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Please note that yesterday we published Special Report on Egypt recommending buying domestic bonds while hedging currency risk. Today we are enclosing analysis on Hungary, Poland and Colombia. I will present our latest thoughts on the global macro outlook and implications for EM during today’s webcast at 10 am EST. You can access the webcast by clicking here. Yours sincerely, Arthur Budaghyan Hungary Versus Poland: Mind The Reversal Conditions are set for the Hungarian forint to outperform the Polish zloty over the coming months. We recommend going long the HUF against the PLN. Hungarian opposition parties criticized the government about the considerable depreciation in the forint. As a result, we suspect that political pressure from Prime Minister Viktor Orban led monetary authorities to alter their stance since April. Critically, the main architect of super-dovish monetary policy Marton Nagy resigned from the board of the central bank on May 28. In line with tighter liquidity, interbank rates have risen above the policy rate. This is marginally positive for the forint. The Hungarian central bank (NBH) tweaked its monetary policy in April after the currency had plunged to new lows against the euro, underperforming its Central European counterparts. The NBH widened its policy rate corridor by hiking the upper interest band to 1.85% and keeping the policy rate at 0.90%. The wider interest rate corridor makes it more costly for commercial banks to borrow reserves from the central bank. Hence, such liquidity tightening is positive for the forint. For years, Hungary was pursuing a super-easy monetary policy and consumer price inflation rose to 4% (Chart I-1). With the NBH keeping interest rates close to zero, real rates have plunged well into negative territory (Chart I-2, top panel). Chart I-1Hungary: Inflation Could Pause For Now Chart I-2Hungary Vs. Poland: Real Rates Reversal Is Coming     In brief, the central bank has been behind the inflation curve. As a result, the forint has been depreciating against both the euro and its central European peers. In such a situation, the key to reversal in the exchange rate trend would be the monetary authority’s readiness to raise real interest rates. The NBH has made a small step in this direction. Going forward, the central bank will be restrained in its quantitative easing (QE) program and will not augment it any further. So far, QE uptake has been slow: around half out of the available HUF 1,500 billion has been tapped by commercial banks and corporates. Importantly, the NBH announced its intention to sterilize its government and corporate bond purchases. Already, the commercial banks excess reserves at the central bank have fallen to zero, which suggests that liquidity is no longer abundant in the banking system (Chart I-3). In line with tighter liquidity, interbank rates have risen above the policy rate. This is marginally positive for the forint. Hungarian authorities have become more cognizant of the economic and financial risks associated with their ultra-accommodative policies. For instance, they initiated a clampdown on real estate speculation, which is leading to dwindling real estate prices. This will lead to a decline in overall inflation expectations and, thereby, lift expected real interest rates. The open nature of Hungary’s economy – whereby exports of goods and services constitute 85% of GDP - makes it much more sensitive to pan-European tourism and manufacturing cycles. With the collapse in its manufacturing and tourism revenues, wage growth in Hungary is bound to decelerate rapidly (Chart I-4). Chart I-3Hungary: Central Bank Has Drained Liquidity Chart I-4Economic Growth: Hungary Is More Vulnerable Than Poland   Rapidly deteriorating wage and employment dynamics reduces the odds of an inflation breakout anytime soon. This will cool down inflation and, thereby, increase real rates on the margin. The central bank in Poland will stay super accommodative while the National Bank of Hungary will be a bit less aggressive. Bottom Line: Although this monetary policy adjustment does not entail the end of easy policy in Hungary, generally, it does signal restraint on the part of monetary authorities resulting from a much reduced tolerance for currency depreciation. This creates conditions for the forint to outperform. Poland In the meantime, Polish monetary authorities have switched into an ultra-accommodative mode. Recent policy announcements by the National Bank of Poland (NBP) represent the most dramatic example of policy easing in Central Europe. Such a policy stance in Poland will produce lower real rates than in Hungary, which is negative for the Polish zloty against the forint. The NBP is set to finance the majority of a new 11% of GDP fiscal spending program enacted by the government amid the COVID-19 lockdowns. This amounts to de-facto public debt and fiscal deficit monetization. The latter will not be sterilized unlike in Hungary and will therefore lead to an excess liquidity overflow in the banking system. The Polish central bank has cut interest