Reference Dependence: Endogenous Anchors and Life-Cycle Investing

45 Pages Posted: 23 Jul 2020 Last revised: 12 Mar 2021

See all articles by Paolo Guasoni

Paolo Guasoni

Boston University - Department of Mathematics and Statistics; Dublin City University - School of Mathematical Sciences; University of Bologna - Department of Statistics

Andrea Meireles-Rodrigues

University of York - Department of Mathematics

Date Written: July 22, 2020

Abstract

In a complete market, we find optimal portfolios for an investor whose satisfaction stems from both a payoff's intrinsic utility and its comparison with a reference, as specified by Köszegi and Rabin. In the regular regime, arising when reference-dependence is low, the marginal utility of the optimal payoff is proportional to a twist of the pricing kernel. High reference-dependence leads to the anchors regime, whereby investors reduce disappointment by concentrating significant probability in one or few fixed outcomes, and multiple personal equilibria arise. If stocks follow geometric Brownian motion, the model implies that younger investors have larger stocks positions than older investors, suggesting that reference-dependence helps explain this typical recommendation of financial planners.

Keywords: complete market; endogenous anchors; life-cycle investment; loss aversion; personal equilibria; reference dependence

JEL Classification: G11, G12

Suggested Citation

Guasoni, Paolo and Guasoni, Paolo and Meireles-Rodrigues, Andrea, Reference Dependence: Endogenous Anchors and Life-Cycle Investing (July 22, 2020). Michael J. Brennan Irish Finance Working Paper Series Research Paper No. 21-2, Available at SSRN: https://ssrn.com/abstract=3658342 or http://dx.doi.org/10.2139/ssrn.3658342

Paolo Guasoni (Contact Author)

Boston University - Department of Mathematics and Statistics ( email )

Boston, MA 02215
United States

Dublin City University - School of Mathematical Sciences ( email )

Dublin
Ireland

HOME PAGE: http://www.guasoni.com

University of Bologna - Department of Statistics ( email )

Bologna, 40126
Italy

Andrea Meireles-Rodrigues

University of York - Department of Mathematics ( email )

Heslington, York YO10 5DD
United Kingdom

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