization and maximizing risk-adjusted returns. Amr Hanafy, Research Associate amrh@bcaresearch.com   1 Nick Granger, Douglas Greenig, Campbell Harvey, Sandy Rattray, David Zou, "The Unexpected Costs of Rebalancing And How To Address Them," AHL Partners LLP, July 2014. 2 Colleen Janconetti, Francis Kinniry Jr., Yan Zilbering, "Best Practices For Portfolio Rebalancing," Vanguard, July 2010. 3 Financial Planning Association, Longboard, and Journal Of Financial Planning, “2017 Trends In Investing,” www.onefpa.org. 4 We assumed that monthly rebalancing occurs on the first trading day of every month, quarterly rebalancing occurs on the first trading day of January, April, July, afn_4nd October, semiannual rebalancing on the first trading day of January and July, and annual rebalancing on the first trading day of the year. 5 Calculated as the difference in annualized return between 10 bps cost assumptions and 0 cost assumption multiplied by the number of years within the sample period divided by the number of trades.  

Highlights Investors are currently too pessimistic on Europe’s growth prospects. In fact, European growth will soon bottom. European growth and inflation are also set to improve relative to the U.S. This should give investors an opportunity to reassess the long-term outlook for European Central Bank policy relative to the Fed. Global growth dynamics are also moving in an increasingly dollar-bearish direction, which should create a tailwind for the euro. Based on the pricing of European assets relative to the U.S., there is scope to see more capital flows into the euro area, implying that more euro buying is forthcoming. The entire European currency complex is a buy relative to the dollar; while the NOK, the SEK, and even the GBP could outperform the euro, the CHF will underperform. EUR/JPY also has upside. Feature The case to sell the euro is easy to make. European growth has been very poor: PMIs, industrial production and even German exports are all pointing to a contraction in output; and economic surprises are testing levels recorded during the euro area crisis. Most importantly, this economic retrenchment is particularly sharp when compared to the U.S., which suggests that real interest rate differentials should continue to hurt EUR/USD (Chart 1). Chart 1Selling The Euro Seems So Easy... Selling The Euro Seems So Easy... Selling The Euro Seems So Easy... The problem with this narrative is that investors are already well aware of Europe’s woes. Could Europe instead recover and the euro rebound against the dollar? After all, in the past, when investor pessimism towards Europe experienced as pronounced a dip as the one just witnessed, EUR/USD invariably rebounded soon after (Chart 2). Chart 2...But Maybe We Should Look The Other Way ...But Maybe We Should Look The Other Way ...But Maybe We Should Look The Other Way In this piece, we explore what could go right for the euro, and argue that the euro is indeed attractive at current levels. European Growth Has Hit A Nadir It is safe to say that the euro area is in a funk today: European real GDP growth dipped to a 1.1% annual rate in the fourth quarter of 2018, while industrial production has plunged by 3.9% on a year-on-year basis. But the markets warned us this would happen: The euro has fallen 9% from its February 2018 top, German bund yields are again flirting with the 0.1% level and European banks plunged by more than 40% between January and December last year. Going forward, for European yields to remain as depressed as they are, for the euro to fall again by a similar margin, or for domestic plays to suffer large declines, European growth will have to slow even further. We are not expecting such a scenario. Instead, we expect European growth to recover significantly this year. First, when it comes to Germany, the locomotive of Europe, the shock from the implementation of the new WLTP auto emission standards is passing: Automobile production is stabilizing, capex is accelerating and inventories have been pared down. Moreover, the slowdown in foreign demand has already percolated through the domestic economy, as domestic manufacturing orders are already experiencing one of their sharpest declines since the Great Financial Crisis (Chart 3, top panel). Chart 3European Growth Is Set To Rebound European Growth Is Set To Rebound European Growth Is Set To Rebound Another source of optimism comes from the credit market. As the middle panel of Chart 3 illustrates, the European 12-month