THE PROPER USE OF RISK MEASURES IN PORTFOLIO THEORY

TLDR

The paper distinguishes two admissible classes of risk measures in portfolio theory: safety‑risk measures and dispersion measures. The study aims to analyze risk measure properties and empirically compare three portfolio choice models based on mean, risk measure, and skewness to guide optimal portfolio selection. The authors examine how risk depends on distributional parameters, compare statistical parametric models with linear fund‑separation models, and empirically evaluate three portfolio choice frameworks. The results show how three risk measures influence investor preferences, including when derivative assets are considered.

Abstract

This paper discusses and analyzes risk measure properties in order to understand how a risk measure has to be used to optimize the investor's portfolio choices. In particular, we distinguish between two admissible classes of risk measures proposed in the portfolio literature: safety-risk measures and dispersion measures. We study and describe how the risk could depend on other distributional parameters. Then, we examine and discuss the differences between statistical parametric models and linear fund separation ones. Finally, we propose an empirical comparison among three different portfolio choice models which depend on the mean, on a risk measure, and on a skewness parameter. Thus, we assess and value the impact on the investor's preferences of three different risk measures even considering some derivative assets among the possible choices.