英文标题：
《Emergence of Turbulent Epochs in Oil Prices》
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作者：
Josselin Garnier and Knut Solna
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最新提交年份：
2019
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英文摘要：
  Oil price data have a complicated multi-scale structure that may vary with time. We use time-frequency analysis to identify the main features of these variations and, in particular, the regime shifts. The analysis is based on a wavelet-based decomposition and analysis of the associated scale spectrum. The joint estimation of the local Hurst exponent and volatility is the key to detect and identify regime shifting and switching of the oil price. The framework involves in particular modeling in terms of a process of `multi-fractional\' type so that both the roughness and the volatility of the price process may vary with time. Special epochs then emerge as a result of these degrees of freedom, moreover, as a result of the special type of spectral estimator used. These special epochs are discussed and related to historical events. Some of them are not detected by standard analysis based on maximum likelihood estimation. The paper presents a novel algorithm for robust detection of such special epochs and multi-fractional behavior in financial or other types of data. In the financial context insight about such behavior of the asset price is important to evaluate financial contracts involving the asset.
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中文摘要：
油价数据具有复杂的多尺度结构，可能随时间而变化。我们使用时频分析来确定这些变化的主要特征，尤其是制度变迁。该分析基于相关尺度谱的小波分解和分析。局部赫斯特指数和波动率的联合估计是检测和识别油价制度变迁和转换的关键。该框架特别涉及“多分数”类型过程的建模，因此价格过程的粗糙度和波动性可能随时间而变化。由于这些自由度，而且由于使用了特殊类型的谱估计器，因此出现了特殊的时代。这些特殊的时代被讨论并与历史事件相关。其中一些未通过基于最大似然估计的标准分析检测到。该文提出了一种新的算法，用于金融或其他类型数据中此类特殊时期和多分数行为的鲁棒检测。在金融环境中，了解资产价格的这种行为对于评估涉及资产的金融合同非常重要。
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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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