Reinforcement Learning in Repeated Portfolio Decisions

Linan Diao () and Jörg Rieskamp ()
Additional contact information
Linan Diao: Max Planck Institute of Economics, Jena, Germany
Jörg Rieskamp: University of Basel, Switzerland

No 2011-009, Jena Economics Research Papers from Friedrich-Schiller-University Jena

Abstract: How do people make investment decisions when they receive outcome feedback? We examined how well the standard mean-variance model and two reinforcement models predict people's portfolio decisions. The basic reinforcement model predicts a learning process that relies solely on the portfolio's overall return, whereas the proposed extended reinforcement model also takes the risk and covariance of the investments into account. The experimental results illustrate that people reacted sensitively to different correlation structures of the investment alternatives, which was best predicted by the extended reinforcement model. The results illustrate that simple reinforcement learning is sufficient to detect correlation between investments.

Keywords: repeated portfolio decisions; reinforcement learning model; correlation (search for similar items in EconPapers)
JEL-codes: C91 D83 G11 (search for similar items in EconPapers)
Date: 2011-02-16
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://oweb.b67.uni-jena.de/Papers/jerp2011/wp_2011_009.pdf (application/pdf)

Related works:
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:jrp:jrpwrp:2011-009

Access Statistics for this paper

More papers in Jena Economics Research Papers from Friedrich-Schiller-University Jena
Bibliographic data for series maintained by Markus Pasche ().