Stochastic Bounds for Reference Sets in Portfolio Analysis

Stelios Arvanitis (), Thierry Post () and Nikolas Topaloglou ()
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Stelios Arvanitis: Department of Economics, Athens University of Economics and Business, 10434 Athens, Greece
Thierry Post: Graduate School of Business, Nazarbayev University, and National Analytical Center ‘Analytica’, 010000 Astana, Kazakhstan
Nikolas Topaloglou: Institut de Préparation à l'Administration et à la Gestion (IPAG), Business School and Department of International and European Economic Studies, Athens University of Economics and Business, 10434 Athens, Greece

Management Science, 2021, vol. 67, issue 12, 7737-7754

Abstract: 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.

Keywords: portfolio analysis; stochastic dominance; linear programming; subsampling; enhanced benchmarking (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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