rates by 140 bps to 10 bps since March. Pushing nominal rates down close to zero has produced more negative real policy rates than in Hungary (Chart I-2, top panel on page 2). Also, Polish prime lending rates in real terms have fallen below those in Hungary (Chart I-2, bottom panel). Chances are that inflation in Poland will also prove to be stickier than in Hungary due to the minimum wage raise at the beginning of the year and very aggressive fiscal and monetary stimulus since the pandemics has erupted (Chart I-5). Critically, the Polish economy is much less open than Hungary’s, and it is therefore less vulnerable to the collapse of pan-European manufacturing and tourism. This will ensure better employment and wage conditions in Poland. All in all, Poland’s final demand outperformance, versus Hungary, will contribute to a higher rate of inflation there. Bottom Line: The central bank in Poland will stay super accommodative while the National Bank of Hungary will be a bit less aggressive. This is producing a U-turn in both countries’ nominal and relative real interest rates, which heralds a reversal in the HUF / PLN cross rate (Chart I-6). Chart I-5Polish Inflation Will Be Sticker Than In Hungary Chart I-6Go Long HUF / Short PLN   Investment Strategy For Central Europe A new trade: go long the HUF versus the PLN. Take a 3% profit on the short HUF and PLN / long CZK trade. Close the short IDR / long PLN trade with a 20% loss. Downgrade central European bourses (Polish, Czech and Hungarian) from an overweight to a neutral allocation within the EM equity benchmark. Lower for longer European interest rates disfavor bank stocks that dominate central European bourses. Andrija Vesic Associate Editor andrijav@bcaresearch.com Colombia: Continue Betting On Lower Rates Colombia has been badly hit by two shocks: the precipitous fall in oil prices and the strict quarantine measures to constrain the spread of the COVID-19 outbreak. An underwhelming fiscal stimulus in response to the lockdowns will further weigh on private demand. An underwhelming fiscal stimulus in response to the lockdowns will further weigh on private demand. We have been recommending receiving 10-year swap rates in Colombia since April 23rd and this strategy remains unchanged: While oil prices seem to have rebounded sharply, they will remain structurally low (Chart II-1). The Emerging Markets Strategy team's view is that oil prices will average $40 per barrel this year and next.1 After the recent rally, chances of further upside in crude prices are limited. Chart II-1A Long-Term Perspective On Oil Prices Table II-1Colombia’s Fiscal Package Is The Lowest In The Region Colombia's high sensitivity to oil prices is particularly visible via its current account balance. Indeed, Colombia’s net crude exports cover as much as 50% of the current account deficit, such that low oil prices severely affect the currency and produce a negative income shock for the economy. Fiscal policy remains unreasonably tight, especially in the face of the global pandemic. The government’s fiscal response plan amounts to only a meagre 1.5% of GDP. This is low not only compared to advanced economies but also to the rest of Latin America (Table II-1). Moreover, President Duque’s administration has been running the tightest fiscal budget in almost a decade, with the primary fiscal balance reaching 1% of GDP before the pandemic. The country’s COVID-19 response has been fast and effective. Colombia has managed to achieve the lowest amount of infections and deaths among major economies in Latin America (Chart II-2). Chart II-2COVID-19 Casualties Across Latin America Duque’s administration has taken a pragmatic approach to handling the pandemic by enforcing strict lockdowns and banning international and inter-municipal travel since late March, only three days after the country’s first casualty. Further, the nationwide confinement measures have been extended until July 1st, with particularly stringent rules applying to major cities. These have helped the country avoid a nation-wide health crisis, but they will engender prolonged economic pain. Regarding monetary stimulus, the central bank (Banrep) has cut interest rates by 150 basis points since March of this year. It also embarked on the first and largest QE program in the region. Banrep has committed to purchase 12 trillion pesos worth of government and corporate securities (amounting to a whopping 8% of GDP). Consumer price inflation is falling across various core measures and will drop below the low end of Banrep’s target range (Chart II-3). This will push the central bank to continue cutting rates. Despite the monetary easing, nominal lending rates are still restrictive. Real lending rates (deflated by core CPI) remain elevated at 7% (Chart II-4). Chart II-3Colombia: Inflation Will Fall Below Target Chart II-4Colombia: Real Lending Rates Are Still High Chart II-5The Colombian Economy Was Already Under Pressure Importantly, there has not been an appropriate amount of credit support and debt waving programs for SMEs, as there has been in many other countries. Given that SMEs employ a large