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多因子随机波动率下的稳健投资组合优化

文章 arXiv papers · 作者: Ben-Zhang Yang et al.

总结

本文为面对多因子随机波动率模型不确定性的投资者推导最优稳健投资组合策略。研究考察有衍生品和无衍生品的投资组合,并在最坏情形下制定策略,将模型模糊性纳入配置决策。研究还将稳健策略与忽略不确定性的替代策略进行比较,并评估由此产生的福利效应。

进一步分析考察衍生品交易如何改变投资组合选择,并将框架扩展至资产价格跳跃和相关波动率因子。数值实验展示了投资组合行为和效用损失。摘要未报告具体参数设定、数据或量化结果,因此仅描述了这一框架,不足以评判其经验表现或实际应用。

核心观点

  • 本文在多因子随机波动率模型下推导稳健投资组合选择。
  • 研究比较考虑模型模糊性的决策与忽略不确定性的策略。
  • 分析涵盖有衍生品交易和无衍生品交易的情形。
  • 扩展分析考察价格跳跃和波动率因子之间的相关性。
  • 数值实验展示投资组合行为和效用损失。

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# Robust portfolio optimization with multi-factor stochastic volatility


# Robust portfolio optimization with multi-factor stochastic volatility









This paper studies a robust portfolio optimization problem under the multi-factor volatility model introduced by Christoffersen et al. (2009). The optimal strategy is derived analytically under the worst-case scenario with or without derivative trading. To illustrate the effects of ambiguity, we compare our optimal robust strategy with some strategies that ignore the information of uncertainty, and provide the corresponding welfare analysis. The effects of derivative trading to the optimal portfolio selection are also discussed by considering alternative strategies. Our study is further extended to the cases with jump risks in asset price and correlated volatility factors, respectively. Numerical experiments are provided to demonstrate the behavior of the optimal portfolio and utility loss.

在遵守原作品许可的前提下,附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写,并非原文副本。