一篇新论文介绍了一种通过分析交易和价格历史来审计算法交易策略的方法。该方法可以识别策略是净消耗者还是流动性提供者，这与 Kyle (1985) 的信息交易者/做市商二分法类似。该方法还可作为非流动性的代理指标，尤其是在 COVID-19 大流行和 2022 年加息冲击等市场压力事件期间，并可以量化相关策略造成的福利损失。 AI
影响 为分析金融市场动态提供了一种新的量化方法，可能影响算法交易和风险管理。
排序理由 该集群包含一篇发表在 arXiv 上的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.29018v1 Announce Type: cross Abstract: We show that net demand for liquidity by algo strategies is identifiable from its trade and price history alone, with no knowledge of its signal or optimization problem. An exact multi-period regret decomposition implies that the …
We show that net demand for liquidity by algo strategies is identifiable from its trade and price history alone, with no knowledge of its signal or optimization problem. An exact multi-period regret decomposition implies that the sign of this statistic classifies a linear strateg…