数学季刊 ›› 2023, Vol. 38 ›› Issue (1): 85-96.doi: 10.13371/j.cnki.chin.q.j.m.2023.01.006

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收益率椭球分布不确定下的均值-CVaR优化研究

  

  1. School of Financial Mathematics and Statistics, City University of Hong Kong,
    Hong Kong 999077, China
  • 收稿日期:2022-10-27 出版日期:2023-03-30 发布日期:2023-03-20
  • 通讯作者: QING Nai-qiao (2000-), female, native of Guangdong, Guangzhou, postgraduate of City U- niversity of Hong Kong, engages in optimization and statistics. E-mail:naiqiao qing@163.com
  • 作者简介:QING Nai-qiao (2000-), female, native of Guangdong, Guangzhou, postgraduate of City U- niversity of Hong Kong, engages in optimization and statistics.
  • 基金资助:
    Supported by the Ministry of Education Planning Fund (Grant No. 15YJA790043).

Worst-Case Optimization on Mean-CVaR Ratio with Returns Distribution Ellipsoidal Uncertainty

  1. School of Financial Mathematics and Statistics, City University of Hong Kong,
    Hong Kong 999077, China
  • Received:2022-10-27 Online:2023-03-30 Published:2023-03-20
  • Contact: QING Nai-qiao (2000-), female, native of Guangdong, Guangzhou, postgraduate of City U- niversity of Hong Kong, engages in optimization and statistics. E-mail:naiqiao qing@163.com
  • About author:QING Nai-qiao (2000-), female, native of Guangdong, Guangzhou, postgraduate of City U- niversity of Hong Kong, engages in optimization and statistics.
  • Supported by:
    Supported by the Ministry of Education Planning Fund (Grant No. 15YJA790043).

摘要: The article explores a mean-CVaR ratio model with returns distribution
uncertainty. To describe the uncertainty of returns distribution, a mixture ellipsoidal
distribution absorbing some typical distributions such as the mixture distribution and
and ellipsoidal distribution is introduced. Then, by using robust technique with some
assumptions, the original robust mean-CVaR ratio model can be formulated as a second-
order cone optimization model where the underlying random returns have a mixture
ellipsoidal distribution. As an illustration, the corresponding robust optimization models
are applied to allocations of assets in securities market. Numerical simulations are
presented to illustrate the relation between robustness and optimality and to compare
mixture ellipsoidal distribution to some typical distributions as well.

关键词: Worst-case mean-CVaR ratio, Mixture ellipsoidal uncertainty, Second-order
cone optimization

Abstract: The article explores a mean-CVaR ratio model with returns distribution
uncertainty. To describe the uncertainty of returns distribution, a mixture ellipsoidal
distribution absorbing some typical distributions such as the mixture distribution and
and ellipsoidal distribution is introduced. Then, by using robust technique with some
assumptions, the original robust mean-CVaR ratio model can be formulated as a second-
order cone optimization model where the underlying random returns have a mixture
ellipsoidal distribution. As an illustration, the corresponding robust optimization models
are applied to allocations of assets in securities market. Numerical simulations are
presented to illustrate the relation between robustness and optimality and to compare
mixture ellipsoidal distribution to some typical distributions as well.

Key words: Worst-case mean-CVaR ratio, Mixture ellipsoidal uncertainty, Second-order
cone optimization

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