ETFs vs. Hedge Funds – Why Not Combine Both?

Grace Kim, Brand Director at DarcMatter, does a good job of setting out the pros and cons of ETFs vs hedge funds for the family office investor in her LinkedIn post.

She points out that ETFs now offer as much liquidity as hedge funds, both now having around $2.96 trillion in assets.  So, too, are her points well made about the low cost, diversification and ease of investing in ETFs compared to hedge funds.

But, of course, the point of ETF investing is to mimic the return in some underlying market – to gain beta exposure, in the jargon – whereas hedge fund investing is all about alpha – the incremental return that is achieved over and above the return attributable to market risk factors.

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But should an investor be forced to choose between the advantages of diversification and liquidity of ETFs on the one hand and the (supposedly) higher risk-adjusted returns of hedge funds, on the other?  Why not both?

Diversified Long/Short ETF Strategies

In fact, there is nothing whatever to prevent an investment strategist from constructing a hedge fund strategy using ETFs.  Just as one can enjoy the hedging advantages of a long/short equity hedge fund portfolio, so, too, can one employ the same techniques to construct long/short ETF portfolios.  Compared to a standard equity L/S portfolio, an ETF L/S strategy can offer the added benefit of exposure to (or hedge against) additional risk factors, including currency, commodity or interest rate.

For an example of this approach ETF long/short portfolio construction, see my post on Developing Long/Short ETF Strategies.  As I wrote in that article:

My preference for ETFs is due primarily to the fact that  it is easier to achieve a wide diversification in the portfolio with a more limited number of securities: trading just a handful of ETFs one can easily gain exposure, not only to the US equity market, but also international equity markets, currencies, real estate, metals and commodities.

More Exotic Hedge Fund Strategies with ETFs

But why stop at vanilla long/short strategies?  ETFs are so varied in terms of the underlying index, leverage and directional bias that one can easily construct much more sophisticated strategies capable of tapping the most obscure sources of alpha.

Take our very own Volatility ETF strategy for example.  The strategy constructs hedged positions, not by being long/short, but by being short/short or long/long volatility and inverse volatility products, like SVXY and UVXY, or VXX and XIV.  The strategy combines not only strategic sources of alpha that arise from factors such as convexity in the levered ETF products, but also short term alpha signals arising from temporary misalignments in the relative value of comparable ETF products.  These can be exploited by tactical, daytrading algorithms of a kind more commonly applied in the context of high frequency trading.

For more on this see for example Investing in Levered ETFs – Theory and Practice.

Does the approach work?  On the basis that a picture is worth a thousand words, let me answer that question as follows:

Systematic Strategies Volatility ETF Strategy

Perf Summary Dec 2015

Conclusion

There is no reason why, in considering the menu of ETF and hedge fund strategies, it should be a case of either-or.  Investors can combine the liquidity, cost and diversification advantages of ETFs with the alpha generation capabilities of well-constructed hedge fund strategies.

The Case for Volatility as an Asset Class

Volatility as an asset class has grown up over the fifteen years since I started my first volatility arbitrage fund in 2000.  Caissa Capital grew to about $400m in assets before I moved on, while several of its rivals have gone on to manage assets in the multiple billions of dollars.  Back then volatility was seen as a niche, esoteric asset class and quite rightly so.  Nonetheless, investors who braved the unknown and stayed the course have been well rewarded: in recent years volatility strategies as an asset class have handily outperformed the indices for global macro, equity market neutral and diversified funds of funds, for example. Fig 1

The Fundamentals of Volatility

It’s worth rehearsing a few of the fundamental features of volatility for those unfamiliar with the territory.

Volatility is Unobservable

Volatility is the ultimate derivative, one whose fair price can never be known, even after the event, since it is intrinsically unobservable.  You can estimate what the volatility of an asset has been over some historical period using, for example, the standard deviation of returns.  But this is only an estimate, one of several possibilities, all of which have shortcomings.  We now know that volatility can be measured with almost arbitrary precision using an integrated volatility estimator (essentially a metric based on high frequency data), but that does not change the essential fact:  our knowledge of volatility is always subject to uncertainty, unlike a stock price, for example.

