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作 者:任飞[1] 顾高峰[1] 蒋志强[1] 周炜星[1]
出 处:《上海理工大学学报》2011年第5期433-443,456,共12页Journal of University of Shanghai For Science and Technology
摘 要:依据复杂性科学的思路,研究了金融市场大波动极端事件的重现时间间隔,考察了中国股市高频数据的重现时间间隔分布和时间关联特性,介绍了几种分布检验和关联测度方法,从不同角度进行精确分析.其次,系统介绍了重现时间间隔分析方法在金融复杂系统研究中的应用,对波动率、已实现波动率、收益率和交易量的重现时间间隔进行了实证分析,并在此基础上进行初步市场风险估计.最后,介绍了基于委托驱动的微观模型,通过模拟交易人的委托下单过程模拟市场的价格波动演化,研究大波动极端事件重现时间间隔的动力学机理,为中国股市大波动极端事件的风险估计和规避提供理论依据.This paper uses the methods of complex science, and studies the statistical properties of probability distribution and memory effect of the recurrence intervals, defined as the intervals between extreme events in financial markets. Relatively accurate analysis is performed by using various goodness-of-fit tests and memory effect detecting methods. The application of the recurrence interval analysis in financial complex systems is systematically introduced, including the empirical studies of recurrence intervals of volatilities, realized volatilities, returns and trading volumes. Based upon this study, we perform a primarily risk estimation for the stock market. Furthermore, an order driven model is introduced. The dynamics of the recurrence intervals between extreme events is studied by mimicking the order submission process of the investors in stock markets. This work may provide a theoretical foundation for the risk estimation and avoiding of extreme events in the Chinese stock market.
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