股票价格持续大幅波动前后多重分形谱的异常及分析被引量：13

Anomaly of Multifractal Spectrum Before and After Stock Price Continuously Fluctuating Sharply and Its Analyses

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摘要利用多重分形谱可以深入地分析金融时间序列的微观结构及其特征。本文以民生银行、长江通信二上市公司的具体数据为例,以它们出现持续大幅震荡前后共35天的5min股价高频交易序列为原始数据,并将连续5天的高频数据分为一组,考察每支股票在持续大涨及持续大跌前后各个阶段时多重分形谱的形态及其重要参数的变化。研究表明股价持续大幅波动前后,股票价格的高频时间序列的多重分形谱具有前兆性的共同特征。运用本文的研究方法可以对个股持续大幅波动的开始及结束做出一定预测。 Using multifractal spectrum this paper analyze the micro finance properties of the stock-price sequences. Taking two stocks as examples, wefirst select each stock＇5 min high frequency trading data totaling 35 trading days, which cover the beginning and ending of continuous and sharp fluctuation on stock-prices. Then five successive trading days are classed into one group. And concerning to this two stocks, we research multifractal spectra＇s sharps and key parameters of each group. Result shows that muhifractal spectra have common precursors before and after prices fluctuate anomalously. Using the method in this paper we can forecast when stock prices＇ abnormal variation occur and finish.

作者周孝华宋坤杨秀苔

机构地区重庆大学经济与工商管理学院

出处《管理工程学报》 CSSCI 2006年第2期92-96,共5页 Journal of Industrial Engineering and Engineering Management

基金国家自然科学基金资助项目(70473107)

关键词持续大涨大跌多重分形谱高频交易数据预测 continuous and sharp fluctuation multifractal spectrum high-frequency trading data forecast

分类号 F830.91 [经济管理—金融学]

作者简介周孝华（1965-），男，湖南武冈人，副教授，博士，主要从事证券市场、金融工程的研究。

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