Bayesian portfolio selection using a multifactor model

Tomohiro Ando

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This article develops a new portfolio selection method using Bayesian theory. The proposed method accounts for the uncertainties in estimation parameters and the model specification itself, both of which are ignored by the standard mean-variance method. The critical issue in constructing an appropriate predictive distribution for asset returns is evaluating the goodness of individual factors and models. This problem is investigated from a statistical point of view; we propose using the Bayesian predictive information criterion. Two Bayesian methods and the standard mean-variance method are compared through Monte Carlo simulations and in a real financial data set. The Bayesian methods perform very well compared to the standard mean-variance method.

Original languageEnglish
Pages (from-to)550-566
Number of pages17
JournalInternational Journal of Forecasting
Volume25
Issue number3
DOIs
Publication statusPublished - 2009 Jul 1

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Keywords

  • Bayesian methods
  • Decision making
  • Finance
  • Model selection

ASJC Scopus subject areas

  • Business and International Management

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