英文标题：
《Multifractal cross wavelet analysis》
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作者：
Zhi-Qiang Jiang (ECUST, BU), Xing-Lu Gao (ECUST), Wei-Xing Zhou
  (ECUST), H. Eugene Stanley (BU)
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最新提交年份：
2018
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英文摘要：
  Complex systems are composed of mutually interacting components and the output values of these components are usually long-range cross-correlated. We propose a method to characterize the joint multifractal nature of such long-range cross correlations based on wavelet analysis, termed multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, the empirical joint multifractality of MFXWT is found to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indexes and uncover intriguing joint multifractal nature in pairs of index returns and volatilities.
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中文摘要：
复杂系统由相互作用的组件组成，这些组件的输出值通常是长程互相关的。我们提出了一种基于小波分析的方法来描述这种长程互相关的联合多重分形性质，称为多重分形交叉小波分析（MFXWT）。我们通过对具有多重分形互相关的双二项式测度和具有单分形互相关的二元分数布朗运动（bFBMs）进行广泛的数值实验来评估MFXWT方法的性能。对于二项式多重分形测度，MFXWT的经验联合多重分形性与理论公式基本一致。对于bFBMs，MFXWT可能会提供虚假的多重分形，因为多重分形谱的范围很广。我们还将MFXWT方法应用于股票市场指数，揭示了指数收益率和波动率对中有趣的联合多重分形性质。
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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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