An Examination of Resampled Portfolio Efficiency

We examined the out-of-sample performance of using resampled portfolio efficiency, an approach proposed in 1998, in international asset allocation strategies for the period January 1983 to May 2000. For most models we used to estimate expected returns, using strategies based on resampled portfolio efficiency provided some benefits, in terms of improved Sharpe ratios and abnormal returns, over using traditional mean–variance strategies. We found little evidence, however, that active mean–variance strategies or resampled efficiency strategies would have generated significantly positive abnormal returns for the time period we considered. Mean–variance portfolio theory is one of the major developments in finance, but it has limitations when implemented. The principal limitation is that the expected return vector and covariance matrix of asset returns are unknown. Researchers have argued that traditional mean–variance portfolios based on the use of sample data are unstable because the method maximizes estimation error. The assets with higher expected returns, negative correlations, and smaller variances will tend to receive the greater weight, and these assets may have the greatest estimation error. As a result, mean–variance optimization often leads to portfolios that are not meaningful to institutional investors.The concept of “resampled portfolio efficiency” was developed to reduce the impact of estimation risk on the standard mean–variance optimization. It follows the process of simulating statistically equivalent efficient frontiers for a given set of expected returns and covariance matrix inputs. The resampled efficient frontier was originally defined as the set of portfolios that are the average weights of the “rank-associated” portfolios of the various simulated efficient frontiers. Using the resampled efficient frontier tends to moderate the extreme weights that can arise from a single mean–variance optimization. Simulation evidence has suggested that using resampled efficient portfolios leads to higher Sharpe ratios than those produced by traditional mean–variance-efficient portfolios.We examined the benefits of using resampled portfolio efficiency as contrasted to mean–variance efficiency in international asset allocation strategies. We used various performance measures to evaluate the out-of-sample performance of the two strategies between January 1983 and May 2000 for a given estimator of expected returns and covariance matrix. We also explored the robustness of the results by using various models of expected returns, including the historical mean, the James–Stein estimator of expected returns, a one-factor capital asset pricing model, and a model that uses instrumental variables to predict expected returns.The three main findings of the study are as follows: First, in confirmation of previous simulation results, some benefit can be gained in terms of improved Sharpe performance and better abnormal returns from using resampled efficiency strategies rather than traditional mean–variance strategies. Second, this benefit holds across most models used to estimate expected returns and the estimation window used to estimate expected returns. Third, neither active mean–variance nor resampled efficiency strategies outperformed the passive benchmark for the time period considered.