share of the workforce, and that household spending accounts for about 70% of GDP, consumer spending and overall economic growth will contract substantially and be slow to recover. Employment rates had already been contracting, and wage growth downshifting, before the pandemic started (Chart II-5). Household income is now certainly in decline as major cities are in full lockdown and economic activity is frozen. Investment Recommendations Even though we are structurally positive on the country due to its orthodox macroeconomic policies, positive structural reforms, and low levels of debt among both households and companies, we maintain a neutral allocation on Colombian stocks within an EM equity portfolio. This bourse is dominated by banks and energy stocks. The lack of both fiscal support and bank loan guarantees amid the recession means that banks will carry the burden of ultimate losses. They will suffer materially due to loan restructuring and defaults. For fixed income investors, we reiterate our call to receive 10-year swap rates and recommend overweighting local currency government bonds versus the EM domestic bond benchmark. The yield curve is steep and real bond yields are elevated (Chart II-6). Hence, long-term interest rates offer great value. Additional monetary easing, including quantitative easing, will suppress yields much further. Chart II-6A Great Opportunity In Colombian Rates Chart II-7The COP Has Depreciated Considerably   We are upgrading Colombia sovereign credit from neutral to overweight within an EM credit portfolio. General public debt (including the central and state governments) stands at 59% of GDP. Conservative fiscal policy and the central bank’s large purchases of local bonds will allow the government to finance itself locally. Presently, 40% of public debt is foreign currency and 60% local currency denominated. As a result, sovereign credit will outperform the EM credit benchmark. In terms of the currency, we recommend investors to be cautious for now. Even though the peso is cheap (Chart II-7), another relapse in oil prices or a potential flare up in social protests could cause further downfall in the currency. Juan Egaña Research Associate juane@bcaresearch.com   1 This differs from the view of BCA’s Commodities and Energy Strategy service. We believe structural forces such as the lasting decline in air travel and commuting will impede a recovery in oil demand while, at the same time, US shale production will rise again considerably if crude prices rise and remain well above $40   Equities Recommendations Currencies, Credit And Fixed-Income Recommendations

  In a webcast this Friday I will be joined by our Chief US Equity Strategist, Anastasios Avgeriou to debate ‘Sectors To Own, And Sectors To Avoid In The Post-Covid World’. Today’s report preludes five of the points that we will debate. Please join us for the full discussion and conclusions on Friday, June 12, at 8:00 AM EDT (1:00 PM BST, 2:00 PM CEST, 8.00 PM HKT).   Highlights Technology is behaving like a Defensive. Defensive versus Cyclical = Growth versus Value. Growth stocks are not a bubble if bond yields stay ultra-low. The post-Covid world will reinforce existing sector mega-trends. Sectors are driving regional and country relative performance. Fractal trade: Long ZAR/CLP.   Chart of the WeekSector Defensiveness/Cyclicality = Positive/Negative Sensitivity To The Bond Price 1. Technology Is Behaving Like A Defensive How do we judge an equity sector’s sensitivity to the post-Covid economy, so that we can define it as cyclical or defensive? One approach is to compare the sector’s relative performance with the bond price. According to this approach, the more negatively sensitive to the bond price, the more cyclical is the sector. And the more positively sensitive to the bond price, the more defensive is the sector (Chart I-1).   On this basis the most cyclical sectors in the post-Covid economy are, unsurprisingly: energy, banks, and materials. Healthcare is unsurprisingly defensive. Meanwhile, the industrials sector sits closest to neutral between cyclical and defensive, showing the least sensitivity to the bond price. The tech sector’s vulnerability to economic cyclicality appears to have greatly reduced. The big surprise is technology, whose high positive sensitivity to the bond price during the 2020 crisis qualifies it as even more defensive than healthcare. This contrasts sharply with its behaviour during the 2008 crisis. Back then, tech’s relative performance was negatively correlated with the bond price, defining it as classically cyclical. But over the past year, tech’s relative performance has been positively correlated with the bond price, defining it as classically defensive (Chart I-2 and Chart I-3). Chart I-2In 2008, Tech Behaved Like ##br##A Cyclical... Chart I-3...But In 2020, Tech Is Behaving Like A Defensive This is not to say that the big tech companies cannot suffer shocks. They can. For example, from new superior technologies, or from anti-oligopoly legislation. However, the tech sector’s vulnerability to economic cyclicality appears to have greatly reduced over the past decade. 