Stochastic Spanning

Stelios Arvanitis, Mark Hallam, Thierry Post, Nikolas Topaloglou

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

This study develops and implements methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for all risk averse investors. We develop a test procedure for “stochastic spanning” for two nested portfolio sets based on subsampling and linear programming. The test is statistically consistent and asymptotically exact for a class of weakly dependent processes. A Monte Carlo simulation experiment shows good statistical size and power properties in finite samples of realistic dimensions. In an application to standard datasets of historical stock market returns, we accept market portfolio efficiency but reject two-fund separation, which suggests an important role for higher-order moment risk in portfolio theory and asset pricing. Supplementary materials for this article are available online.

Original languageEnglish
Pages (from-to)573-585
Number of pages13
JournalJournal of Business and Economic Statistics
Volume37
Issue number4
DOIs
Publication statusPublished - Oct 2 2019

Keywords

  • Linear programming
  • Portfolio choice
  • Spanning
  • Stochastic dominance
  • Subsampling

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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