credit impulse has begun to bottom. This points to stronger euro area-wide domestic demand. Moreover, the Chinese credit and fiscal impulse is also bottoming, suggesting the drag from foreign demand could be dissipating (Chart 3, bottom panel). When looking at other specific trouble spots, Italy first springs to mind. In our view, the most recent deceleration in Italy was mainly a consequence of the tightening in financial conditions that resulted from the surge in Italian yields following the budget standoff between Rome and Brussels. However, the Lega Nord / Five Star Movement coalition has folded and is more or less acquiescing to the EU’s demands. Moreover, the rising probability that the European Central Bank will continue to provide long-term liquidity to the eurozone banking system via some form of new LTRO should diminish the funding risk to the Italian banking system, and thus, the risks to Rome’s fiscal sustainability. This implies that the decline in Italian borrowing costs could deepen (Chart 4), further easing Italian financial conditions and improving the growth outlook in the euro area’s third-largest economy. Chart 4Easing Financial Conditions In Italy Easing Financial Conditions In Italy Easing Financial Conditions In Italy France, too, has had its fair share of problems, though it is interesting that its industrial sector is not suffering as much as Germany’s, as highlighted by a French manufacturing PMI above the 50 boom/bust line. Instead, the French service sector is the one contracting (Chart 5). This bifurcation is likely to be a byproduct of the gilets jaunes protests that have lasted since November 2018 and affected retail trade. However, the intensity of the protests is declining and the French population is getting used to this. As a result, we are seeing a rebound in French household confidence, which implies that consumption, the main engine of French growth, is likely to perk up. Chart 5Fade The Gilets Jaunes, Paris In Spring Is Beautiful Fade The Gilets Jaunes, Paris In Spring Is Beautiful Fade The Gilets Jaunes, Paris In Spring Is Beautiful Finally, euro area fiscal policy is set to be loosened this year, with the fiscal thrust moving from 0.05% of GDP to 0.4% of GDP (Chart 6). The response of French President Emmanuel Macron to the gilets jaunes protests could even make the fiscal policy support slightly bigger this year. Chart 6Positive Fiscal Thrust In 2019 Positive Fiscal Thrust In 2019 Positive Fiscal Thrust In 2019 Ultimately, this combination of factors suggests that the large dip in European industrial production is likely to prove transitory, and that European activity will revert back toward the levels implied by the Belgian Business Confidence Index, which has historically been a good leading indicator of European growth (Chart 7). Chart 7European IP To Follow Brussels' Mood European IP To Follow Brussels' Mood European IP To Follow Brussels' Mood Bottom Line: The deterioration in European growth has captured the imagination of investors. However, the performance of European assets last year forewarned that growth would decelerate meaningfully. What matters now is how growth will evolve. Developments from Germany, France, Italy, the credit channel and the fiscal front all suggest that European activity will perk up soon. It’s All Relative While getting a sense of European growth is important when making a call on EUR/USD, economic trends must also be considered relative to the U.S. Surprisingly, despite notorious European growth underperformance, rays of hope are emerging. A major structural negative for EUR/USD has abated: The European debt crisis is behind us, and the aggregate European banking sector has been getting healthier, albeit slowly. This means that the euro area credit growth is not declining anymore against that of the U.S. This is a very long-term force that dictates multi-year cycles in the EUR/USD. As Chart 8 shows, it will be difficult for EUR/USD to move below 1.10 so long as the broad trend in the relative credit growth does not weaken anew. Chart 8Credit Dynamics Suggest That The Worst Is Over For EUR/USD Credit Dynamics Suggest That The Worst Is Over For EUR/USD Credit Dynamics Suggest That The Worst Is Over For EUR/USD More immediately, the euro area leading economic indicator relative to the U.S. is forming a bottom (Chart 9). Since the U.S. is not benefiting from as large a fiscal boost as in 2018, and financial as well as monetary conditions have tightened there