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Multiportfolio optimization with CVaR risk measure

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Abstract

In the financial industry, the trading of multiple portfolios is usually aggregated and optimized simultaneously. When multiple portfolios are managed together, unique issues such as market impact costs must be dealt with properly. Conditional Value-at-Risk (CVaR) is a coherent risk measure with the computationally friendly feature of convexity. In this study, we propose the new combination of CVaR with the multiportfolio optimization (MPO) problem and develop optimization models with using CVaR to measure risks in MPO problems. A five-step scheme is presented for practical operations with considering the impact costs caused by aggregating the trading of multiple portfolios. The impact of CVaR on returns and utility in MPO environment is studied, and the comparisons with existing methods and sensitivity analysis are reported.

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Acknowledgements

This research supported by the Natural Sciences and Engineering Research Council of Canada discovery grant (RGPIN-2014-03594, RGPIN-2019-07115).

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Authors and Affiliations

  1. Supply Chain and Logistics Optimization Research Center, University of Windsor, Windsor, ON, Canada

    Guoqing Zhang & Qiqi Zhang

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  1. Guoqing Zhang
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  2. Qiqi Zhang
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Correspondence to Guoqing Zhang.

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Zhang, G., Zhang, Q. Multiportfolio optimization with CVaR risk measure. J. of Data, Inf. and Manag. 1, 91–106 (2019). https://doi.org/10.1007/s42488-019-00007-w

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  • DOI: https://doi.org/10.1007/s42488-019-00007-w

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