英文标题：
《Multifractal cross-correlations between the World Oil and other
  Financial Markets in 2012-2017》
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作者：
Marcin W\\k{a}torek, Stanis{\\l}aw Dro\\.zd\\.z, Pawe{\\l}
  O\\\'swi\\c{e}cimka, Marek Stanuszek
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最新提交年份：
2019
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英文摘要：
  Statistical and multiscaling characteristics of WTI Crude Oil prices expressed in US dollar in relation to the most traded currencies as well as to gold futures and to the E-mini S$\\&$P500 futures prices on 5 min intra-day recordings in the period January 2012 - December 2017 are studied. It is shown that in most of the cases the tails of return distributions of the considered financial instruments follow the inverse cubic power law. The only exception is the Russian ruble for which the distribution tail is heavier and scales with the exponent close to 2. From the perspective of multiscaling the analysed time series reveal the multifractal organization with the left-sided asymmetry of the corresponding singularity spectra. Even more, all the considered financial instruments appear to be multifractally cross-correlated with oil, especially on the level of medium-size fluctuations, as the multifractal cross-correlation analysis carried out by means of the multifractal cross-correlation analysis (MFCCA) and detrended cross-correlation coefficient $\\rho_q$ show. The degree of such cross-correlations is however varying among the financial instruments. The strongest ties to the oil characterize currencies of the oil extracting countries. Strength of this multifractal coupling appears to depend also on the oil market trend. In the analysed time period the level of cross-correlations systematically increases during the bear phase on the oil market and it saturates after the trend reversal in 1st half of 2016. The same methodology is also applied to identify possible causal relations between considered observables. Searching for some related asymmetry in the information flow mediating cross-correlations indicates that it was the oil price that led the Russian ruble over the time period here considered rather than vice versa.
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中文摘要：
研究了2012年1月至2017年12月期间，以美元表示的WTI原油价格与大多数交易货币、黄金期货和E-mini S$\\&$P500期货价格之间的统计和多尺度特征。结果表明，在大多数情况下，所考虑的金融工具的收益分布尾部遵循逆三次幂律。唯一的例外是俄罗斯卢布，其分布尾部较重，指数接近2。从多尺度的角度来看，所分析的时间序列揭示了多重分形组织以及相应奇异谱的左侧不对称性。更重要的是，所有考虑的金融工具似乎都与石油存在多重分形互相关，尤其是在中等规模波动的水平上，正如通过多重分形互相关分析（MFCCA）和去趋势互相关系数$\\ rho\\u q$进行的多重分形互相关分析所示。然而，这些金融工具之间的相互关联程度各不相同。与石油联系最紧密的是石油开采国的货币。这种多重分形耦合的强度似乎也取决于石油市场的趋势。在分析的时间段内，在石油市场熊市阶段，互相关水平系统性地增加，并在2016年上半年趋势逆转后达到饱和。同样的方法也适用于确定所考虑的观测值之间可能的因果关系。对介导相互关联的信息流中的一些相关不对称进行搜索表明，在本文所考虑的时间段内，正是油价导致了俄罗斯卢布的上涨，而不是相反。
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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：Computer Science        计算机科学
二级分类：Computational Engineering, Finance, and Science        计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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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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