Multiple tests for the performance of different investment strategies

Arbeitspapier

In the context of modern portfolio theory, we compare the out-of-sample performance of 8 investment strategies which are based on statistical methods with the out-of-sample performance of a family of trivial strategies. A wide range of approaches is considered in this work, including the traditional sample-based approach, several minimum-variance techniques, a shrinkage, and a minimax approach. In contrast to similar studies in the literature, we also consider shortselling constraints and a risk-free asset. We provide a way to extend the concept of minimum-variance strategies in the context of short-selling constraints. A main drawback of most empirical studies on that topic is the use of simple-testing procedures which do not account for the effects of multiple testing. For that reason we conduct several hypothesis tests which are proposed in the multiple-testing literature. We test whether it is possible to beat a trivial strategy by at least one of the non-trivial strategies, whether the trivial strategy is better than every non-trivial strategy, and which of the non-trivial strategies are significantly outperformed by naive diversification. In our empirical study we use monthly US stock returns from the CRSP database, covering the last 4 decades.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Discussion Papers in Statistics and Econometrics ; No. 5/10

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Portfolio Choice; Investment Decisions
• Thema: Asset allocation ; Certainty equivalent ; Investment strategy ; Markowitz ; Multiple tests ; Naive diversification ; Out-of-sample performance ; Portfolio optimization ; Sharpe ratio

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Frahm, Gabriel ; Wickern, Tobias ; Wiechers, Christof
• Ereignis: Veröffentlichung
• (wer): University of Cologne, Seminar of Economic and Social Statistics
• (wo): Cologne
• (wann): 2010

Weitere Informationen

• Handle: http://hdl.handle.net/10419/45355
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