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隐藏漂移状态与波动率惩罚效用下的配对交易

文章 arXiv papers · 作者: Sühan Altay et al.

总结

本文将配对交易表述为动态投资组合优化问题。两种相关证券之间的价差服从高斯均值回复过程,其漂移率则随一个不可观测的有限状态连续时间马尔可夫链变化。由于状态不可见,作者使用随机滤波将部分信息问题转化为完全信息问题。他们针对对数效用求解该问题,并纳入与已实现投资组合波动率挂钩的终端财富惩罚。

研究刻画了完全信息和部分信息条件下的最优美元中性策略及价值函数。文中还指出,最优策略满足确定性等价原则,即可以根据隐藏状态的滤波估计来刻画策略。数值示例使用两状态马尔可夫链,但本文没有提供真实市场验证或盈利证据。因此,结果属于理论研究,并取决于所假设的价差动态、滤波模型、效用选择和基于波动率的惩罚。

核心观点

  • 资产价差被建模为具有隐藏马尔可夫漂移状态的高斯均值回复过程。
  • 随机滤波将部分信息优化问题简化为完全信息形式。
  • 目标函数采用对数效用,并根据已实现波动率对终端财富施加惩罚。
  • 研究刻画了完全信息和部分信息下的最优美元中性策略。
  • 一个双状态玩具示例展示了该模型,但未报告真实市场表现证据。

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# Pairs Trading under Drift Uncertainty and Risk Penalization


# Pairs Trading under Drift Uncertainty and Risk Penalization









In this work, we study a dynamic portfolio optimization problem related to pairs trading, which is an investment strategy that matches a long position in one security with a short position in another security with similar characteristics. The relationship between pairs, called a spread, is modeled by a Gaussian mean-reverting process whose drift rate is modulated by an unobservable continuous-time, finite-state Markov chain. Using the classical stochastic filtering theory, we reduce this problem with partial information to the one with full information and solve it for the logarithmic utility function, where the terminal wealth is penalized by the riskiness of the portfolio according to the realized volatility of the wealth process. We characterize optimal dollar-neutral strategies as well as optimal value functions under full and partial information and show that the certainty equivalence principle holds for the optimal portfolio strategy. Finally, we provide a numerical analysis for a toy example with a two-state Markov chain.

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。