2. Defensive Versus Cyclical = Growth Versus Value If we reclassify the tech sector as defensive in the 2020s economy, then the post mid-March rebound in stocks was first led by defensives. Cyclicals took over leadership of the rally only in May. Moreover, with the reclassification of tech as defensive, the two dominant defensive sectors become tech and healthcare. But tech and healthcare are also the dominant ‘growth’ sectors. The upshot is that growth versus value has now become precisely the same decision as defensive versus cyclical (Chart I-4). Chart I-4Defensive Versus Cyclical = Growth Versus Value 3. Growth Stocks Are Not A Bubble If Bond Yields Stay Ultra-Low Some people fear that growth stocks have become dangerously overvalued. There is even mention of the B-word. Let’s address these fears. Yes, valuations have become richer. For example, the forward earnings yield for healthcare is down to 5 percent; and for big tech it is down to just over 4 percent. This valuation starting point has proved to be an excellent guide to prospective 10-year returns, and now implies an expected annualised return from big tech in the mid-single digits. Yet this modest positive return is well above the extremes of the negative 10-year returns implied and delivered from the dot com bubble (Chart I-5). Chart I-5Big Tech Is Priced To Deliver A Positive Return, Unlike In 2000 Moreover, we must judge the implied returns from growth stocks against those available from competing long-duration assets – specifically, against the benchmark of high-quality government bond yields. If bond yields are ultra-low, then they must depress the implied returns on growth stocks too. Meaning higher absolute valuations (Chart I-6 and Chart I-7). Chart I-6Tech's Forward Earnings Yield Is Above The Bond Yield, Unlike In 2000 Chart I-7Healthcare's Forward Earnings Yield Is Above The Bond Yield, Unlike In 2000 In the real bubble of 2000, big tech was priced to return 12 percent (per annum) less than the 10-year T-bond. Whereas today, the implied return from big tech – though low in absolute terms – is above the ultra-low yield on the 10-year T-bond. If bond yields are ultra-low, then they must depress the implied returns on growth stocks too. The upshot is that high absolute valuations of growth stocks are contingent on bond yields remaining at ultra-low levels. And that the biggest threat to growth stock valuations would be a sustained rise in bond yields. 4. The Post-Covid World Will Reinforce Existing Sector Mega-Trends If a sector maintains a structural uptrend in sales and profits, then a big drop in the share price provides an excellent buying opportunity for long-term investors. This is because the lower share price stretches the elastic between the price and the up-trending profits, resulting in an eventual catch-up. However, if sales and profits are in terminal decline, then the sell-off is not a buying opportunity other than on a tactical basis. This is because the elastic will lose its tension as profits drift down towards the lower price. In fact, despite the sell-off, if the profit downtrend continues, the price may be forced ultimately to catch-down. This leads to a somewhat counterintuitive conclusion. After a big drop in the stock market, long-term investors should not buy everything that has dropped. And they should not buy the stocks and sectors that have dropped the most if their profits are in major downtrends. In this regard, the post-Covid world is likely to reinforce the existing mega-trends. The profits of oil and gas, and of European banks will remain in major structural downtrends (Chart I-8 and Chart I-9). Conversely, the profits of healthcare, and of European personal products will remain in major structural uptrends (Chart I-10 and Chart I-11). Chart I-8Oil And Gas Profits In A Major ##br##Downtrend Chart I-9Bank Profits In A Major ##br##Downtrend Chart I-10Healthcare Profits In A Major Uptrend Chart I-11Personal Products Profits In A Major Uptrend   5. Sectors Are Driving Regional And Country Relative Performance Finally, sector winners and losers determine regional and country equity market winners and losers. Nowadays, a stock market’s relative performance is predominantly a play on its distinguishing overweight and underweight ‘sector fingerprint’. This is because major stock markets are dominated by multinational corporations which are plays on their global sectors, rather than the region or country in which they have a stock market listing. It follows that when tech and healthcare outperform, the tech-heavy and healthcare-heavy US stock market must outperform, while healthcare-lite emerging markets (EM) must underperform. It also follows that the tech-heavy Netherlands and healthcare-heavy Denmark stock markets must outperform. Sector mega-trends will shape the mega-trends in regional and country relative performance. Equally, when energy and banks underperform, the energy-heavy Norway and bank-heavy Spain stock markets must underperform. (Chart I-12 and Chart I-13). These are just a few examples. Every stock market is defined by a sector fingerprint which drives its relative performance.  