Modeling a Multivariate Transaction Process

Modeling a Multivariate Transaction Process
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多元交易流程建模

DOI:
10.1093/jjfinec/nbm020
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发表时间:
2008
影响因子:
2.5
通讯作者:
--
中科院分区:
经济学3区
文献类型:
--
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本文研究了一类联合交易过程的动力学问题。交易过程有四个标志:价格变化、交易量、买卖价差和交易持续时间。基于Copula方法,提出了一种联合密度模型,避免了在分解模型中对四个变量之间的瞬时因果关系进行先验假设,将联合密度分解为条件密度和无条件密度.价格变化过程被视为一个离散的过程,并指定一个整数计数障碍模型和交易量,买卖价差,和贸易持续时间的过程建模沿着线的分数集成自回归条件模型,这是非常适合捕捉高持久性,经验观察到在这些过程中。本文以2001年5月在纽约证券交易所(NYSE)上市的三只股票为研究对象,对市场微观结构的几个假设进行了实证分析。
In this paper the dynamics of a joint transaction process are investigated. The transaction process is characterized by four marks: price changes, transaction volumes, bid–ask spreads and intertrade durations. Based on a copula approach, a model for their joint density is proposed, which avoids forcing a priori assumptions on the instantaneous causality relationships between the four variables as necessary in decomposition models, where the joint density is decomposed into its conditional and unconditional densities. The price change process is treated as a discrete process and specified with an integer count hurdle model and the transaction volumes, bid–ask spreads, and trade durations processes are modeled along the lines of fractionally integrated autoregressive conditional models, which are suited very well to capture the high persistency, empirically observed in these processes. The model is applied to three stocks traded at the New York Stock Exchange (NYSE) in May, 2001 and we investigate several market microstructure hypotheses in the empirical part of this paper.
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