流动性与波动性的经验行为模型
An empirical behavioral model of liquidity and volatility
摘要：
本文以伦敦证券交易所的交易订单流为例，建立了一个流动性和波动性的行为模型。这可以被看作是一个非常简单的基于代理的模型，其中模型的所有组件都是针对真实数据进行验证的。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的几个有趣的问题。由此产生的简单模型的订单流被用来模拟下的连续双向拍卖的价格形成，并将由此产生的模拟序列的价格的统计特性与真实数据进行比较。该模型是使用一个股票（AZN）和24个其他股票进行测试。对于低波动性、小最小价格变动单位的股票（称为第一类），预测是非常好的，但对于第一类以外的股票，预测就不好了。对于第一组，该模型预测的波动率和买卖价差的分布的正确幅度和函数形式，而不调整任何参数的价格。这表明，至少对于第一类股票，价格的波动性和重尾与市场微观结构效应有关，并支持以下假设：至少在短时间尺度上，绝对收益的大幅波动可以很好地用指数随股票而变化的幂律来描述。
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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