Abstract
In this study, we address the social interaction process in which PT (Prospect Theory) preferences are influenced by other market participants, e.g., regular CRRA (Constant Relative Risk Averse) investors or other PT investors, and study then the long run wealth convergence of the two trading parties: one PT agent vs. one CRRA agent or both agents of PT types. In the model with one PT agent vs. one CRRA agent, the PT agent knows the CRRA agent’s optimal terminal wealth and takes it as his/her reference point. If the PT agent starts with an initial wealth level higher than that of the CRRA agent, he/she will always do better than the CRRA agent by imitating the CRRA agent’s policy. On the other hand, if the PT agent starts with a wealth level lower than that of the CRRA agent, he/she can still do better than the CRRA agent by adopting a “gambling policy”. When both trading parties are of PT type, we consider two types of reference points: either both PT agents take their average wealth as their reference point or they are mutually reference dependent. Under both situations, we give sufficient conditions on the long run wealth convergence.
This research work was partially supported by Hong Kong Research Grants Council under grant CUHK 419511. The second author is also grateful to the support from Patrick Huen Wing Ming Chair Professorship of Systems Engineering & Engineering Management.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Schultz, P.W., Nolan, J.M., Cialdini, R.B., Goldstein, N.J., Griskevicius, V.: The constructive, destructive, and reconstructive power of social norms. J. Public Econ. 94(7), 435–452 (2007)
Azmat, G., Iriberri, N.: The importance of relative performance feedback information: Evidence from a natural experiment using high school students. Psychol. Sci. 18(5), 429–434 (2010)
Basak, S., Makarov, D.: Strategic asset allocation in money management. J. Financ. 69(1), 179–217 (2014)
Kahneman, D., Tversky, A.: Prospect theory: An analysis of decisions under risk. Econometrica 47(2), 263–292 (1979)
Tversky, A., Kahneman, D.: Advances in prospect theory: Cumulative representation of uncertainty. J. Risk Uncertainty 5(4), 297–323 (1992)
Shi, Y., Cui, X.Y., Yao, J., Li, D.: Dynamic trading with reference point adaptation and loss aversion (2013) (submitted for publication)
Jin, H., Zhou, X.Y.: Behavioral portfolio selection in continuous time. Math. Financ. 18(3), 385–426 (2008)
Shi, Y.: Behavioral portfolio models and their implications in investors’ behaviors, PhD thesis, the Chinese University of Hong Kong, Hong Kong (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Shi, Y., Li, D., Cui, X. (2015). Behavioral Portfolio Optimization with Social Reference Point. In: Le Thi, H., Pham Dinh, T., Nguyen, N. (eds) Modelling, Computation and Optimization in Information Systems and Management Sciences. Advances in Intelligent Systems and Computing, vol 359. Springer, Cham. https://doi.org/10.1007/978-3-319-18161-5_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-18161-5_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18160-8
Online ISBN: 978-3-319-18161-5
eBook Packages: EngineeringEngineering (R0)