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Risk-Reward Ratio Optimisation (Revisited)

Author

Listed:
  • Manfred Gilli

    (University of Geneva and Swiss Finance Institute)

  • Enrico Schumann

    (Independent researcher)

Abstract

We study the empirical performance of alternative risk and reward specifications in portfolio selection. In particular, we look at models that take into account asymmetry of returns, and treat losses and gains differently. In tests on a dataset of German equities we find that portfolios constructed with the help of such models generally outperform the market index and in many cases also the risk-based benchmark (minimum variance). In part, higher returns can be explained by exposure to factors such as momentum and value. Nevertheless, a substantial part of the performance cannot be explained by standard asset-pricing models.

Suggested Citation

  • Manfred Gilli & Enrico Schumann, 2017. "Risk-Reward Ratio Optimisation (Revisited)," Swiss Finance Institute Research Paper Series 17-55, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1755
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    Keywords

    Numerical optimisation; Heuristics; Risk-based investing; Downside risk; Factor Investing; UCITS;
    All these keywords.

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