具有长尾和多重分形的事件间时间模型 人际交往在金融交易中的应用

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摘要翻译：
社会、技术和经济的时间序列通常被认为是随机的，尽管具有一定的层次结构。众所周知，在这些背景下观察到的交互统计量不同于泊松剖面，它是长尾分布的，静息期和活跃期交织在一起。因此，了解产生一致统计数据的机制已成为一个中心问题。我们提出的方法取自连续时间随机游动的形式，代表了一种分析的替代最近提出的非平凡优先级模型。我们的分析还更进一步，通过观察人类决策交互时间的多重分形结构。我们在这里分析了几个金融市场之间的交易时间间隔。我们观察到经验数据描述了一种微妙的多重分形行为。我们的模型通过将暂停时间密度以超统计的形式来解释这种结构，其中积分核量化了已执行任务的异构性质。一个拉伸指数核提供了一个在一定范围内有效的多重分形轮廓。建议的启发式分析剖面能够覆盖更广泛的区域。
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英文标题：
《A model for interevent times with long tails and multifractality in
  human communications: An application to financial trading》
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作者：
J. Perello, J. Masoliver, A. Kasprzak, R. Kutner
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最新提交年份：
2008
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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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：
  Social, technological and economic time series are divided by events which are usually assumed to be random albeit with some hierarchical structure. It is well known that the interevent statistics observed in these contexts differs from the Poissonian profile by being long-tailed distributed with resting and active periods interwoven. Understanding mechanisms generating consistent statistics have therefore become a central issue. The approach we present is taken from the Continuous Time Random Walk formalism and represents an analytical alternative to models of non-trivial priority that have been recently proposed. Our analysis also goes one step further by looking at the multifractal structure of the interevent times of human decisions. We here analyze the inter-transaction time intervals of several financial markets. We observe that empirical data describes a subtle multifractal behavior. Our model explains this structure by taking the pausing-time density in the form of a superstatistics where the integral kernel quantifies the heterogeneous nature of the executed tasks. An stretched exponential kernel provides a multifractal profile valid for a certain limited range. A suggested heuristic analytical profile is capable of covering a broader region.
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PDF链接：
https://arxiv.org/pdf/0805.1353

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关键词：金融交易 人际交往 Multifractal Quantitative Hierarchical 性质 拉伸 异构 任务 Our