不完全信息下的竞争性交易策略
文章 arXiv papers · 作者: Neil A. Chriss
总结
本文研究竞争企业在不了解对手策略重要细节(例如目标持仓规模或市场冲击模型)时应如何建立交易头寸。文章将企业的不确定性和不同信念纳入贝叶斯博弈框架,拓展了竞争性交易均衡分析。分析考察对市场状况和竞争对手行为的判断如何影响各企业的最优交易选择。
作者推导了适用于这一不确定情形的策略,并将其与完全信息情形进行比较,指出不确定性会改变最终策略。他们还提出一种建模方法,用于在策略性企业对非策略交易者的特征看法不一时描述这类交易者。本文是理论分析,没有实证检验或数值绩效证据。其适用范围受线性市场冲击假设以及缺少动态策略调整的限制;作者将这两点列为未来研究方向。因此,研究阐明了模型中的策略互动,但并未证明这些策略在实盘市场中的表现。
核心观点
- 本文将竞争企业建立头寸建模为不确定条件下的贝叶斯博弈。
- 企业对市场状况和对手交易行为可能持有不同看法。
- 分析推导了最优交易策略,并将其与完全信息策略进行比较。
- 一种建模方法可在特征存在分歧时描述非策略交易者。
- 线性市场冲击假设和缺少动态调整限制了模型的适用范围。
标签
全文
# Position building in competition is a game with incomplete information # Position building in competition is a game with incomplete information This paper examines strategic trading under incomplete information, where firms lack full knowledge of key aspects of their competitors' trading strategies such as target sizes and market impact models. We extend previous work on competitive trading equilibria by incorporating uncertainty through the framework of Bayesian games. This allows us to analyze scenarios where firms have diverse beliefs about market conditions and each other's strategies. We derive optimal trading strategies in this setting and demonstrate how uncertainty significantly impacts these strategies compared to the complete information case. Furthermore, we introduce a novel approach to model the presence of non-strategic traders, even when strategic firms disagree on their characteristics. Our analysis reveals the complex interplay of beliefs and strategic adjustments required in such an environment. Finally, we discuss limitations of the current model, including the reliance on linear market impact and the lack of dynamic strategy adjustments, outlining directions for future research.
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。