Portfolio choice based on third-degree stochastic dominance

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

We develop an optimization method for constructing investment portfolios that dominate a given benchmark portfolio in terms of third-degree stochastic dominance. Our approach relies on the properties of the semivariance function, a refinement of an existing “superconvex” dominance condition, and quadratic constrained programming. We apply our method to historical stock market data using an industry momentum strategy. Our enhanced portfolio generates important performance improvements compared with alternatives based on mean-variance dominance and second-degree stochastic dominance. Relative to the Center for Research in Security Prices all-share index, our portfolio increases average out-of-sample return by almost seven percentage points per annum without incurring more downside risk, using quarterly rebalancing and without short selling.

Original languageEnglish
Pages (from-to)3381-3392
Number of pages12
JournalManagement Science
Volume63
Issue number10
DOIs
Publication statusPublished - Oct 1 2017

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Portfolio choice
Stochastic dominance
Benchmark portfolio
Security price
Short selling
Rebalancing
Stock market
Semivariance
Performance improvement
Investment portfolio
Industry
Momentum strategies
Downside risk
Market data
Mean-variance
Programming

Keywords

  • Enhanced indexing
  • Industry momentum
  • Portfolio choice
  • Quadratic programming
  • Stochastic dominance

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

Cite this

Portfolio choice based on third-degree stochastic dominance. / Post, Gerrit Tjeerd (Thierry); Kopa, Miloš.

In: Management Science, Vol. 63, No. 10, 01.10.2017, p. 3381-3392.

Research output: Contribution to journalArticle

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