relative to Europe, this suggests the improvement in the euro area relative LEI could continue this year. Chart 9Bottoming European LEI Versus U.S. Bottoming European LEI Versus U.S. Bottoming European LEI Versus U.S. Relative labor market slack is also evolving in a euro-friendly fashion. From 2013 to 2018, the euro area suffered from greater labor market slack than the U.S., courtesy of a double-dip recession and generally more-moribund growth. However, thanks to a 4.2-percentage-point fall in the European unemployment rate since 2013 to 7.9%, the euro area unemployment gap has not only closed, it is also below that of the U.S. Historically, when the U.S. unemployment gap leapfrogs that of Europe, EUR/USD tends to appreciate (Chart 10). Chart 10Less Slack Leads To A Stronger EUR/USD Less Slack Leads To A Stronger EUR/USD Less Slack Leads To A Stronger EUR/USD Relative slack does not only have value in itself, it also matters for relative inflation trends, which have been a crucial determinant of EUR/USD. As Chart 11 illustrates, EUR/USD tends to follow how euro area core CPI evolves relative to the U.S. After sharply falling last year, European relative core inflation is trying to rebound, which at a minimum suggests that EUR/USD has limited downside. Moreover, EUR/USD has correlated positively with German market-based inflation expectations (Chart 11, bottom panel). This suggests that actual relative inflation as well as euro area inflation expectations play a key role in determining perceptions among investors of how ECB policy will evolve relative to the Federal Reserve. Chart 11EUR/USD Trades Off Of Inflation Dynamics EUR/USD Trades Off Of Inflation Dynamics EUR/USD Trades Off Of Inflation Dynamics The recent euro decline has matched the decline in inflation expectations. However, inflation expectations have been much weaker than implied by the level of wage growth in Europe (Chart 12). This suggests that European inflation breakevens have scope to improve, a positive for the euro. Moreover, European wage growth is not only picking up steam in isolation, it is also rising relative to the U.S., which highlights that European inflation should not just stabilize vis-à-vis the U.S., but also accelerate. Chart 12European Wages Point To Rising Inflation Expectations European Wages Point To Rising Inflation Expectations European Wages Point To Rising Inflation Expectations This case is made even more saliently by looking at relative financial conditions. Due to the tightening in U.S. financial conditions compared to the euro area, European headline and core inflation is set to accelerate relative to the U.S. (Chart 13). Again, this reinforces the case that maybe the euro has upside this year. Chart 13Relative Euro Area Inflation Will Rise Thanks To Easier FCI Relative Euro Area Inflation Will Rise Thanks To Easier FCI Relative Euro Area Inflation Will Rise Thanks To Easier FCI Ultimately, for the euro to rise, investors will have to begin pricing in some switch in policy spreads between the ECB and the Fed. In the past, we showed that short-term policy expectations are important, but long-term ones can be even more relevant, especially when a central bank is well along the path of lifting rates, as the Fed is, while the other remains at maximum accommodation, like the ECB is today.1  Currently, investors expect euro area short rates to be only 0.5% 5-years from now (Chart 14, top panel). The spread between the eurozone and U.S. 5-year forward 1-month OIS rates remains near all-time lows, which explains the weakness in the euro. Now that European policy is much more accommodative than the U.S.’s, there’s scope for investors to upgrade the path of long-term euro area rates relative to the U.S. This would be bullish for the euro (Chart 14, bottom panel). Recovering relative credit flows and improving relative slack and inflation dynamics could catalyze this change. Chart 14The ECB Is Never Raising Rates The ECB Is Never Raising Rates The ECB Is Never Raising Rates Bottom Line: To make the euro an attractive buy, European growth and inflation conditions cannot just increase, they need to improve relative to the U.S. Since long-term interest rate expectations are very depressed in Europe relative to the U.S., a small improvement in the relative growth profile could be enough to catalyze a repricing of the ECB vis-à-vis the Fed, creating a powerful tailwind behind the euro. Nothing Happens In A Vacuum Ultimately, exchange rates, like other prices