
Princeton University Press; revised edition 2010.
Lo, an MIT finance professor who has also run a quantitative fund, collected his research on hedge funds into a coherent treatment of how the industry's returns should be measured and what risks they carry.
His most consequential finding concerns illiquidity and smoothed returns. Reported hedge fund returns frequently exhibit positive serial correlation, meaning this month's return predicts next month's, which should not occur in an efficiently traded portfolio. Lo shows that the cause is valuation: funds holding illiquid positions mark them infrequently or using stale or modelled prices, which smooths the reported series. Smoothing reduces measured volatility without reducing actual risk, which inflates Sharpe ratios and understates correlation with markets. He develops an econometric method for estimating the degree of smoothing from the serial correlation and for recovering the underlying volatility, and shows that adjusted Sharpe ratios for illiquid strategies are substantially lower than reported.
His second contribution concerns the shape of hedge fund returns. Many strategies have payoffs resembling written options: small steady gains most of the time with occasional large losses. Lo shows that conventional risk measures based on volatility cannot capture this, and that a strategy can produce an excellent record for years while carrying a large embedded tail exposure.
He also covers database biases, since funds self-report and failed funds disappear, which overstates measured industry returns; capacity constraints, where a strategy's returns decline as assets grow; the systemic risk from correlated positions and shared prime broker financing, which he raised before 2008; and the measurement of liquidity risk.
The book is technical and assumes econometrics. The serial correlation finding has become standard in institutional due diligence and is the most practically useful result in the hedge fund literature.
Allocators and risk managers evaluating hedge funds who need the econometric methods for detecting smoothed valuation and option-like payoffs.
Charles E. and Susan T. Harris Professor, MIT Sloan School of Management; Director, MIT Laboratory for Financial Engineering; founder of AlphaSimplex Group
The Econometrics of Financial Markets and the variance-ratio work with MacKinlay are primary sources the field builds on, and the Adaptive Markets Hypothesis is a named framework in its own right.
Chosen by shared topics, the entries that hold them, and the people who recommended both.


