Friday, September 11, 2009

Lo, Hedge Funds

Andrew W. Lo, in Hedge Funds: An Analytic Perspective (Princeton University Press, 2008) makes a convincing case that we need new quantitative models for assessing the risks and rewards of hedge funds. Take the case of the imaginary hedge fund Capital Decimation Partners. By traditional metrics its performance over an eight-year period was stellar, and if you didn’t know how it achieved its success you might rush to invest in it. If, however, you found out that its strategy was simply to short out-of-the-money S&P 500 put options you might have second thoughts; do you really want to assume such tail risk (and do you want to pay someone a premium to execute such a mindless strategy)?

Whereas long-only portfolio managers are judged by such widely accepted performance metrics as alpha, beta, volatility, tracking error, the Sharpe ratio, and the information ratio, hedge funds are often held to a single standard—absolute return. In this monograph Lo proposes a set of new measures for hedge funds that are dynamic rather than static in nature. He tries to quantify, for instance, a hedge fund manager’s asset-timing ability with multipoint statistics (the active/passive decomposition and active ratio) that “capture the very essence of active management: time-series predictability.” (p. 197)

Just as there have been no adequate measures of the performance of hedge funds so there is no single summary measure of the risks of these funds. Here Lo is not talking so much about the risk profiles of hedge funds as they affect individual investors (though he does briefly deal with the topic later) as he is addressing the question of systemic risk. In both a theoretical analysis and, later, an assessment of what happened in August 2007 Lo focuses on the themes of illiquidity exposure and time-varying hedge fund correlations.

Lo also returns to the adaptive markets hypothesis he first proposed in 2004 as an alternative to the efficient markets hypothesis and applies it to the hedge fund world. He draws four Darwinian implications:

1. Arbitrage opportunities exist from time to time. “From an evolutionary perspective, the existence of active liquid financial markets implies that profit opportunities must be present. As they are exploited, they disappear. But new opportunities are also continually being created. . . . Rather than the inexorable trend toward high efficiency predicted by the EMH, the AMH implies considerably more complex market dynamics, with cycles as well as trends, panics, bubbles, crashes, and other phenomena routinely witnessed in natural market ecologies.” (p. 247)

2. “[I]nvestment strategies also wax and wane, performing well in certain environments and performing poorly in other environments.” (p. 248)

3. “[I]nnovation is the key to survival.” (p. 249)

4. “Survival is the only objective that matters. While profit maximization, utility maximization, and general equilibrium are certainly relevant aspects of market ecology, the organizing principle in determining the evolution of markets and financial technology is simply survival.” (p. 249)

Lo’s monograph is first and foremost a scholarly work, replete with formulas and tables. He continues to expand the horizons of quantitative analysis of the financial markets. But his practical experience (he’s the founder of AlphaSimplex) also informs this book, and the combination is powerful.

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