Dynamic Portfolio Choice and Asset Pricing with Narrow Framing and Probability Weighting

64 Pages Posted: 3 Jun 2009 Last revised: 21 Jun 2012

See all articles by Enrico G. De Giorgi

Enrico G. De Giorgi

University of St. Gallen - SEPS: Economics and Political Sciences

Shane Legg

University of Lugano; University College London - Gatsby Computational Neuroscience Unit

Date Written: January 11, 2012

Abstract

This paper shows that the framework proposed by Barberis and Huang (2009) to incorporate narrow framing and loss aversion into dynamic models of portfolio choice and asset pricing can be extended to also account for probability weighting and for a value function that is convex on losses and concave on gains. We show that the addition of probability weighting and a convex-concave value function reinforces previous applications of narrow framing and cumulative prospect theory to understanding the stock market non-participation puzzle and the equity premium puzzle. Moreover, we show that a convex-concave value function generates new wealth eff ects that are consistent with empirical observations on stock market participation.

Keywords: Narrow framing, cumulative prospect theory, probability weighting function, negative skewness, simulation methods

JEL Classification: D1, D8, G11, G12

Suggested Citation

De Giorgi, Enrico G. and Legg, Shane, Dynamic Portfolio Choice and Asset Pricing with Narrow Framing and Probability Weighting (January 11, 2012). Swiss Finance Institute Research Paper No. 09-25, Available at SSRN: https://ssrn.com/abstract=1413087 or http://dx.doi.org/10.2139/ssrn.1413087

Enrico G. De Giorgi (Contact Author)

University of St. Gallen - SEPS: Economics and Political Sciences ( email )

Department of Economics
Bodanstrasse 6
CH-9000 St. Gallen
Switzerland
+41712242430 (Phone)

Shane Legg

University of Lugano ( email )

Via Lambertenghi 10 A
Lugano, TN Ticino 6900
Switzerland

University College London - Gatsby Computational Neuroscience Unit ( email )

Alexandra House
17 Queen Square
London, WC1N 3AR
United Kingdom

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