Stochastic Bounds for Reference Sets in Portfolio Analysis

Stelios Arvanitis, Thierry Post, Nikolas Topaloglou

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


A stochastic bound is a portfolio that stochastically dominates all alternatives in a reference portfolio set instead of a single alternative portfolio. An approximate bound is a portfolio that comes as close as possible to this ideal. To identify and analyze exact or approximate bounds, feasible approaches to numerical optimization and statistical inference are developed based on linear programming and subsampling. The use of reference sets and stochastic bounds is shown to improve investment performance in representative applications to enhanced benchmarking using equity industry rotation and equity index options combinations.

Original languageEnglish
Pages (from-to)7737-7754
Number of pages18
JournalManagement Science
Issue number12
Publication statusPublished - Dec 2021


  • Enhanced benchmarking
  • Linear programming
  • Portfolio analysis
  • Stochastic dominance
  • Subsampling

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research


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