Chart I-12Sector Relative Performance Drives... Chart I-13...Regional And Country Relative Performance If sector mega-trends continue, they will also shape the mega-trends in regional and country relative performance – favouring those stock markets that are heavy in growth stocks and light in old-fashioned cyclicals. Please join the webcast to hear the full debate and conclusions. Fractal Trading System*  This week’s recommended trade is to go long the South African rand versus the Chilean peso. Set the profit target and symmetrical stop-loss at 5 percent. In other trades, long Spanish 10-year bonds versus New Zealand 10-year bonds achieved its 3.5 percent profit target at which it was closed. And long Australia versus New Zealand equities is approaching its 12 percent profit target. The rolling 1-year win ratio now stands at 63 percent. Chart I-14ZAR/CLP   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 Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields   Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch - Interest Rate Expectations  

Special Report

Highlights Volatility strategies are a useful tool for asset allocators. They can be used for both alpha generation and risk mitigation, but they have to be managed properly within a fund’s total risk management framework. Dedicated tail-risk hedging can reduce volatility, but can be very costly depending on the holding period. Short volatility strategies can generate alpha, but can also incur large losses when volatility spikes. Long volatility and also relative-value volatility strategies are much better alpha generators. A simple and easy-to-implement rule-based dynamic hedging strategy using short-term VIX futures reduces equity portfolio risk significantly without sacrificing return. The Sensational Headlines The COVID-19 pandemic-induced financial market volatility has put two major pension funds in the proverbial spotlight. First, CalPERS was questioned about its October 2019 decision to unwind its tail-risk hedging program that would have generated a payoff of more than US$1 billion during the March equity market selloff.1 Then, AIMCo was said to have lost over C$3 billion in its short volatility program, and was also forced to shut the program down.2 With such high-profile stories making the rounds, it is not surprising that we have received questions about tail-risk hedging and volatility strategies from many clients: Should long-term investors hedge tail risk? Is short volatility not a suitable strategy for pension funds? What are the efficient ways to manage large drawdowns? Chart 1The High Profile Failures: Not Uncommon Before we attempt to answer these questions, we want to first point out that tail-risk hedging and short-volatility strategies are negatively correlated, as shown in Chart 1, panel 1. It is normal for short-volatility strategies to suffer large drawdowns when tail-hedging strategies make handsome gains in periods of extreme financial market stress. This is largely due to the nature of volatility. As shown in panel 2 in Chart 1, VIX futures curves are normally in contango (the far-month contract is higher than the near-month contract), so a plain-vanilla short position in VIX futures benefits from positive rolling yields, while a plain-vanilla long position suffers from negative rolling yields. When VIX spikes, however, the futures curve turns into large backwardation (the far-month contract is lower than the near-month contract) in a fast and furious fashion, hence the large insurance-like payoff. The short-volatility and tail-hedge indexes in Chart 1 are from CBOE Eurekahedge, which has a suite of volatility indexes. As shown in Table 1, these indexes track the average performance of hedge funds that employ various volatility strategies, including tail-risk volatility, long volatility, short volatility and relative-value volatility. Table 1CBOE Eurekahedge Volatility Hedge Fund Indexes*  The performance statistics of these indexes are shown in Table 2. It is clear that not all volatility strategies are created equal. Below, we explore in more detail how these strategies should be used. Table 2CBOE Eurekahedge Volatility Index Performance Statistics Tail-Risk Hedging Is Not Free Tail-risk hedging has been in the news of late, given the unprecedently sharp drop in equities in February and March and also the untimely decision by CalPERS to unwind its tail-risk hedging program last October. So, what is tail-risk-hedging exactly? How does it work? Tail-risk hedging strategies aim to profit from large drawdowns in risky assets. Unlike the traditional approach of diversification that reduces the weighting of risky assets (for example, a 60-40 equity-bond portfolio is less risky than a 100% equity portfolio), tail-risk hedging attempts to allocate a small percentage of capital, say 3-5%, to a specially designed insurance-like payoff, while maintaining exposure to the risky asset. As such, tail-risk hedging is like buying an insurance policy against a catastrophic event. The premiums paid may or may not be