Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155833
Title: Robust state-dependent mean–variance portfolio selection : a closed-loop approach
Authors: Han, Bingyan
Pun, Chi Seng
Wong, Hoi Ying
Keywords: Science::Mathematics
Issue Date: 2021
Source: Han, B., Pun, C. S. & Wong, H. Y. (2021). Robust state-dependent mean–variance portfolio selection : a closed-loop approach. Finance and Stochastics, 25(3), 529-561. https://dx.doi.org/10.1007/s00780-021-00457-4
Project: MOE2017-T2-1-044
Journal: Finance and Stochastics
Abstract: This paper studies a class of robust mean–variance portfolio selection problems with state-dependent risk aversion. Model uncertainty, in the sense of considering alternative dominated models, is introduced to the problem to reflect the investor’s uncertainty-averse preference. To characterise the robust portfolios, we consider closed-loop equilibrium control and spike variation approaches. Moreover, we show that a closed-loop equilibrium strategy exists and is unique under some technical conditions. This partially addresses open problems left in Björk et al. (Finance Stoch. 21:331–360, 2017) and Pun (Automatica 94:249–257, 2018). By using a necessary and sufficient condition for the equilibrium, we manage to derive the analytical form of the equilibrium strategy via the unique solution to a nonlinear ordinary differential equation system. To validate the proposed closed-loop control framework, we show that when there is no uncertainty, our equilibrium strategy is reduced to the strategy in Björk et al. (Math. Finance 24:1–24, 2014), which cannot be deduced under the open-loop control framework.
URI: https://hdl.handle.net/10356/155833
ISSN: 0949-2984
DOI: 10.1007/s00780-021-00457-4
Rights: © 2021 The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. This is a post-peer-review, pre-copyedit version of an article published in Finance and Stochastics. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00780-021-00457-4.
Fulltext Permission: embargo_20220807
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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