In modern portfolio theory, financial portfolios are characterised by a desired property, the ‘reward’, and something undesirable, the ‘risk’. While these properties are commonly identified with mean and variance of returns, respectively, we test alternative specifications like partial and conditional moments, quantiles, and drawdowns. More specifically, we analyse the empirical performance of portfolios selected by optimising risk–reward ratios constructed from these alternative functions. We find that these portfolios in many cases outperform our benchmark (minimum-variance), in particular when long-run returns are concerned. However, we also find that all the strategies tested seem quite sensitive to relatively small changes in the data. The main theme throughout our results is that minimising risk, as opposed to maximising reward, often leads to good out-of-sample performance. In contrast, adding a reward-function to the selection criterion improves a given strategy often only marginally.
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