Modeling stock price dynamics by continuum percolation system and relevant complex systems analysis
Modeling stock price dynamics by continuum percolation system and relevant complex systems analysis
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DOI：
10.1016/j.physa.2012.05.024
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发表时间：
2012-10
影响因子：
3.3
通讯作者：
Di Xiao;Jun Wang
中科院分区：
文献类型：
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作者：
Di Xiao;Jun Wang
在这项工作中，连续介质渗流系统被用来模拟一个随机的股票价格过程。最近的实证研究显示了股票价格变动的各种统计特征，旨在理解价格波动的金融模型需要定义一种价格形成机制，以试图再现和解释这一组经验事实。连续体渗流模型通常被称为随机覆盖过程或布尔模型，交易者之间的局部相互作用或影响是由连续体渗流构建的，而连续统渗流簇被用来定义对市场有相同看法的交易者簇。运用幂函数尾部分析、混沌行为分析和Zipf分析等分析方法，考察和分析了该价格模型的归一化收益率的统计行为。此外，我们还考虑了1997年1月至2011年7月上证综指的单日收益率，并对实际数据和模拟数据的收益率行为进行了比较。
The continuum percolation system is developed to model a random stock price process in this work. Recent empirical research has demonstrated various statistical features of stock price changes, the financial model aiming at understanding price fluctuations needs to define a mechanism for the formation of the price, in an attempt to reproduce and explain this set of empirical facts. The continuum percolation model is usually referred to as a random coverage process or a Boolean model, the local interaction or influence among traders is constructed by the continuum percolation, and a cluster of continuum percolation is applied to define the cluster of traders sharing the same opinion about the market. We investigate and analyze the statistical behaviors of normalized returns of the price model by some analysis methods, including power-law tail distribution analysis, chaotic behavior analysis and Zipf analysis. Moreover, we consider the daily returns of Shanghai Stock Exchange Composite Index from January 1997 to July 2011, and the comparisons of return behaviors between the actual data and the simulation data are exhibited.