摘要翻译：
本文介绍了多重分形递减互相关方法，并将其应用于外汇市场时间序列。利用2010-2018年间世界八大货币高频汇率的波动来研究交叉相关性。这项研究的动机是复杂系统对重大环境变化的反应的基本问题，以及投资策略的潜在应用，包括发现三角套利机会。汇率之间的主要多尺度交叉相关通常发生在较小的波动水平上。然而，用多尺度互相关系数的新应用，用树状图表示的关系的层次组织在大波动时更加明显。在三角关系内的汇率对之间，交叉相关性被量化为平均更强。然而，与三角关系的平均强度相比，一些来自三角关系之外的对被发现异常强烈的相关性，这尤其适用于涉及澳元和新西兰元并反映其经济关系的汇率。对外汇市场有影响的重大事件会诱导三角套利机会，从而减少最小时间尺度上的交叉相关性，并对相关性的多尺度组织产生破坏性作用。2010-2018年，这种情况发生在瑞士央行干预和英国退出欧盟程序启动后英镑走软的情况下。该方法适用于任何时间序列的时域和多尺度模式检测。
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英文标题：
《Detecting correlations and triangular arbitrage opportunities in the
  Forex by means of multifractal detrended cross-correlations analysis》
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作者：
Robert G\k{e}barowski, Pawe{\l} O\'swi\k{e}cimka, Marcin W\k{a}torek,
  Stanis{\l}aw Dro\.zd\.z
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最新提交年份：
2019
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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：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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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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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  Multifractal detrended cross-correlation methodology is described and applied to Foreign exchange (Forex) market time series. Fluctuations of high frequency exchange rates of eight major world currencies over 2010-2018 period are used to study cross-correlations. The study is motivated by fundamental questions in complex systems' response to significant environmental changes and by potential applications in investment strategies, including detecting triangular arbitrage opportunities. Dominant multiscale cross-correlations between the exchange rates are found to typically occur at smaller fluctuation levels. However hierarchical organization of ties expressed in terms of dendrograms, with a novel application of the multiscale cross-correlation coefficient, are more pronounced at large fluctuations. The cross-correlations are quantified to be stronger on average between those exchange rate pairs that are bound within triangular relations. Some pairs from outside triangular relations are however identified to be exceptionally strongly correlated as compared to the average strength of triangular correlations.This in particular applies to those exchange rates that involve Australian and New Zealand dollars and reflects their economic relations. Significant events with impact on the Forex are shown to induce triangular arbitrage opportunities which at the same time reduce cross--correlations on the smallest time scales and act destructively on the multiscale organization of correlations. In 2010--2018 such instances took place in connection with the Swiss National Bank intervention and the weakening of British pound sterling accompanying the initiation of Brexit procedure. The methodology could be applicable to temporal and multiscale pattern detection in any time series.
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PDF链接：
https://arxiv.org/pdf/1906.07491