摘要翻译：
了解极端事件复发间隔的统计特性对于复杂系统的风险评估和管理至关重要。许多系统的递推区间的概率分布及其相关性已被广泛研究。然而，复杂系统的微观规律对其递推区间宏观性质的影响研究较少。在这封信中，我们采用了一个订单驱动的股票市场模型来解决这个问题的股票回报。我们发现模拟收益的标度递推区间的分布具有幂律标度，且具有伸展指数截止，具有多重分形性质，这与实证结果是一致的。我们进一步研究了顺序流的方向（或符号）和相对价格上的长记忆对这些性质的特征量的影响。结果表明，序列方向上的长记忆性(Hurst指数$H_s$)对区间分布和多重分形性质的影响可以忽略不计。与此相反，区间分布的幂律指数随相对价格的Hurst指数$H_x$线性增加，多重分形特性的奇异性宽度在$H_x<0.7$附近波动，然后随$H_x$增加。$H_s$和$H_x$对复发间隔的长记忆无明显影响。我们的结果表明，收益重复区间的非平凡性质主要是由交易者在最佳出价和出价附近持续下新单的行为引起的。
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英文标题：
《Effects of long memory in the order submission process on the properties
  of recurrence intervals of large price fluctuations》
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作者：
Hao Meng (ECUST), Fei Ren (ECUST), Gao-Feng Gu (ECUST), Xiong Xiong
  (TJU), Yong-Jie Zhang (TJU), Wei-Xing Zhou (ECUST), Wei Zhang (TJU)
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最新提交年份：
2012
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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：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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英文摘要：
  Understanding the statistical properties of recurrence intervals of extreme events is crucial to risk assessment and management of complex systems. The probability distributions and correlations of recurrence intervals for many systems have been extensively investigated. However, the impacts of microscopic rules of a complex system on the macroscopic properties of its recurrence intervals are less studied. In this Letter, we adopt an order-driven stock market model to address this issue for stock returns. We find that the distributions of the scaled recurrence intervals of simulated returns have a power law scaling with stretched exponential cutoff and the intervals possess multifractal nature, which are consistent with empirical results. We further investigate the effects of long memory in the directions (or signs) and relative prices of the order flow on the characteristic quantities of these properties. It is found that the long memory in the order directions (Hurst index $H_s$) has a negligible effect on the interval distributions and the multifractal nature. In contrast, the power-law exponent of the interval distribution increases linearly with respect to the Hurst index $H_x$ of the relative prices, and the singularity width of the multifractal nature fluctuates around a constant value when $H_x<0.7$ and then increases with $H_x$. No evident effects of $H_s$ and $H_x$ are found on the long memory of the recurrence intervals. Our results indicate that the nontrivial properties of the recurrence intervals of returns are mainly caused by traders' behaviors of persistently placing new orders around the best bid and ask prices.
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PDF链接：
https://arxiv.org/pdf/1201.2825