Open AccessAsset allocation for a DC pension plan with learning about stock return predictability
Author(s) -
Pei Wang,
Ling Zhang,
Zhongfei Li
Publication year - 2022
Publication title -
journal of industrial and management optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.325
H-Index - 32
eISSN - 1553-166X
pISSN - 1547-5816
DOI - 10.3934/jimo.2021138
Subject(s) - unobservable , bond , predictability , pension , asset allocation , economics , econometrics , hedge fund , investment performance , stock (firearms) , investment strategy , predictive power , financial economics , actuarial science , finance , return on investment , microeconomics , market liquidity , portfolio , mathematics , mechanical engineering , statistics , production (economics) , engineering , philosophy , epistemology
This paper investigates an optimal investment problem for a defined contribution pension plan member who receives a stochastic salary, and considers inflation risk and stock return predictability. The member aims to maximize the expected power utility from her terminal real wealth by investing her pension account wealth in a financial market consisting of a risk-free asset, an inflation-indexed bond and a stock. The expected excess return on the stock can be predicted by both an observable predictor and an unobservable predictor, and the member has to estimate the unobservable predictor by learning the history information. By using the filtering techniques and dynamic programming approach, the closed-form optimal investment strategy and the corresponding value function are derived. Finally, with the help of numerical analysis, we explore the impact of model parameters on the optimal investment strategy, and analyze the welfare benefits from leaning and using inflation-indexed bond to hedge the stock return predictors.