A statistical analysis of investor preferences for portfolio selection

Doron Nisani, Amit Shelef

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Is the market portfolio consistent with the investors’ preferences for risk and return in the capital markets? The answer to this question is not so simple: on the one hand, the market portfolio (which is derived from a minimization of a coherent risk measurement) is an efficient portfolio in terms of risk and return and therefore should be consistent with the investor’s preference. On the other hand, since none of the current risk indices are considered to be coherent risk measurements, the market portfolio might not be consistent with the investors’ preference. This research attempts to fill this gap by invoking the Lorenz curve ranking method combined with compatible statistical tests, in order to rank the S&P 500 Index and its components in 2014–2017. We conclude that the S&P 500 Index is not considered to be the market portfolio from the investors’ point of view, but rather seen as another asset. In addition, we conclude that the investors exhibit a decreasing risk aversion behavior in ranking financial assets, which suggests that they are willing to take risks for higher rewards. This methodology presents a unique way to empirically examine the theoretical preference relation of von Neumann and Morgenstern.

Original languageEnglish
Pages (from-to)1883-1915
Number of pages33
JournalEmpirical Economics
Volume61
Issue number4
DOIs
StatePublished - 1 Oct 2021
Externally publishedYes

Keywords

  • Expected utility model
  • Investment management
  • Lorenz curves
  • Marginal conditions for stochastic dominance
  • Stochastic dominance rules

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics (miscellaneous)
  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Fingerprint

Dive into the research topics of 'A statistical analysis of investor preferences for portfolio selection'. Together they form a unique fingerprint.

Cite this