in the economy, do not only respond to domestic determinants but are also influenced by much larger, global forces. This is because those global trends percolate through domestic economies, resulting in changing relative expected returns that drive money across borders, leading to currency movements. In the case of the euro, global growth matters a lot, because European growth is much more sensitive to global economic fluctuations than U.S. growth is. This is particularly true if shocks emanate from emerging markets (Chart 15). Today, global cyclical variables are increasingly pointing toward an end to the global growth slowdown. A stabilization and reacceleration in global activity would support the euro. Chart 15 First, Chinese monetary conditions have begun to ease, which historically tends to be linked with improvements in European growth relative to the U.S. (Chart 16). Questions remain surrounding this point: How durable will the rebound in Chinese credit be? By how much will Chinese policymakers nurture this bounce? And will this jump be large enough to lift economic activity in the Middle Kingdom? Nonetheless, a reflationary wind from China has begun to blow, and since investors have already discounted much bad news out of Europe, only small improvements could turn the euro around.   Chart 16If China Is Really Stimulating, Europe Will Rip A Greater Dividend If China Is Really Stimulating, Europe Will Rip A Greater Dividend If China Is Really Stimulating, Europe Will Rip A Greater Dividend Second, as Chart 17 shows, our Nowcast for global industrial activity has decisively stepped down. Yet, the countercyclical dollar has been flat since October 2018. Historically, the performance of EM carry trades funded in yen tends to lead global growth. Currently the performance of these strategies is stabilizing. If EM carry trades funded in yen can rally further, this will spell trouble for the greenback, helping the euro – the anti-dollar – in the process. Chart 17An Early Positive For Global Growth An Early Positive For Global Growth An Early Positive For Global Growth Third, EUR/USD tends to correlate with the relative performance of global cyclical equities (Chart 18). The stabilization in these sectors since 2015 suggests it will be difficult for the euro to fall further from current levels. In fact, if EM carry trades can rebound more, cyclicals have additional scope to outperform, and the euro could rally. Chart 18Cyclical Stocks Pointing To No Real Downside In EUR/USD Cyclical Stocks Pointing To No Real Downside In EUR/USD Cyclical Stocks Pointing To No Real Downside In EUR/USD Fourth, the prospects for the semiconductor sector are improving. Demand for semis is highly pro-cyclical, and the U.S. Chip Stock Timing Model developed by our U.S. Equity Strategy service colleagues is currently sending a bullish signal.2 Since such developments link to improving global growth prospects, they are also associated with a stronger EUR/USD (Chart 19). This is also consistent with a generally weaker dollar and stronger Asian currencies. Chart 19The Outlook For Semiconductors Point Toward A Stronger Euro And A Weaker Dollar The Outlook For Semiconductors Point Toward A Stronger Euro And A Weaker Dollar The Outlook For Semiconductors Point Toward A Stronger Euro And A Weaker Dollar Finally, the breakout in copper prices, the stabilization in the CRB Raw Industrials Index and the rally in gold prices all support an improving global growth outlook that could lift EUR/USD. Bottom Line: Various indicators, such as Chinese monetary conditions, EM carry trades, semiconductor demand determinants and commodity prices are suggesting that global growth may soon bottom. Such a development should hurt the countercyclical dollar, amounting to a macro tailwind for EUR/USD. The Bad News Is Priced In Ultimately, the capacity of EUR/USD to rally rests on how much investors upgrade their outlook for Europe. It is therefore crucial to get a sense of exactly how uninspiring Europe currently is to global market participants. There is no better gauge of relative economic pessimism than the price of euro area financial assets relative to U.S. ones. Essentially, money talks. On this front, markets already seem to have internalized the known bad news from Europe, and there is scope for a contrarian rally in the euro, especially if, as we expect, European economic activity improves. First, on a 12-month forward P/E ratio basis, euro area equities are trading at the kind