recouped, depending on how likely it is that a catastrophic event may occur and how long one has held the insurance policy. The Universa Tail Fund is one of the two tail-risk funds that CalPERS made the untimely decision to redeem. The fund returned 3,600% in March alone, and 4,440% in the first quarter of 2020. As well, according to reports, a portfolio with 96.7% in the S&P 500 and 3.3% in Universa’s tail-risk fund would effectively have mitigated the S&P 500’s large loss in March, and would have also produced a compounded return of 11.5% since March 2008 versus 7.9% for the S&P 500.3  The performance of the Universa Tail Fund seems to be very different from the average hedge fund in this category, as shown in Table 2 and Chart 1. The CBOE Eurekahedge Tail Risk Hedge Fund index is an average of eight hedge funds that employ tail-risk strategies to achieve capital appreciation during periods of market stress. Since December 2007, when the index started, it has had two outsized monthly gains: 37.5% in March 2020 and 27.5% in August 2011, when MSCI US equities lost 12.7 and 5.5%. However, such benefit is very costly from a long-term perspective because the index has generated an annualized loss of 2.5%, even through April 2020. Its arithmetic average during the period is about -1.6%. To better understand why Universa has been doing so much better than the “average” tail risk hedge fund, we replicate a stylized exercise by Universa published in October 2017.4 The only difference is that we use the MSCI US equity total return index instead of the S&P 500 index. The payoff structure of 9 to 1 means that when the MSCI US calendar year return is less than -15%, the hedge would generate a return of 900%. In other years, insurance premium is not recouped at all, i.e. there is a loss of 100%. The original exercise by Universa designed such a payoff structure because it aimed to have an average payoff of zero in the period from 1996 to 2016. As shown in Chart 2, the biggest advantage of the tail-hedged portfolio (97% MSCI US + 3% Insurance) is its much smoother return stream, with a standard deviation of 12.9% compared to 17.7% for the unhedged MSCI US equity portfolio based on calendar year returns from 1970 to 2020 (as of March for 2020). Also, the skew is improved to -0.1 from -0.7. In terms of return, however, it is highly variable depending on the period chosen. The hedged portfolio outperformed the MSCI US total return index by about 70 basis points annualized from 1996 to 2016, consistent with the result from the original exercise by Universa.5 Outside this period, however, the average return of the payoff stream really depends on how often US equities fall below -15% yearly. In the 50-year period from December 1969 to December 2019, the average return of the insurance payoff was -20%, and the tail-hedged program underperformed MSCI US by 26 basis points annualized. Chart 2Universa Exercise Replica* For 12/1969 - 3/2020 This simple stylized exercise shows that both the starting point to initiate the tail-risk hedge and the length of time to hold the hedge are very important for a tail-risk hedge to work, not to mention generate spectacular results. Like a catastrophic insurance policy, a tail hedge should not be considered as a stand-alone strategy but as a hedge to the underlying portfolio. It is critical to design the right payoff structure, which in turn requires a view on how often a large drawdown will likely happen in the forecast period. It also takes special skill to find the right instruments to implement such a payoff structure and manage it accordingly. As we will show in the section on page 9, a dynamic approach is needed to ensure the hedge is on only when it’s needed to reduce cost. In fact, Universa did mention about using extreme valuation as one indicator to identify periods with high likelihood of downside risks.6 It also locked in a massive gain in March 2020,7 another indication of the “dynamic nature” of tail-hedging management. Bottom Line: From a long-term perspective, tail-risk hedge does not significantly improve compound returns, but it does reduce volatility significantly. Unless an investor has the skill to dynamically manage a hedge program, passively holding a tail-risk hedge can be costly in terms of return, even though it does improve risk-adjusted returns. Is A Short-Volatility Strategy Suitable For Pension Funds? The CBOE Eurekhedge Short Volatility index lost 20.8% in the first four months of 2020, in which March was the worst month in its history since December 2004, with a loss of 15.8%, while April was the best month with a gain of 9.3%. The annualized return since December 2004, however, has been 5.4%, and 73% of monthly returns have been in positive territory (Table 2). On the other hand, AIMCo had to shut down its volatility trading program in March because of its large $3 billion loss, or about 2.5% of its $119 billion of AUM. It is not known why a small volatility program was allowed to lose more than the fund’s total full-year value-add target. Chart 3Volatility Measures: Implied Vs. Realized There are different ways to short