Michael Busack

We study the performance persistence of alternative UCITS funds, which are a hybrid between mutual funds and hedge funds. Persistence is gauged by alternative measures of performance and risk. Based on contingency tables, we find that performance persists for up to 2 years following ranking. However, persistence is stronger in the short run, and ranked portfolio tests indicate that investors can benefit from persistence for only up to 1 year. The evidence for persistence in risk is ambiguous. We link fund characteristics to performance persistence and find that offshore hedge fund experience enhances persistence. Our results are robust against survivorship bias and other potential database biases.

We study the performance of alternative UCITS funds and account for potential survivorship biases in our sample in the best possible manner. Alternative UCITS funds offer similar raw returns but a lower volatility compared to offshore hedge funds. Single-index models show that alternative UCITS funds provide only marginal exposure to variations in hedge fund returns. Multifactor models indicate that the most important risk factors for both alternative UCITS funds and their matched hedge funds strategies are related to stock market risks, but alternative UCITS funds exhibit a lower exposure to these factors than hedge funds. Moreover, we find factor loadings on different risk factors, suggesting that alternative UCITS and hedge funds pursue different strategies. Finally, we assess the degree of the value added for an investor in terms of enhanced diversification benefits by implementing a spanning test and find that both groups are different asset classes with time-varying diversification properties.

The authors study the out-of-sample predictability of the returns of pan-European harmonized mutual funds that follow hedge fund–like investment strategies (“alternative UCITS”) and allow retail investors to gain access to nontraditional investment strategies. Given these funds’ higher liquidity compared with hedge funds, investors could exploit relevant information more easily and use it for their asset allocation and risk management decisions. Using a large set of fundamental and technical variables, the authors estimate single predictor models, combination forecasts, and multivariate regression models. Forming hypothetical funds-of-funds portfolios based on predicted returns generates economic gains for investors, especially during crisis times. Combination approaches and multivariate models reduce estimation uncertainty and lead to economic gains across different market environments.