Modelling financial transaction price movements: a dynamic integer count data model
Modelling financial transaction price movements: a dynamic integer count data model
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DOI：
10.1007/s00181-005-0001-1
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发表时间：
2006-01-01
影响因子：
3.2
通讯作者：
Pohlmeier, W
中科院分区：
文献类型：
--
作者：
Liesenfeld, R;Nolte, I;Pohlmeier, W
在本文中，我们建立了一个整数计数的动态模型，以捕捉交易层面上金融价格的基本属性。我们的模型依赖于一个用于价格变化方向的自回归多项式分量和一个用于价格变化大小的动态计数数据分量。由于该模型能够捕捉广泛的离散价格变动，因此特别适合交易强度适中或较低的金融市场。我们将该模型应用于一个交易月内在纽约证券交易所交易的两只股票的交易数据，从而展示了该模型的有效性。我们发现，该模型很好地检验了市场微观结构理论关于价格变动与交易过程的其他标志之间的关系的一些理论含义。基于离散随机变量情况下改进的密度预测方法，我们的模型能够在交易水平上解释大部分观察到的价格变化的分布。
In this paper we develop a dynamic model for integer counts to capture fundamental properties of financial prices at the transaction level. Our model relies on an autoregressive multinomial component for the direction of the price change and a dynamic count data component for the size of the price changes. Since the model is capable of capturing a wide range of discrete price movements it is particularly suited for financial markets where the trading intensity is moderate or low. We present the model at work by applying it to transaction data of two shares traded at the NYSE traded over a period of one trading month. We show that the model is well suited to test some theoretical implications of the market microstructure theory on the relationship between price movements and other marks of the trading process. Based on density forecast methods modified for the case of discrete random variables we show that our model is capable to explain large parts of the observed distribution of price changes at the transaction level.