Volatility Trends

Huge effort is expended in identifying trends in commodity markets and many billions of dollars are invested in trend following CTA strategies (and, equivalently, momentum strategies in equities).  Trend following undoubtedly works, according to academic research, but is also subject to prolonged drawdowns during periods when a trend moderates or reverses. By contrast, volatility always trends.  You can see this from the charts below, which express the relationship between volatility in the S&P 500 index in consecutive months.  The r-square of the regression relationship is one of the largest to be found in economics. Fig 2 And this is a feature of volatility not just in one asset class, such as equities, nor even for all classes of financial assets, but in every time series process for which data exists, including weather and other natural phenomena.  So an investment strategy than seeks to exploit volatility trends is relying upon one of the most consistent features of any asset process we know of (more on this topic in Long Memory and Regime Shifts in Asset Volatility).

Volatility Mean-Reversion and Correlation

One of the central assumptions behind the ever-popular stat-arb strategies is that the basis between two or more correlated processes is stationary. Consequently, any departure from the long term relationship between such assets will eventually revert to the mean. Mean reversion is also an observed phenomenon in volatility processes.  In fact, the speed of mean reversion (as estimated in, say, an Ornstein-Ulenbeck framework) is typically an order of magnitude larger than for a typical stock-pairs process.  Furthermore, the correlation between one volatility process and another volatility process, or indeed between a volatility process and an asset returns process, tends to rise when markets are stressed (i.e. when volatility increases). Fig 3

Another interesting feature of volatility correlations is that they are often lower than for the corresponding asset returns processes.  One can therefore build a diversified volatility portfolio with far fewer assets that are required for, say, a basket of equities (see Modeling Asset Volatility for more on this topic).

Fig 4   Finally, more sophisticated stat-arb strategies tend to rely on cointegration rather than correlation, because cointegrated series are often driven by some common fundamental factors, rather than purely statistical ones, which may prove temporary (see Developing Statistical Arbitrage Strategies Using Cointegration for more details).  Again, cointegrated relationships tend to be commonplace in the universe of volatility processes and are typically more reliable over the long term than those found in asset return processes.

Volatility Term Structure

One of the most marked characteristics of the typical asset volatility process its upward sloping term structure.  An example of the typical term structure for futures on the VIX S&P 500 Index volatility index (as at the end of May, 2015), is shown in the chart below. A steeply upward-sloping curve characterizes the term structure of equity volatility around 75% of the time.

Fig 5   Fixed income investors can only dream of such yield in the current ZIRP environment, while f/x traders would have to plunge into the riskiest of currencies to achieve anything comparable in terms of yield differential and hope to be able to mitigate some of the devaluation risk by diversification.

The Volatility of Volatility

One feature of volatility processes that has been somewhat overlooked is the consistency of the volatility of volatility.  Only on one occasion since 2007 has the VVIX index, which measures the annual volatility of the VIX index, ever fallen below 60.

Fig 6   What this means is that, in trading volatility, you are trading an asset whose annual volatility has hardly ever fallen below 60% and which has often exceeded 100% per year.  Trading opportunities tend to abound when volatility is consistently elevated, as here (and, conversely, the performance of many hedge fund strategies tends to suffer during periods of sustained, low volatility)

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Anything You Can Do, I Can Do better

The take-away from all this should be fairly obvious:  almost any strategy you care to name has an equivalent in the volatility space, whether it be volatility long/short, relative value, stat-arb, trend following or carry trading. What is more, because of the inherent characteristics of volatility, all these strategies tend to produce higher levels of performance than their more traditional counterparts. Take as an example our own Volatility ETF strategy, which has produced consistent annual returns of between 30% and 40%, with a Sharpe ratio in excess of 3, since 2012.   VALUE OF $1000

Sharpe

  Monthly Returns

 

(click to enlarge)

Where does the Alpha Come From?

It is traditional at this stage for managers to point the finger at hedgers as the source of abnormal returns and indeed I will do the same now.   Equity portfolio managers are hardly ignorant of the cost of using options and volatility derivatives to hedge their portfolios; but neither are they likely to be leading experts in the pricing of such derivatives.  And, after all, in a year in which they might be showing a 20% to 30% return, saving a few basis points on the hedge is neither here nor there, compared to the benefits of locking in the performance gains (and fees!). The same applies even when the purpose of using such derivatives is primarily to produce trading returns. Maple Leaf’s George Castrounis puts it this way:

Significant supply/demand imbalances continuously appear in derivative markets. The principal users of options (i.e. pension funds, corporates, mutual funds, insurance companies, retail and hedge funds) trade these instruments to express a view on the direction of the underlying asset rather than to express a view on the volatility of that asset, thus making non-economic volatility decisions. Their decision process may be driven by factors that have nothing to do with volatility levels, such as tax treatment, lockup, voting rights, or cross ownership. This creates opportunities for strategies that trade volatility.

