英文标题：
《Burst and inter-burst duration statistics as empirical test of
  long-range memory in the financial markets》
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作者：
V. Gontis and A. Kononovicius
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最新提交年份：
2017
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英文摘要：
  We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to $3/2$, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.
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中文摘要：
我们解决金融市场中的长期记忆问题。有两种在概念上不同的方法来再现自相关函数的幂律衰减：使用分数布朗运动和非线性随机微分方程。在本文中，我们通过分析外汇的经验收益率和交易活动时间序列来解决这个问题。从经验时间序列中，我们得到了突发和突发间持续时间的概率密度函数。我们的分析表明，得到的概率密度函数的幂律指数接近$3/2$，这是一维随机过程的一个特征。这与早期提出的基于基于基于主体的羊群模型导出的非线性随机微分方程的绝对收益模型非常一致。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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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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