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跨相关资产配置趋势跟随策略

文章 arXiv papers · 作者: Denis S. Grebenkov et al.
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总结

本研究探讨如何在收益可能相关的多种资产之间配置趋势跟随策略。在高斯市场假设和线性策略下，研究推导了投资组合均值与方差的公式，并据此构建风险调整后的配置。作者证明，跨n种资产的动态配置可以表示为对n平方种虚拟资产的静态配置，并对趋势跟随头寸进行领先滞后调整。

论文在双资产情形和行业模型中研究资产自相关及跨资产相关性。论文指出，相关性有助于估计看似存在的趋势并调整头寸，因此可能改善配置，而不只是削弱分散化收益。结论依赖简化的高斯和线性假设，摘录没有提供实证绩效结果或实施细节。其主要贡献是提供一个分析框架，用于思考相关性如何与趋势跟随信号和投资组合配置相互作用。

核心观点

  • 论文在高斯假设下推导线性趋势跟随策略的风险调整配置。
  • 通过n平方种虚拟资产和领先滞后调整，重新表述跨n种资产的动态配置问题。
  • 资产自相关和跨资产相关性都会影响趋势跟随投资组合的表现。
  • 作者认为，跨资产相关性有助于改善趋势估计和头寸调整。
  • 摘录提供了理论框架，但未报告实证绩效证据。

标签

趋势跟踪投资组合构建统计学多资产
全文
# Optimal Allocation of Trend Following Strategies


# Optimal Allocation of Trend Following Strategies









We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for $n$ assets is shown to be equivalent to the classical static allocation problem for $n^2$ virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers.

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。