摘要翻译：
我们利用纽约证券交易所50只美国股票的TAQ数据，研究订单簿事件--限价订单、市价订单和取消--对价格的影响。我们发现，在短时间内，价格变化主要是由订单流不平衡驱动的，即在最佳出价和出价下的供需不平衡。我们的研究揭示了订单流不平衡与价格变化之间的线性关系，斜率与市场深度成反比。结果表明，这些结果对季节性影响具有鲁棒性，并且在时间尺度和股票之间具有稳定性。我们认为，这种线性价格影响模型，加上一个规模论证，暗示了经验观察到的价格变化和交易量之间的“平方根”关系。然而，价格变化与交易量之间的关系比基于订单流不平衡的关系具有噪声性和鲁棒性。
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英文标题：
《The Price Impact of Order Book Events》
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作者：
Rama Cont and Arseniy Kukanov and Sasha Stoikov
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最新提交年份：
2011
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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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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  We study the price impact of order book events - limit orders, market orders and cancelations - using the NYSE TAQ data for 50 U.S. stocks. We show that, over short time intervals, price changes are mainly driven by the order flow imbalance, defined as the imbalance between supply and demand at the best bid and ask prices. Our study reveals a linear relation between order flow imbalance and price changes, with a slope inversely proportional to the market depth. These results are shown to be robust to seasonality effects, and stable across time scales and across stocks. We argue that this linear price impact model, together with a scaling argument, implies the empirically observed "square-root" relation between price changes and trading volume. However, the relation between price changes and trade volume is found to be noisy and less robust than the one based on order flow imbalance.
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PDF链接：
https://arxiv.org/pdf/1011.6402