We might also point to another source of potential alpha:  the uncertainty as to what the current level of volatility is, and how it should be priced.  As I have already pointed out, volatility is intrinsically uncertain, being unobservable.  This allows for a disparity of views about its true level, both currently and in future.  Secondly, there is no universal agreement on how volatility should be priced.  This permits at times a wide divergence of views on fair value (to give you some idea of the complexities involved, I would refer you to, for example, Range based EGARCH Option pricing Models). What this means, of course, is that there is a basis for a genuine source of competitive advantage, such as the Caissa Capital fund enjoyed in the early 2000s with its advanced option pricing models. The plethora of volatility products that have emerged over the last decade has only added to the opportunity set.

 Why Hasn’t It Been Done Before?

This was an entirely legitimate question back in the early days of volatility arbitrage. The cost of trading an option book, to say nothing of the complexities of managing the associated risks, were significant disincentives for both managers and investors.  Bid/ask spreads were wide enough to cause significant heads winds for strategies that required aggressive price-taking.  Mangers often had to juggle two sets of risks books, one reflecting the market’s view of the portfolio Greeks, the other the model view.  The task of explaining all this to investors, many of whom had never evaluated volatility strategies previously, was a daunting one.  And then there were the capacity issues:  back in the early 2000s a $400m long/short option portfolio would typically have to run to several hundred names in order to meet liquidity and market impact risk tolerances. Much has changed over the last fifteen years, especially with the advent of the highly popular VIX futures contract and the newer ETF products such as VXX and XIV, whose trading volumes and AUM are growing rapidly.  These developments have exerted strong downward pressure on trading costs, while providing sufficient capacity for at least a dozen volatility funds managing over $1Bn in assets.

Why Hasn’t It Been Done Right Yet?

Again, this question is less apposite than it was ten years ago and since that time there have been a number of success stories in the volatility space. One of the learning points occurred in 2004-2007, when volatility hit the lows for a 20 month period, causing performance to crater in long volatility funds, as well as funds with a volatility neutral mandate. I recall meeting with Nassim Taleb to discuss his Empirica volatility fund prior to that period, at the start of the 2000s.  My advice to him was that, while he had some great ideas, they were better suited to an insurance product rather than a hedge fund.  A long volatility fund might lose money month after month for an entire year, and with it investors and AUM, before seeing the kind of payoff that made such investment torture worthwhile.  And so it proved.

Conversely, stories about managers of short volatility funds showing superb performance, only to blow up spectacularly when volatility eventually explodes, are legion in this field.  One example comes to mind of a fund in Long Beach, CA, whose prime broker I visited with sometime in 2002.  He told me the fund had been producing a rock-steady 30% annual return for several years, and the enthusiasm from investors was off the charts – the fund was managing north of $1Bn by then.  Somewhat crestfallen I asked him how they were producing such spectacular returns.  “They just sell puts in the S&P, 100 points out of the money”, he told me.  I waited, expecting him to continue with details of how the fund managers handled the enormous tail risk.  I waited in vain. They were selling naked put options.  I can only imagine how those guys did when the VIX blew up in 2003 and, if they made it through that, what on earth happened to them in 2008!

Conclusion

The moral is simple:  one cannot afford to be either all-long, or all-short volatility.  The fund must run a long/short book, buying cheap Gamma and selling expensive Theta wherever possible, and changing the net volatility exposure of the portfolio dynamically, to suit current market conditions. It can certainly be done; and with the new volatility products that have emerged in recent years, the opportunities in the volatility space have never looked more promising.

What Wealth Managers and Family Offices Need to Understand About Alternative Investing

Gold

The most recent Morningstar survey provides an interesting snapshot of the state of the alternatives market.  In 2013, for the third successive year, liquid alternatives was the fastest growing category of mutual funds, drawing in flows totaling $95.6 billion.  The fastest growing subcategories have been long-short stock funds (growing more than 80% in 2013), nontraditional bond funds (79%) and “multi-alternative” fund-of-alts-funds products (57%).

Benchmarking Alternatives
The survey also provides some interesting insights into the misconceptions about alternative investments that remain prevalent amongst advisors, despite contrary indications provided by long-standing academic research.  According to Morningstar, a significant proportion of advisors continue to use inappropriate benchmarks, such as the S&P 500 or Russell 2000, to evaluate alternatives funds (see Some advisers using ill-suited benchmarks to measure alts performance by Trevor Hunnicutt, Investment News July 2014).  As Investment News points out, the problem with applying standards developed to measure the performance of funds that are designed to beat market benchmarks is that many alternative funds are intended to achieve other investment goals, such as reducing volatility or correlation.  These funds will typically have under-performed standard equity indices during the bull market, causing investors to jettison them from their portfolios at a time when the additional protection they offer may be most needed.

