Portfolio Selection with Hierarchical Isomorphic Risk Aversion

Abstract

Researchers usually specify risk aversion coefficients from 1 (lowest) to M (highest) for a portfolio to indicate active or passive approaches. How effective is this practice? Recent studies suggest that the global minimum variance portfolio (GMVP) is statistically equivalent to portfolios with extensive risk aversion coefficients (the GMVP-equivalent). Expressing the risk aversion coefficient as a Taylor series of the target return and efficient set constants, we generalize the previous result to the non-GMVP-equivalents and segment mean-variance portfolios according to a hierarchy of risk aversion coefficients. In this paper, we show that hierarchical risk aversion coefficients are superior to isometric attributes.