of deep discount to U.S. stocks normally symptomatic of a trough in relative sentiment toward Europe. Such a discount is often followed by a rally in EUR/USD (Chart 20). Chart 20Stock Valuations: Investors Do Not Like Europe Stock Valuations: Investors Do Not Like Europe Stock Valuations: Investors Do Not Like Europe Second, retailers’ equities can often give a more focused assessment of how investors perceive the comparative outlook for domestic demand between two nations. Currently, euro area retailers trade at a 16-year low versus their U.S. counterparts (Chart 21). Investors are therefore much more ebullient about the prospects for U.S. domestic demand than in Europe. Interestingly, the euro’s gyrations since 2016 have tracked the direction of the relative performance of retailers but have diverged in terms of levels. This suggests some underlying support for the currency. Chart 21Can European Domestic Demand Really Validate Such Pessimistic Expectations? Can European Domestic Demand Really Validate Such Pessimistic Expectations? Can European Domestic Demand Really Validate Such Pessimistic Expectations? Third, the relative stock-to-bond ratio also often provides a good read on investors’ comparative economic euphoria/pessimism towards two nations. In 2018, the annual performance of the euro area stock-to-bond ratio relative to the U.S. collapsed to levels not recorded since the euro area crisis was at its apex (Chart 22). This further confirms that investors were massively depressed on European growth prospects relative to the U.S. While this indicator is rebounding, it is still in negative territory, implying that market participants still have room to upgrade their assessment of the euro area relative to the U.S. Historically, this kind of setup has been associated with a rebound in the EUR/USD. Chart 22The Stock-To-Bond Ratio Points To Some Upside Potential The Stock-To-Bond Ratio Points To Some Upside Potential The Stock-To-Bond Ratio Points To Some Upside Potential Fourth, European net earnings revisions relative to the U.S. have also hit bombed-out levels and are in the process of improving. Since earnings are tightly linked to global growth and reflect the same information that informs capital flows into a country (Chart 23), sell-side analysts becoming more positive on Europe at the margin could indicate that investors are in the process of re-assessing whether to buy European assets. A decision to do so would support EUR/USD. Chart 23When The Sell-Side Move From Deeply To Mildly Bearish, EUR/USD Rallies When The Sell-Side Move From Deeply To Mildly Bearish, EUR/USD Rallies When The Sell-Side Move From Deeply To Mildly Bearish, EUR/USD Rallies Bottom Line: Financial market pricing suggests that investors are displaying deep pessimism toward the euro area’s relative growth prospects. The euro could be a contrarian buy. Most importantly, there are early signs that this growth pricing is starting to move in favor of Europe. If our economic view on Europe and global growth is correct, this trend has further to go, implying that more capital could move into Europe, creating a potent tailwind for EUR/USD. What Else? Three additional factors need to be considered: Currency valuations, balance-of-payment dynamics, and technicals. First, while it is not as cheap as it once was, the real trade-weighted euro is still trading below its historical average (Chart 24). Purchasing-power considerations can rarely be used as a timing tool, but our confidence in the euro’s upside would be greatly dented if the euro were a very expensive currency. It is not even mildly pricey. Chart 24Euro Valuations: No Headwinds There Euro Valuations: No Headwinds There Euro Valuations: No Headwinds There Second, balance-of-payment considerations have become increasingly euro-positive. The euro area runs a current account surplus of 3.3% of GDP, and despite large FDI outflows – a natural consequence of being a savings-rich economy – the basic balance of payments remains in surplus. Moreover, as fixed-income outflows have been dissipating, the aggregate portfolio flows into Europe have also been improving (Chart 25). The end of the ECB’s Asset Purchase Program should solidify this trend. Chart 25The Euro Area Balance Of Payments Is Increasingly Favorable The Euro Area Balance Of Payments Is Increasingly Favorable The Euro Area Balance Of Payments Is Increasingly Favorable Finally, technical oscillators are behaving increasingly well. As Chart 26 shows, not