Liesiö, Juuso and Xu, Peng and Kuosmanen, Timo (2020) Portfolio diversification based on stochastic dominance under incomplete probability information. European Journal of Operational Research, 286 (2). pp. 755-768. DOI https://doi.org/10.1016/j.ejor.2020.03.042
Liesiö, Juuso and Xu, Peng and Kuosmanen, Timo (2020) Portfolio diversification based on stochastic dominance under incomplete probability information. European Journal of Operational Research, 286 (2). pp. 755-768. DOI https://doi.org/10.1016/j.ejor.2020.03.042
Liesiö, Juuso and Xu, Peng and Kuosmanen, Timo (2020) Portfolio diversification based on stochastic dominance under incomplete probability information. European Journal of Operational Research, 286 (2). pp. 755-768. DOI https://doi.org/10.1016/j.ejor.2020.03.042
Abstract
Identifying efficient portfolio diversification strategies subject to stochastic dominance (SD) criteria usually assumes that the state-space of future asset returns can be captured by a fixed sample of equally probable historical returns. This paper relaxes this assumption by developing SD criteria under incomplete information on state probabilities. Specifically, we identify portfolios that dominate a given benchmark for any state probabilities in a given set. The proposed approach is applied to analyze if industrial diversification can be utilized to outperform the market portfolio. The results from this application demonstrate that the use of set-valued state probabilities can help to improve out-of-sample performance of SD-based portfolio optimization.
Item Type: | Article |
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Uncontrolled Keywords: | Decision analysis; Finance; Stochastic dominance; Portfolio diversification; Incomplete probability information |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 22 Aug 2022 09:05 |
Last Modified: | 30 Oct 2024 20:32 |
URI: | http://repository.essex.ac.uk/id/eprint/33297 |
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