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This is but one example in a broader spectrum of issues about alternative investing that are poorly understood.  Even where advisors recognize the need for a more appropriate hedge fund index to benchmark fund performance, several traps remain for the unwary.  As shown in Brooks and Kat (The Statistical Properties of Hedge Fund Index Returns and Their Implications for Investors, Journal of Financial and Quantitative Analysis, 2001), there can be considerable heterogeneity between indices that aim to benchmark the same type of strategy, since indices tend to cover different parts of the alternatives universe.  There are also significant differences between indices in terms of their survivorship bias – the tendency to overstate returns by ignoring poorly performing funds that have closed down (see Welcome to the Dark Side – Hedge Fund Attribution and Survivorship Bias, Amin and Kat, Working Paper, 2002).  Hence, even amongst more savvy advisors, the perception of performance tends to be biased by the choice of index.

Risks and Benefits of Diversifying with Alternatives
An important and surprising discovery in relation to diversification with alternatives was revealed in Amin and Kat’s Diversification and Yield Enhancement with Hedge Funds (Working Paper, 2002).  Their study showed that the median standard deviation of a portfolio of stocks, bonds and hedge funds reached its lowest point where the allocation to alternatives was 50%, far higher than the 1%-5% typically recommended by advisors.

Standard Deviation of Portfolios of Stocks, Bonds and 20 hedge Funds

Hedge Fund Pct Mix and Volatility

Source: Diversification and Yield Enhancement with Hedge Funds, Amin and Kat, Working Paper, 2002

Another potential problem is that investors will not actually invest in the fund index that is used for benchmarking, but in a basket containing a much smaller number of funds, often through a fund of funds vehicle.  The discrepancy in performance between benchmark and basket can often be substantial in the alternatives space.

Amin and Kat studied this problem in 2002 (Portfolios of Hedge Funds, Working Paper, 2002), by constructing hedge fund portfolios ranging in size from 1 to 20 funds and measuring their performance on a number of criteria that included, not just the average return and standard deviation, but also the skewness (a measure of the asymmetry of returns), kurtosis (a measure of the probability of extreme returns)and the correlation with the S&P 500 Index and the Salomon (now Citigroup) Government Bond Index.  Their startling conclusion was that, in the alternatives space, diversification is not necessarily a good thing.    As expected, as the number of funds in the basket is increased, the overall volatility drops substantially; but at the same time skewness drops and kurtosis and market correlation increase significantly.  In other words, when adding more funds, the likelihood of a large loss increases and the diversification benefit declines.   The researchers found that a good approximation to a typical hedge fund index could be constructed with a basket of just 15 well-chosen funds, in most cases.

Concerns about return distribution characteristics such as skewness and kurtosis may appear arcane, but these factors often become crucially important at just the wrong time, from the investor’s perspective.  When things go wrong in the stock market they also tend to go wrong for hedge funds, as a fall in stock prices is typically accompanied by a drop in market liquidity, a widening of spreads and, often, an increase in stock loan costs.  Equity market neutral and long/short funds that are typically long smaller cap stocks and short larger cap stocks will pay a higher price for the liquidity they need to maintain neutrality.  Likewise, a market sell-off is likely to lead to postponing of M&A transactions that will have a negative impact on the performance of risk arbitrage funds.  Nor are equity-related funds the only alternatives likely to suffer during a market sell-off.  A market fall will typically be accompanied by widening credit spreads, which in turn will damage the performance of fixed income and convertible arbitrage funds.   The key point is that, because they all share this risk, diversification among different funds will not do much to mitigate it.

Conclusions
Many advisors remain wedded to using traditional equity indices that are inappropriate benchmarks for alternative strategies.  Even where more relevant indices are selected, they may suffer from survivorship and fund-selection bias.

In order to reap the diversification benefit from alternatives, research shows that investors should concentrate a significant proportion of their wealth in the limited number of alternatives funds, a portfolio strategy that is diametrically opposed to the “common sense” approach of many advisors.

Finally, advisors often overlook the latent correlation and liquidity risks inherent in alternatives that come into play during market down-turns, at precisely the time when investors are most dependent on diversification to mitigate market risk.  Such risks can be managed, but only by paying attention to portfolio characteristics such as skewness and kurtosis, which alternative funds significantly impact.