Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations

Hao Meng, Fei Ren, Gao-Feng Gu, Xiong Xiong, Yong-Jie Zhang, Wei-Xing Zhou and Wei Zhang
Additional contact information
Hao Meng: ECUST
Fei Ren: ECUST
Gao-Feng Gu: ECUST
Xiong Xiong: TJU
Yong-Jie Zhang: TJU
Wei Zhang: TJU

Papers from arXiv.org

Abstract: 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

Date: 2012-01
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (24)

Published in EPL 98 (3), 38003 (2012)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1201.2825

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