Eling focuses on relative performance persistence, that is, the persistence of the performance ranking in a sample of funds. In an extensive literature review, the author reports the methodologies and the results of twenty-five studies, the first published in 1998, of relative persistence. These studies differ by database provider, investigation period, time horizon (the persistence of monthly or yearly returns, for example), performance measure, and persistence measure. Among the methods the papers use to measure persistence are the Cross Product Ratio test, the Chi-square test, the rank information coefficient, the Spearman rank correlation test, the regression-based parametric method, and the Kolmogorov-Smirnov goodness-of-fit test. All these measures relate to a two-period framework, except the Kolmogorov-Smirnov, which is a multi-period test. Three of the twenty-five studies do not use a statistical methodology, but a descriptive comparison of rankings, weakening the significance of their conclusions.

Eling proposes an empirical analysis of performance persistence in which the six persistence measures are applied on successive horizons of one, two, three, six, twelve, and twenty-four months. Previous studies, taken one by one, have examined performance persistence by using only some of the six persistence measures and different time horizons. Eling’s paper, then, is interesting because in the same study it proposes a comparison of the results arrayed by the six persistence methods, and the use of horizons ranging from one to twenty-four months makes it possible to analyse the impact of the horizon on persistence.

A sample of 2,936 single hedge funds and 1,378 funds of hedge funds, with CISDM data from January 1996 to December 2005, is studied. A Jarque-Bera test, with a 5% significance level, is done. 55% of the single hedge funds and 46% of the funds of hedge funds post returns that are not normally distributed. The persistence of six performance measures is examined: raw returns, Sharpe ratio, two versions of alpha, and the two associated appraisal ratios. With raw returns, the percentage of persistent funds is compared for the six persistence measures and for the six time horizons. The regression-based parametric method is the method most sensitive to the time horizon. For single funds, the proportion of persistent funds falls from 30.7% at a one-month horizon to 21.3%, 10.5%, 9.1%, 5.8%, and 5.7% at two-, three-, six-, twelve-, and twenty-four-month horizons. The regression-based method and the Kolmogorov-Smirnov test are the most discriminant of the six persistence measures, whatever the time horizon. They display the lowest portion of persistent funds. For example, for single funds and at the six-month horizon, the regression-based method and the Kolmogorov-Smirnov test exhibit a percentage of persistent funds of 9.1% and 8.6%, while other methods display percentages that range from 31.6% to 45.3%. For single funds, the Kolmogorov-Smirnov test is more discriminant than the regression-based method at the one-, two-, and three-month horizons, while it is less discriminant at the twelve- and twenty-four-month horizons. For funds of hedge funds, the Kolmogorov-Smirnov test is more discriminant than the regression-based method at the one- and twenty-four-month horizons. These results confirm that the Kolmogorov-Smirnov test, which is a multi-period test, removes from persistent funds the funds that persist “by chance”, only from one period to the next.

All the persistence measures taken together, the performance persistence of the strategies is compared. When raw returns are used as the measure of performance, the two strategies with the highest portion of persistent funds are Convertible Arbitrage and Emerging Markets, with 53.2% and 45.1% at a one-month time horizon. As a rule, persistence declines when the time horizon increases to twelve and twenty-four months, except for Sector, Merger Arbitrage, and Emerging Markets. Over fifty months, Sector is more likely than any other strategy to display persistence at six, twelve, and twenty-four months. Equity Long Only and Short Bias have the lowest portion of persistent funds.

The impact of the performance measure used to test performance persistence is examined by comparing the portion of persistent funds for each of the six aforementioned performance measures. The author states that “the level of hedge fund performance persistence is not related to the choice of performance measure.”

Eling explores four factors that could potentially generate artificial performance persistence: the use of option-like strategies, return smoothing, survivorship bias, and backfilling bias. The author explains that “returns from writing an out-of-the-money (OTM) put option will be positive until the occurrence of a tail event brings losses when the option pays out.” He tests the persistence of the performance of 250 funds that write OTM put options. Whatever the time horizons and the persistence test, a very low portion of funds exhibit persistence. The Kolmogorov-Smirnov test displays a nil level of persistence, whatever the time horizon. It indicates that the use of option-like strategies doesn’t generate performance persistence. Concerning the impact of return smoothing on persistence, Eling measures the serial correlation of returns and attempts to determine, strategy by strategy, whether high serial correlation is associated with high persistence and whether low serial correlation is associated with low persistence. He states that “smoothing of returns might explain the high levels of short-term persistence found with some strategies”, as in the case of Convertible Arbitrage. He concludes that “survivorship bias as well as backfilling bias can partly explain the persistence.”