only does our Intermediate-Term Indicator remains oversold, but also, it is has begun to form a positive divergence with the price of EUR/USD. If the economic outlook is becoming more bullish, such a technical setup can often be translated into significant gains. Chart 26EUR/USD: Oversold And A Positive Divergence Is Forming EUR/USD: Oversold And A Positive Divergence Is Forming EUR/USD: Oversold And A Positive Divergence Is Forming Bottom Line: The euro’s valuation is not as attractive as it once was, but it remains cheap. Moreover, the euro area’s balance-of-payment dynamics and the EUR/USD’s technical setup both suggest the timing is increasingly ripe to buy the euro against the dollar. Investment Conclusions A trough in European growth, improving growth and inflation prospects relative to the U.S., green shoots for global growth and deep pessimism toward Europe relative to the U.S. all argue that the timing is right to bet on a euro rebound. At this point, the durability of the euro rebound remains unclear. Investors are under-appreciating the ability of the Fed to raise rates this year, which could help the dollar. On the other hand, they seem even more sanguine toward the ECB ever lifting rates. Ultimately, the capacity of the euro to rebound on a long-term basis against the dollar will be constrained by global growth. This means that China will continue to play a center-stage role for this crucial FX pair. At this point, it is unclear how determined Chinese policymakers are to reflate their economy. Thus, we recommend investors monitor Chinese policy to gauge how long to stay in the euro. For the time being, enough pieces are falling into place to warrant buying EUR/USD for three to six months. However, if the Chinese credit impulse can continue on its recent rebound, the durability of a euro rally could be extended, implying that the euro may be in the process of forming a long-term bottom against the dollar. A strengthening euro should support the entire European currency complex against the dollar. In fact, the NOK, the SEK and the GBP may even outperform the EUR. The NOK is being boosted by rising oil prices, a more hawkish central bank, better valuations and an even healthier balance of payments. The SEK is also supported by a Riksbank that is slightly more hawkish than the ECB, and better valuations; it also benefits from a Swedish economy that is even more pro-cyclical than the euro area’s. The GBP also benefits from a greater valuation discount than the euro, and political developments in the U.K. are beginning to move toward a more clear-cut positive outcome on the Brexit front.3 The countercyclical and expensive CHF will prove the European laggard. Finally, EUR/JPY is also set to continue its rebound that began on January 4th. In fact, it may be one of the best vehicles to express a euro-bullish view because it is less sensitive to what the Fed does than EUR/USD is. Rising bond yields are an unmitigated positive for EUR/JPY, and BCA firmly believes that U.S. Treasury yields have upside, whether or not the Fed goes back to lifting rates. The Fed will mostly impact whether it is the real or inflation component that lifts Treasury yields. Bottom Line: The entire European currency complex is set to rise along with the euro against the greenback. In fact, the NOK, the SEK and the GBP are likely to outperform the euro, while the CHF should underperform. EUR/JPY may in fact offer the best risk-adjusted returns to play a euro rebound. While it is clear that at this moment that buying the euro makes sense, the principal risk lies around how long this rally will last. We are increasingly convinced that the euro has made a low for the cycle and that its long-term outlook is looking increasingly bright.  Mathieu Savary, Vice President Foreign Exchange Strategy mathieu@bcaresearch.com Footnotes 1 Please see the EUR/USD: Focus On The Western Shores Of The Atlantic section of the Foreign Exchange Strategy Weekly Report, titled “Canaries In The Coal Mine Alert: EM/JPY Carry Trades”, dated December 1, 2017, available at fes.bcaresearch.com 2 Please see U.S. Equity Strategy Weekly Report, titled “Reflationary Or Recessionary”, dated February 25, 2019, available at uses.bcaresearch.com 3 Please see European Investment Strategy Weekly Report, titled “Why A Catastrophic No-Deal Might Be Good… For The EU”, dated February 28, 2019, available at eis.bcaresearch.com Trades & Forecasts Forecast Summary Core Portfolio Tactical Trades Closed Trades