Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio
The importance of proper tail risk management is a crucial component of the investment process and conditional Value at Risk (CVaR) is often used as a tail risk measure. CVaR is the asymmetric risk measure that controls and manages the downside risk of a portfolio while symmetric risk measures such...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/13/6/922 |
| _version_ | 1797533239103979520 |
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| author | Kei Nakagawa Katsuya Ito |
| author_facet | Kei Nakagawa Katsuya Ito |
| author_sort | Kei Nakagawa |
| collection | DOAJ |
| description | The importance of proper tail risk management is a crucial component of the investment process and conditional Value at Risk (CVaR) is often used as a tail risk measure. CVaR is the asymmetric risk measure that controls and manages the downside risk of a portfolio while symmetric risk measures such as variance consider both upside and downside risk. In fact, minimum CVaR portfolio is a promising alternative to traditional mean-variance optimization. However, there are three major challenges in the minimum CVaR portfolio. Firstly, when using CVaR as a risk measure, we need to determine the distribution of asset returns, but it is difficult to actually grasp the distribution; therefore, we need to invest in a situation where the distribution is uncertain. Secondly, the minimum CVaR portfolio is formulated with a single <i>β</i> and may output significantly different portfolios depending on the <i>β</i>. Finally, most portfolio allocation strategies do not account for transaction costs incurred by each rebalancing of the portfolio. In order to improve these challenges, we propose a Regularized Multiple <i>β</i> Worst-case CVaR (RM-WCVaR) portfolio. The characteristics of this portfolio are as follows: it makes CVaR robust with worst-case CVaR which is still an asymmetric risk measure, it is stable among multiple <i>β</i>, and against changes in weights over time. We perform experiments on well-known benchmarks to evaluate the proposed portfolio.RM-WCVaR demonstrates superior performance of having both higher risk-adjusted returns and lower maximum drawdown. |
| first_indexed | 2024-03-10T11:11:43Z |
| format | Article |
| id | doaj.art-dc515382622f45cbbed77a255e2fbabc |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T11:11:43Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-dc515382622f45cbbed77a255e2fbabc2023-11-21T20:45:31ZengMDPI AGSymmetry2073-89942021-05-0113692210.3390/sym13060922Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR PortfolioKei Nakagawa0Katsuya Ito1Innovation Lab, NOMURA Asset Management Co., Ltd., 2-2-1 Toyosu, Koto-ku, Tokyo 135-0061, JapanMITSUI & Co., Ltd., 2-1 Otemachi 1-chome, Chiyoda-ku, Tokyo 100-8631, JapanThe importance of proper tail risk management is a crucial component of the investment process and conditional Value at Risk (CVaR) is often used as a tail risk measure. CVaR is the asymmetric risk measure that controls and manages the downside risk of a portfolio while symmetric risk measures such as variance consider both upside and downside risk. In fact, minimum CVaR portfolio is a promising alternative to traditional mean-variance optimization. However, there are three major challenges in the minimum CVaR portfolio. Firstly, when using CVaR as a risk measure, we need to determine the distribution of asset returns, but it is difficult to actually grasp the distribution; therefore, we need to invest in a situation where the distribution is uncertain. Secondly, the minimum CVaR portfolio is formulated with a single <i>β</i> and may output significantly different portfolios depending on the <i>β</i>. Finally, most portfolio allocation strategies do not account for transaction costs incurred by each rebalancing of the portfolio. In order to improve these challenges, we propose a Regularized Multiple <i>β</i> Worst-case CVaR (RM-WCVaR) portfolio. The characteristics of this portfolio are as follows: it makes CVaR robust with worst-case CVaR which is still an asymmetric risk measure, it is stable among multiple <i>β</i>, and against changes in weights over time. We perform experiments on well-known benchmarks to evaluate the proposed portfolio.RM-WCVaR demonstrates superior performance of having both higher risk-adjusted returns and lower maximum drawdown.https://www.mdpi.com/2073-8994/13/6/922RM-WCVaRtail riskportfolio optimization |
| spellingShingle | Kei Nakagawa Katsuya Ito Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio Symmetry RM-WCVaR tail risk portfolio optimization |
| title | Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio |
| title_full | Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio |
| title_fullStr | Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio |
| title_full_unstemmed | Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio |
| title_short | Taming Tail Risk: Regularized Multiple <i>β</i> Worst-Case CVaR Portfolio |
| title_sort | taming tail risk regularized multiple i β i worst case cvar portfolio |
| topic | RM-WCVaR tail risk portfolio optimization |
| url | https://www.mdpi.com/2073-8994/13/6/922 |
| work_keys_str_mv | AT keinakagawa tamingtailriskregularizedmultipleibiworstcasecvarportfolio AT katsuyaito tamingtailriskregularizedmultipleibiworstcasecvarportfolio |