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摘要翻译：
在崩盘和危机频繁发生的今天，国际金融市场需要一个有效的监控系统。现代非线性方法，如递归量化分析(RQA)显示了揭示系统行为规律性的能力。因此，它们可以用于实时分析市场状态。本文对RQA在经济时间序列监测中的应用进行了研究。研究选取了12种股票指数、6种货币对和4种商品。
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英文标题：
《RQA Application for the Monitoring of Financial and Commodity markets
state》
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作者：
Sergii Piskun, Oleksandr Piskun, Dmitry Chabanenko
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最新提交年份：
2011
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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：Chaotic Dynamics 混沌动力学
分类描述：Dynamical systems, chaos, quantum chaos, topological dynamics, cycle expansions, turbulence, propagation
动力系统，混沌，量子混沌，拓扑动力学，循环展开，湍流，传播
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一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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英文摘要：
Nowadays, when crashes and crises are rather frequent events, an effective monitoring system for the international financial market is needed. Modern nonlinear methods, such as Recurrence Quantification Analysis (RQA), demonstrate the ability to reveal the regularities of the system behavior. Thus, they can be useful for the analysis of the market state in real time. In present paper we did an effort to apply the RQA for the purpose of economic time series monitoring. 12 stock indexes, 6 currency pairs and 4 commodities were taken for the study.
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PDF链接：
https://arxiv.org/pdf/1112.0297
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