摘要翻译：
众所周知，交易对股票价格的影响（市场影响）是订单规模的凹函数，但几乎没有定量理论来解释为什么会这样。我为隐藏订单（反映买卖真实意图的订单）的市场影响发展了一个定量理论，它与经验测量的结果相匹配，并再现了股票收益（收益是股票价格的百分比变化）的一些非平凡的和普遍的性质。该理论基于一个简单的前提，即股票市场可以以机械的方式建模--作为一种将订单流转化为不相关价格流的设备。鉴于订单流是高度自相关的，这个前提要求市场影响（1）依赖于过去的订单流，(2)对于买卖是不对称的。我通过假设当前流动性对关于所有当前活跃的隐藏订单的信息做出响应（流动性是对给定规模交易的价格响应的度量）来推导出（1）中依赖性的具体形式。这产生了一个方程，表明市场影响应该与总订单规模成对数关系。利用伦敦证券交易所的数据对市场影响进行了实证检验，结果与理论相吻合。同样利用经验数据，定性地说明了（2）的非对称性。把所有的结果放在一起，我形成了一个市场影响模型，它再现了股票收益的三个普遍性质--收益不相关，收益呈幂律尾部分布，以及收益的大小高度自相关（也称为聚集波动性）。
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英文标题：
《A Theory for Market Impact: How Order Flow Affects Stock Price》
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作者：
Austin Gerig
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最新提交年份：
2008
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分类信息：

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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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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英文摘要：
  It is known that the impact of transactions on stock price (market impact) is a concave function of the size of the order, but there exists little quantitative theory that suggests why this is so. I develop a quantitative theory for the market impact of hidden orders (orders that reflect the true intention of buying and selling) that matches the empirically measured result and that reproduces some of the non-trivial and universal properties of stock returns (returns are percent changes in stock price). The theory is based on a simple premise, that the stock market can be modeled in a mechanical way - as a device that translates order flow into an uncorrelated price stream. Given that order flow is highly autocorrelated, this premise requires that market impact (1) depends on past order flow and (2) is asymmetric for buying and selling. I derive the specific form for the dependence in (1) by assuming that current liquidity responds to information about all currently active hidden orders (liquidity is a measure of the price response to a transaction of a given size). This produces an equation that suggests market impact should scale logarithmically with total order size. Using data from the London Stock Exchange I empirically measure market impact and show that the result matches the theory. Also using empirical data, I qualitatively specify the asymmetry of (2). Putting all results together, I form a model for market impact that reproduces three universal properties of stock returns - that returns are uncorrelated, that returns are distributed with a power law tail, and that the magnitude of returns is highly autocorrelated (also known as clustered volatility).
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PDF链接：
https://arxiv.org/pdf/0804.3818