现有模型难以准确预测大单交易对价格的影响，因无法捕捉订单流自相关性。
Why is the estimation of metaorder impact with public market data so challenging?
- 提出改进的瞬时影响模型，假设仅部分大单触发市场订单流
- 模型生成的价格轨迹更接近真实交易中线性上涨、反转极少的现象
- 发现价格影响永久化的临界条件，适用于量化交易策略研究
估算大额交易（元订单）的市场冲击和交易成本是金融领域的重要课题。然而，基于公开市场数据的价格与交易模型所生成的平均价格轨迹，与真实元订单执行过程中的观察结果存在显著差异：价格在执行期间呈线性上升，而非凹形变化，且结束后回撤极小。我们认为这一现象具有普遍性，源于即使复杂的统计模型也无法正确描述订单流自相关的来源。本文提出一种修正的瞬时影响模型，通过假设仅部分元订单交易会引发市场订单流，从而生成更贴近现实的价格轨迹。有趣的是，该模型揭示了价格与订单流方程核函数间的临界条件，在此条件下市场冲击将变为永久性。
原文摘要 · Abstract (English)
Estimating market impact and transaction costs of large trades (metaorders) is a very important topic in finance. However, using models of price and trade based on public market data provide average price trajectories which are qualitatively different from what is observed during real metaorder executions: the price increases linearly, rather than in a concave way, during the execution and the amount of reversion after its end is very limited. We claim that this is a generic phenomenon due to the fact that even sophisticated statistical models are unable to correctly describe the origin of the autocorrelation of the order flow. We propose a modified Transient Impact Model which provides more realistic trajectories by assuming that only a fraction of the metaorder trading triggers market order flow. Interestingly, in our model there is a critical condition on the kernels of the price and order flow equations in which market impact becomes permanent.
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