arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0806.3171cond-mat.stat-mechq-fin.ST
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随机游动的分数阶导数:具有长时间记忆的时间序列

Fractional derivatives of random walks: Time series with long-time memory

H. Eduardo Roman, Markus Porto

摘要:

我们审查的统计特性产生的应用程序(正,负阶)分数阶导数算子的标准随机游走模型,并显示所产生的随机游走显示缓慢衰减的自相关函数。这些相关的步行和著名的分数集成自回归(FIGIGUAL)模型,通常用于计量经济学研究之间的关系进行了讨论。相关随机游走模拟经验金融时间序列的应用程序被认为是和比较从FIGERAND和简单的FIGERAND过程的预测。与经验数据进行比较。

英文摘要:

We review statistical properties of models generated by the application of a (positive and negative order) fractional derivative operator to a standard random walk and show that the resulting stochastic walks display slowly-decaying autocorrelation functions. The relation between these correlated walks and the well-known fractionally integrated autoregressive (FIGARCH) models, commonly used in econometric studies, is discussed. The application of correlated random walks to simulate empirical financial times series is considered and compared with the predictions from FIGARCH and the simpler FIARCH processes. A comparison with empirical data is performed.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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