volatility. One is to sell options on the underlying assets. This approach, however, is also impacted by the price level of the underlying assets. VIX futures, as shown in Chart 1, panel 2, are a way to bet on the change in implied volatility. Another way to short volatility is via variance swaps, which bet on the change between realized variance at the expiry of the swap and the strike variance, which is set according to both historical variance and implied variance.8 Because variance is the square of volatility, the payoff of a variance swap is convex, i.e. when volatility spikes up, a short seller loses more money than when volatility decreases. As shown in Chart 3, VIX, the implied volatility, peaked on March 16, and realized volatility peaked on March 27. However, the difference between realized and implied volatility did not peak until April 6, and remained positive through the end of April. As such, a short volatility program via variance swaps would have experienced severe mark-to-market losses daily from mid-March to early April, even though equities bottomed on March 23.   However, such a spike happened in 2008 as well. Any back-test would have included such an occurrence in 2008. Granted, the magnitude of the current spike is larger than that in 2008, but it reversed quickly down to the 2008 level. We may never know why AIMCo’s short volatility program suffered such outsized losses. The only guess is that it may have used variance swaps, and the embedded leverage made the size of the program not appropriate for the total fund. Bottom Line: Short volatility can be a useful tool for alpha generation. The key, however, is risk management. It should be properly sized within the overall risk management framework of the total fund. Volatility As An Asset Class? Tail-risk hedging using volatility is too costly in general, while shorting volatility outright can be disastrous. Some argue that investors should not have anything to do with volatility strategies. On the other hand, other investors treat volatility as an asset class for both alpha generation and risk mitigation. Chart 4 shows the CBOE Eurekahedge Relative-Value Volatility index and the Long-Volatility index together with the MSCI US equity index, and Bloomberg Barclays US aggregate bond index and US Treasury index. The relative-value volatility index can be long, short, or neutral on volatility (Table 1). As shown in Table 2, it has achieved an annualized return of 7.6%, only 60 basis points less than MSCI US equity return of 8.2%, but much higher than the 4.3% and 4.5% respective return from Bloomberg Barclays US Treasury index and aggregate bond index in the period from December 2004 to April 2020. Its standard deviation of 3.9% is much lower than the MSCI US (14.7%) and very close to Treasurys (4.1%) and aggregate bonds (3.2%). For this specific period, in fact, this index even has a much better risk-return profile than a typical 60/40 US equity/aggregate-bond portfolio, which scores a 7.1% annualized return with 8.9% standard deviation. With almost zero correlation to both stocks and bonds, this index serves as an ideal addition to a balanced equity-bond portfolio (Chart 5). Chart 4Volatility As An Asset Class Chart 5Relative-Value Vol Strategy Improves The Performance Of A 60/40 Equity/Bond Portfolio The challenge, however, is that this index is an average of 35 hedge funds that employ relative-value or opportunistic-volatility strategies that can be long, short, or neutral on implied volatility.9 Because of this, capacity constraints for investors to get into those funds may exist, which could produce diverging performances. Even the long-volatility strategy (Chart 4, panel 2), which in theory suffers negative rolling yields when the VIX is in a normal range, has generated a 5% annualized return. It has a negative correlation of 0.46 with MSCI US equities, comparable to the negative correlation of 0.5 between the Tail-Risk index and MSCI US. Given the much better statistics of this index compared to the Tail-Risk index, it should be a less costly alternative to the Tail-Risk Hedge index (Table 2). To illustrate how these two strategies work to mitigate downside risk in the MSCI US equities, we compare a series of portfolios that allocate from 0-100% of capital to MSCI US and 100-0% to the two volatility strategies, respectively. As shown in Chart 6, the long-volatility strategy is a much better risk mitigator to the MSCI US equities index than the tail-hedge strategy at all levels of allocations for the period from January 2008 to April 2020.  Chart 6Risk Mitigation Using Long Vol Vs. Tail-Risk Hedge Dynamic Hedging Using VIX Futures The CBOE Eurekahedge volatility indexes are based on average returns of the funds in each index. They are not investable. Also, hedge funds in these indexes may have capacity issues to accommodate large investors. In this section we run a simple rule-based hedging strategy using VIX futures to illustrate how investors can use volatility strategies in-house as an alternative tool to mitigate risk. We use the S&P VIX short-term futures index for this exercise, because it can be easily replicated in-house. This index is constructed based on rolling daily 5% of the front-month contract to the second-month contract. This means the index always has one month to expiry. It also means that daily rolling averages out the rolling yield for any given month.  