英文标题：
《Nonlinear price impact from linear models》
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作者：
Felix Patzelt, Jean-Philippe Bouchaud
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最新提交年份：
2017
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英文摘要：
The impact of trades on asset prices is a crucial aspect of market dynamics for academics, regulators and practitioners alike. Recently, universal and highly nonlinear master curves were observed for price impacts aggregated on all intra-day scales [1]. Here we investigate how well these curves, their scaling, and the underlying return dynamics are captured by linear \"propagator\" models. We find that the classification of trades as price-changing versus non-price-changing can explain the price impact nonlinearities and short-term return dynamics to a very high degree. The explanatory power provided by the change indicator in addition to the order sign history increases with increasing tick size. To obtain these results, several long-standing technical issues for model calibration and -testing are addressed. We present new spectral estimators for two- and three-point cross-correlations, removing the need for previously used approximations. We also show when calibration is unbiased and how to accurately reveal previously overlooked biases. Therefore, our results contribute significantly to understanding both recent empirical results and the properties of a popular class of impact models.
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中文摘要：
交易对资产价格的影响对于学术界、监管机构和从业人员来说都是市场动态的一个重要方面。最近，观察到在所有日内尺度上聚集的价格影响的普遍和高度非线性主曲线【1】。在这里，我们研究了线性“传播子”模型捕捉这些曲线、它们的标度和潜在收益动态的情况。我们发现，将交易分类为价格变动与非价格变动可以在很大程度上解释价格影响非线性和短期回报动态。除了订单号历史记录之外，变更指示器提供的解释力随着勾号大小的增加而增加。为了获得这些结果，解决了几个长期存在的模型校准和测试技术问题。我们为两点和三点互相关提出了新的谱估计，消除了以前使用近似的需要。我们还展示了何时校准是无偏的，以及如何准确地揭示以前忽略的偏差。因此，我们的结果有助于理解最近的实证结果和一类流行的影响模型的性质。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Trading and Market Microstructure 交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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