This paper integrates transfer entropy (TE) within the portfolio optimization framework to account for dependencies among assets. This approach helps mitigate systemic risk and create portfolios that are resilient to asymmetric information flows. Key contributions of this study include (1) demonstrating the impact of TE constraints on portfolio diversification and stability, (2) linking TE thresholds to the Herfindahl–Hirschman Index to quantify this effect, and (3) establishing the coherence of a TE-integrated multivariate entropic risk measure using extreme value theory. Empirical analyses of a diversified portfolio, including traditional and contemporary asset classes, reveal that TE constraints effectively modulate portfolio stability and offer a robust alternative to conventional risk measures such as Value at Risk and Conditional Value at Risk.

中文翻译：

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使用转移熵约束的投资组合优化


本文将转移熵 （TE） 集成到投资组合优化框架中，以考虑资产之间的依赖关系。这种方法有助于降低系统性风险，并创建能够抵御不对称信息流的投资组合。本研究的主要贡献包括 （1） 证明 TE 约束对投资组合多元化和稳定性的影响，（2） 将 TE 阈值与 Herfindahl-Hirschman 指数联系起来以量化这种影响，以及 （3） 使用极值理论建立 TE 综合多变量熵风险测量的连贯性。对多元化投资组合（包括传统和现代资产类别）的实证分析表明，TE 约束有效地调节了投资组合的稳定性，并为风险价值和条件风险价值等传统风险衡量标准提供了稳健的替代方案。