Reinforcement Learning in Repeated Portfolio Decisions
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.
|Date of creation:||16 Feb 2011|
|Date of revision:|
|Contact details of provider:|| Postal: Carl-Zeiss-Strasse 3, 07743 JENA|
Phone: +049 3641/ 9 43000
Fax: +049 3641/ 9 43000
Web page: http://www.jenecon.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
- Ed Hopkins, 2002.
"Two Competing Models of How People Learn in Games,"
Econometric Society, vol. 70(6), pages 2141-2166, November.
- Ed Hopkins, 2000. "Two Competing Models of How People Learn in Games," ESE Discussion Papers 51, Edinburgh School of Economics, University of Edinburgh.
- Ed Hopkins, 2001. "Two Competing Models of How People Learn in Games," Levine's Working Paper Archive 625018000000000226, David K. Levine.
- Ed Hopkins, 2001. "Two Competing Models of How People Learn in Games," NajEcon Working Paper Reviews 625018000000000226, www.najecon.org.
- Peter Bossaerts & Charles Plott, 2004.
"Basic Principles of Asset Pricing Theory: Evidence from Large-Scale Experimental Financial Markets,"
Review of Finance,
Springer, vol. 8(2), pages 135-169.
- Bossaerts, Peter & Plott, Charles R., 2000. "Basic Principles of Asset Pricing Theory: Evidence From Large-Scale Experimental Financial Markets," Working Papers 1070, California Institute of Technology, Division of the Humanities and Social Sciences.
- Bossaerts, Peter & Plott, Charles, 2000. "Basic Principles Of Asset Pricing Theory: Evidence From Large-Scale Experimental Financial Markets," CEPR Discussion Papers 2578, C.E.P.R. Discussion Papers.
- Markku Kaustia & Samuli Knüpfer, 2008. "Do Investors Overweight Personal Experience? Evidence from IPO Subscriptions," Journal of Finance, American Finance Association, vol. 63(6), pages 2679-2702, December.
- Bossaerts, Peter & Plott, Charles, 2002. "The CAPM in thin experimental financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 26(7-8), pages 1093-1112, July.
- Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
When requesting a correction, please mention this item's handle: RePEc:jrp:jrpwrp:2011-009. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Markus Pasche)
If references are entirely missing, you can add them using this form.