Hebei University of Technology Researchers Advance Knowledge in Risk Management (Optimal Investment Strategy for DC Pension Schemes under Partial Information): Insurance – Risk Management

2022 NOV 28 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Current study results on risk management have been published. According to news reporting from Tianjin, People’s Republic of China, by NewsRx journalists, research stated, “We consider a defined-contribution (DC)-pension-fund-management problem under partial information.”

Financial supporters for this research include Natural Science Foundation of Tianjin; Natural Science Foundation of Hebei Province; Research Foundation For Returned Scholars of Hebei Province; Humanities And Social Science Research Project of Hebei Province.

Our news editors obtained a quote from the research from Hebei University of Technology: “The fund manager is allowed to invest the wealth from the fund account into a financial market consisting of a risk-free account, a stock and a rolling bond. The aim of the fund manager is to maximize the expected utility of the terminal wealth. In contrast to the traditional literature, we assume that the fund manager can only observe the stock-price process and the interest-rate process, but the expected return rate of the stock is unobservable, following a mean-reverting stochastic process. We apply a martingale approach and Clark’s formula to solve this problem and the closed-form representations for the optimal terminal wealth and trading strategy are derived.”

According to the news editors, the research concluded: “We further present the results for the constant relative risk aversion (CRRA) function as a special case.”

For more information on this research see: Optimal Investment Strategy for DC Pension Schemes under Partial Information. Risks, 2022,10(211):211. (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks10110211.

Our news journalists report that additional information may be obtained by contacting Manli Ban, School of Sciences, Hebei University of Technology, Tianjin 300401, People’s Republic of China. Additional authors for this research include Hua He, Xiaoqing Liang.

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