Spanning analysis of stock market anomalies under prospect stochastic dominance

Stelios Arvanitis, Olivier Scaillet and Nikolas Topaloglou

No unige:134101, Working Papers from University of Geneva, Geneva School of Economics and Management

Abstract: We develop and implement methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors. We formulate a new testing procedure for prospect spanning for two nested portfolio sets based on subsampling and Linear Programming. In an application, we use the prospect spanning framework to evaluate whether well-known anomalies are spanned by standard factors. We find that of the strategies considered, many expand the opportunity set of the prospect type investors, thus have real economic value for them. In-sample and out-of-sample results prove remarkably consistent in identifying genuine anomalies for prospect investors.

Keywords: Nonparametric test; Prospect stochastic dominance efficiency; Prospect spanning; Market anomaly; Linear Programming (search for similar items in EconPapers)
JEL-codes: C12 C14 C44 C58 D81 G11 G40 (search for similar items in EconPapers)
Pages: 31 p.
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://luniarchidoc5.unige.ch/archive-ouverte/arc ... :134101/ATTACHMENT01

Related works:
Journal Article: Spanning Analysis of Stock Market Anomalies Under Prospect Stochastic Dominance (2024)
Working Paper: Spanning analysis of stock market anomalies under Prospect Stochastic Dominance (2020)
Working Paper: Spanning analysis of stock market anomalies under Prospect Stochastic Dominance (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gnv:wpgsem:unige:134101

Access Statistics for this paper

More papers in Working Papers from University of Geneva, Geneva School of Economics and Management Contact information at EDIRC.
Bibliographic data for series maintained by Jean-Blaise Claivaz ().