The ability of hedge funds to generate profits regardless of market conditions is a regularly cited favourable characteristic of this class of asset managers. Indeed, the term “hedge fund” was coined with reference to the goal of the first such funds, which was to invest in undervalued securities using the proceeds from short sales of related securities, thereby creating a “market neutral” strategy.
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Hedge funds are often classified according to their self-described investment strategies or styles and the “equity market neutral” strategy is one of the largest such categories representing up to 20% of funds under the management of hedge funds. But despite their size, what exactly is meant by the moniker “market neutral” can be hard to pin down. Most definitions of an equity market neutral strategy include phrases such as “neutralize market risks by combining long and short positions in related securities”, with limited detail on how neutrality should be measured and what risks should be considered “market” risks.
A very simple measure of neutrality is “dollar neutrality”, whereby the dollar value of long investments in a given market or sector is offset with short positions of equal dollar value in those same markets. This measure has the great benefit of being directly verifiable: The initial value of the investments is observable, at least to the hedge fund manager and perhaps to his investors. However, the extent to which the assets in the short portfolio truly offset the market exposure from the assets in the long portfolio is not observable by the hedge fund manager or anyone else because this depends on the unobservable risk characteristics of the long and short portfolios.
The market neutrality of a hedge fund can also be studied empirically by looking at its past performance and the past performance of a market index such as the Standard & Poor’s 500 or the Bombay Stock Exchange’s Sensex. The most common way to measure market neutrality is based on linear correlation: A fund may be said to be “market neutral” if it generates returns that have zero (or low) correlation with the returns on the market index. A hedge fund that has low correlation with the market is a better addition to your portfolio than one with high correlation: The low correlation provides diversification benefits that a highly correlated fund does not.
But do hedge funds really provide diversification benefits to investors?
The events of the past year have revealed some funds to be not as neutral as they may have liked to be with many funds losing money at the same time as equity market indices have fallen. Even before the recent financial turmoil, sharp movements in certain markets occasionally led to spectacular “blow-ups” of hedge funds.
Andrew Lo, a finance professor at Massachusetts Institute of Technology, or MIT, cautions investors and regulators about these “tail risks” via a simple and illuminating example: He considers a hypothetical fund which pursues an investment strategy that generates small, but consistent, returns in most periods regardless of swings in the market index. But when the market index drops particularly far, the fund makes a very large loss. Thus in relatively tranquil market conditions this hypothetical fund appears both profitable and market neutral but in times of falling equity prices, its correlation with the market becomes apparent. This strategy can be implemented in practice by shorting out-of-the-money put options on the market index which is very much like selling insurance on the market portfolio. Similar to other insurance providers, when things are going smoothly no claims are made and the insurer gets to keep the insurance premium. But when things start going bad, the insurer needs to start paying and the profits of the insurer become tightly linked with the object that was insured.
The above example of tail risk is a specific example of a “non-linear risk”. The dynamic nature of hedge fund managers’ strategies and the sophisticated combinations of positions held by hedge funds mean that many of the risk exposures of hedge funds are non-linear. The difficulty this causes for investors and regulators is that some of these risks are hard to detect using standard methods such as linear correlation. Linear correlation may be well suited to study the exposure of companies to risks to their profitability (changes in the prices of inputs to production or changes in the market share of competing firms) and to study the exposure of mutual funds to risk factors (equity market risk or interest rate risk) but it is less well suited to risk analysis for hedge funds.
In a paper titled Are ‘Market Neutral’ Hedge Funds Really Market Neutral?, I explored the concept of neutrality more generally than that implied by the use of linear correlation. To extend our ability to detect important forms of non-neutrality, I proposed a variety of alternative neutrality concepts: “mean neutrality” which is the standard correlation-based definition of neutrality; “variance neutrality” and “tail neutrality” relate to the neutrality of the risk of the hedge fund returns to market returns. I applied these tests to a collection of around 1,500 individual hedge funds over a 10-year period and I found that approximately a quarter of funds in the “market neutral” style are significantly non-neutral. While this is a surprisingly high proportion, I also found that this was the most neutral of the various styles I considered: Around 85% of funds in the “equity non-hedge” style, for example, are non-neutral.
Warren Buffett is quoted as saying, “It’s only when the tide goes out that you learn who’s been swimming naked.” But through careful analysis of hedge fund performance relative to market indices and recognizing the non-linear nature of their risk exposures, we do not have to wait for the tide to go all the way out to uncover information about the diversification benefits offered by hedge funds.
Andrew J. Patton is a reader in economics at the Department of Economics and deputy director of the Oxford-Man Institute of Quantitative Finance at the University of Oxford
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