CHAPTER 3 Performance of Managed Futures: Persistence and the Source of Returns. Managed futures investments are shown to exhibit a small amount of performance persistence. Thus, there do appear to be some differences in the skills of commodity trading advisors. | 3 Performance of Managed Futures Persistence and the Source of Returns B. Wade Brorsen and John P. Townsend Managed futures investments are shown to exhibit a small amount of performance persistence. Thus there do appear to be some differences in the skills of commodity trading advisors. The funds with the highest returns used long-term trading systems charged higher fees and had fewer dollars under management. Returns were negatively correlated with the most recent past returns but the sum of all correlations was positive. Consistent with work in behavioral finance when deciding whether to invest or withdraw funds investors put the most weight on the most recent returns. The results suggest that the source of futures fund returns is exploiting inefficiencies. INTRODUCTION There is little evidence from past research that the top performing managed futures funds can be predicted Schwager 1996 . Past literature has primarily used variations of the methods of Elton Gruber and Rentzler EGR . Yet EGR s methods have little power to reject the null hypothesis of no predictability Grossman 1987 . Using methods with sufficient power to reject a false null hypothesis this research seeks to determine whether performance persists for managed futures advisors. The data used are from public funds private funds and commodity trading advisors CTAs . Regression analysis is used to determine whether all funds have the same mean returns. This is done after adjusting for changes in overall returns and differences in leverage. Monte Carlo methods are used to determine the power of EGR s 31 32 PERFORMANCE TABLE Descriptive Statistics for the Public Private and Combined CTA Data Sets and Continuous Time Returns Statistic Public Funds Private Funds Combined CTAs Observations 32 420 23 723 57 018 Funds 577 435 1 071 Percentage returns Mean SD Minimum Maximum Skewness Kurtosis
