Ambiguity aversion and optimal derivative-based pension investment with stochastic income and volatility
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Date
2018-03-01
Authors
Zeng, Yan
Li, Danping
Chen, Zheng
Yang, Zhou
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
This paper provides a derivative-based optimal investment strategy for an ambiguity-adverse pension investor who faces not only risks from time-varying income and market return volatility but also uncertain economic conditions over a long time horizon. We derive a robust dynamic derivative strategy and show that the optimal strategy under ambiguity aversion reduces the exposures to market return risk and volatility risk and that the investor holds opposite positions for the two risk exposures. In the presence of a derivative, ambiguity has distinct effects on the optimal investment strategy. More important, we demonstrate the utility improvement when considering ambiguity and exploiting derivatives and show that ambiguity aversion and derivative trading significantly improve utility when return volatility increases. This improvement becomes more significant under ambiguity aversion over a long investment horizon.
Description
The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.jedc.2018.01.023 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
Ambiguity, DC pension plan, Derivative, Robust portfolio choice, Stochastic salary, Stochastic volatility