The rule is simple: invest in the short-term volatility futures only when the VIX is outside its normal range. Since its inception in 1990, the VIX average is about 20. To test how different thresholds and rebalancing frequencies work, we test four different VIX thresholds: 25, 30, 35 and 40 with both weekly and monthly rebalances. The rebalance rule is: if the VIX is greater than a threshold at the end of one period, then in the next period, 5% of the fund is allocated to the S&P short-term VIX futures index and 95% is allocated to MSCI US. Otherwise 100% goes to MSCI US equities. For comparison, we also run a static hedge that has 5% in VIX futures and 95% in the MSCI US index.  The monthly rebalanced results are quite interesting, as shown in Table 3 and Chart 7: Table 3Dynamic Hedging Using VIX Futures Chart 7Dynamic Hedging Works Despite a terrible risk-return profile on its own, VIX futures can be a good risk mitigator when the hedge is put on only when the VIX is above a certain threshold.  Even though the 60-40 wins in terms of risk-adjusted return, dynamically hedged portfolios have better returns than both the 60-40 and US equities. The results are also robust when we do a weekly rebalance. Three conclusions can be drawn from Charts 8A and 8B, and Chart 9: Chart 8ADynamic Hedging – Monthly Rebalance Chart 8BDynamic Hedging – Weekly Rebalance     Chart 9Simple But Robust Dynamic Hedging   Hedging reduces volatility significantly. The lower the VIX threshold is, the larger the volatility reduction in the hedged portfolio compared to the unhedged. Hedging also improves average returns, albeit at a smaller scale compared to the reductions in volatility. Depending on the rebalancing frequency, the return improvement differs. For the monthly rebalance, the best VIX threshold lies between 30-35; for the weekly rebalance, the best is when the VIX threshold is at 30. Hedging is not needed all the time because volatility is within a normal range most of the time. Even when it spikes, it does not stay high for an extended period of time. Bottom Line: A simple rule-based dynamic hedging approach using VIX futures can substantially improve an equity portfolio’s risk-return profile by decreasing volatility significantly without sacrificing return. In a low interest rate environment, dynamic hedging using VIX futures can be a good alternative to a 60-40 equity-bond mix.   Xiaoli Tang Associate Vice President xiaoliT@bcaresearch.com   Footnotes 1  https://www.institutionalinvestor.com/article/b1l65mvpw5xpts/The-Inside-Story-of-CalPERS-Untimely-Tail-Hedge-Unwind 2 https://www.institutionalinvestor.com/article/b1l9c8n9lgdj1r/AIMCo-s-3-Billion-Volatility-Trading-Blunder 3 https://www.bloomberg.com/news/articles/2020-04-08/taleb-advised-universa-tail-risk-fund-returned-3-600-in-march 4 https://www.universa.net/UniversaResearch_SafeHavenPart1_RiskMitigation.pdf 5  https://www.universa.net/UniversaResearch_SafeHavenPart1_RiskMitigation.pdf 6 https://www.universa.net/UniversaResearch_SafeHavenPart2_NotAllRisk.pdf 7 https://www.bloomberg.com/news/articles/2020-04-08/taleb-advised-universa-tail-risk-fund-returned-3-600-in-march 8  https://en.wikipedia.org/wiki/Variance_swap 9 https://www.eurekahedge.com/Indices/CBOE-Eurekahedge-Volatility-Indexes-Methodology  

The SPX catapulted to fresh recovery highs, on the back of optimism surrounding the successful reopening of the economy along with the ongoing support of easy fiscal and monetary policies. Sentiment is not as extended as in February or during previous SPX tops in the past few years, as we highlighted in recent research.1 Equity market internals signal that there is likely a bit more gas left in the tank, despite the roughly 1000 point rise since the March 23 lows. The S&P deep cyclicals/defensives share price ratio, has led the broad equity market bottom and continues to herald additional gains for the SPX (not shown). Deep cyclicals include tech stocks, but even if IT were excluded, the cyclicals ex-tech/defensives ratio still troughed prior to the SPX and is gaining steam. Importantly, the turn in our Global Trade Activity Indicator corroborates the message that the cyclicals/defensives ratio is emitting (see chart). Further, the recent breakout in the JPM EM currency index along with budding evidence of China’s economic recovery and likelihood of a stimulus package (not as large as the GFC, but bigger than the early-2016 manufacturing recession one) suggest that global growth is slated to recover in the back half of the year. Bottom Line: We remain constructive on the broad market’s prospects  over the coming 9-12 month time horizon. For more details, please refer to this Monday’s Weekly Report.   Footnotes 1  Please see BCA US Equity Strategy Weekly Report, “There’s No Limit” dated May 26, 2020, available at uses.bcaresearch.com.