TY - JOUR
T1 - Multiperiod Asset Allocation Considering Dynamic Loss Aversion Behavior of Investors
AU - Wang, Jia
AU - Zhou, Mengchu
AU - Guo, Xiwang
AU - Qi, Liang
N1 - Funding Information:
Manuscript received June 11, 2018; accepted July 10, 2018. Date of publication December 25, 2018; date of current version February 12, 2019. This work was supported in part by NSFC under Grant 71601040, in part by the Fundamental Research Funds for the Central Universities under Grant N172304020, in part by the China Postdoctoral Science Foundation under Grant 2018M631797, and in part by the Liaoning Province Dr. Research Foundation of China under Grant 20175032. (Corresponding author: MengChu Zhou.) J. Wang is with the School of Economics, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China (e-mail: wangjia@neuq.edu.cn).
Funding Information:
This work was supported in part by NSFC under Grant 71601040, in part by the Fundamental Research Funds for the Central Universities under Grant N172304020, in part by the China Postdoctoral Science Foundation under Grant 2018M631797, and in part by the Liaoning Province Dr. Research Foundation of China under Grant 20175032.
Publisher Copyright:
© 2014 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - In order to study the effect of loss aversion behavior on multiperiod investment decisions, we first introduce some psychological characteristics of dynamic loss aversion and then construct a multiperiod portfolio model by considering a conditional value-at-risk (CVaR) constraint. We then design a variable neighborhood search-based hybrid genetic algorithm to solve the model. We finally study the optimal asset allocation and investment performance of the proposed multiperiod model. Some important metrics, such as the initial loss aversion coefficient and reference point, are used to test the robustness of the model. The result shows that investors with loss aversion tend to centralize most of their wealth and have a better performance than rational investors. The effects of CVaR on investment performance are given. When a market is falling, investors with a higher degree of risk aversion can avoid a large loss and can obtain higher gains.
AB - In order to study the effect of loss aversion behavior on multiperiod investment decisions, we first introduce some psychological characteristics of dynamic loss aversion and then construct a multiperiod portfolio model by considering a conditional value-at-risk (CVaR) constraint. We then design a variable neighborhood search-based hybrid genetic algorithm to solve the model. We finally study the optimal asset allocation and investment performance of the proposed multiperiod model. Some important metrics, such as the initial loss aversion coefficient and reference point, are used to test the robustness of the model. The result shows that investors with loss aversion tend to centralize most of their wealth and have a better performance than rational investors. The effects of CVaR on investment performance are given. When a market is falling, investors with a higher degree of risk aversion can avoid a large loss and can obtain higher gains.
KW - Conditional value-at-risk (CVaR)
KW - dynamic loss aversion
KW - genetic algorithm (GA)
KW - multiperiod portfolio
KW - prospect theory (PT)
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U2 - 10.1109/TCSS.2018.2883764
DO - 10.1109/TCSS.2018.2883764
M3 - Article
AN - SCOPUS:85059289610
SN - 2329-924X
VL - 6
SP - 73
EP - 81
JO - IEEE Transactions on Computational Social Systems
JF - IEEE Transactions on Computational Social Systems
IS - 1
M1 - 8588367
ER -