摘要翻译：
利用一种新的技术，通过不同长度的局部平稳斑块的并置来表示非平稳数据，我们引入了对金融市场中的关键观察项：交易量和价格波动的综合分析。从分割过程中，我们可以引入交易量和价格波动的一组统计特征（程式化事实）的定量描述，即每个分布的尾部、交易量在一个交易时段中的U形剖面和交易量自相关函数的演化。交易量序列的分割提供了每个斑块波动参数缓慢演变的证据，指向混合场景。假设长期特征是简单局部形式的统计混合的结果，我们检验和比较不同的概率密度函数来提供交易量的长期分布，得出对数正态分布与经验分布的最佳一致性。此外，对价格波动幅度的分段与对交易量的分段结果有很大差异，表明价格波动统计量的变化比交易量的变化更快。
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英文标题：
《Bridging stylized facts in finance and data non-stationarities》
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作者：
Sabrina Camargo, Silvio M. Duarte Queiros, Celia Anteneodo
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最新提交年份：
2013
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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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一级分类：Physics        物理学
二级分类：Data Analysis, Statistics and Probability        数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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英文摘要：
  Employing a recent technique which allows the representation of nonstationary data by means of a juxtaposition of locally stationary patches of different length, we introduce a comprehensive analysis of the key observables in a financial market: the trading volume and the price fluctuations. From the segmentation procedure we are able to introduce a quantitative description of a group of statistical features (stylizes facts) of the trading volume and price fluctuations, namely the tails of each distribution, the U-shaped profile of the volume in a trading session and the evolution of the trading volume autocorrelation function. The segmentation of the trading volume series provides evidence of slow evolution of the fluctuating parameters of each patch, pointing to the mixing scenario. Assuming that long-term features are the outcome of a statistical mixture of simple local forms, we test and compare different probability density functions to provide the long-term distribution of the trading volume, concluding that the log-normal gives the best agreement with the empirical distribution. Moreover, the segmentation of the magnitude price fluctuations are quite different from the results for the trading volume, indicating that changes in the statistics of price fluctuations occur at a faster scale than in the case of trading volume.
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PDF链接：
https://arxiv.org/pdf/1302.3197