摘要翻译：
我们基于伦敦证券交易所交易订单流的经验规律，建立了流动性和波动性的行为模型。这可以看作是一个非常简单的基于agent的模型，其中模型的所有组件都根据实际数据进行验证。我们对订单流的实证研究揭示了交易订单的下达和取消方式中几个有趣的规律性。利用所得到的简单订单流模型模拟了连续双向拍卖条件下的价格形成，并将所得到的模拟价格序列的统计特性与实际数据进行了比较。该模型是用一只股票(AZN)构建的，并在其他24只股票上进行了测试。对于波动性低、规模小的股票（称为I组），预测是非常好的，但对于I组以外的股票，预测就不好了。对于第一组，该模型预测了波动率和买卖价差分布的正确大小和函数形式，而没有根据价格调整任何参数。这表明，至少对于第一类股票，价格的波动性和重尾性与市场微观结构效应有关，并支持了至少在短时间尺度上，绝对收益的大幅波动被指数随股票不同的幂律很好地描述的假设。
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英文标题：
《An empirical behavioral model of liquidity and volatility》
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作者：
Szabolcs Mike, J. Doyne Farmer
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最新提交年份：
2007
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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：
  We develop a behavioral model for liquidity and volatility based on empirical regularities in trading order flow in the London Stock Exchange. This can be viewed as a very simple agent based model in which all components of the model are validated against real data. Our empirical studies of order flow uncover several interesting regularities in the way trading orders are placed and cancelled. The resulting simple model of order flow is used to simulate price formation under a continuous double auction, and the statistical properties of the resulting simulated sequence of prices are compared to those of real data. The model is constructed using one stock (AZN) and tested on 24 other stocks. For low volatility, small tick size stocks (called Group I) the predictions are very good, but for stocks outside Group I they are not good. For Group I, the model predicts the correct magnitude and functional form of the distribution of the volatility and the bid-ask spread, without adjusting any parameters based on prices. This suggests that at least for Group I stocks, the volatility and heavy tails of prices are related to market microstructure effects, and supports the hypothesis that, at least on short time scales, the large fluctuations of absolute returns are well described by a power law with an exponent that varies from stock to stock.
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PDF链接：
https://arxiv.org/pdf/0709.0159