英文标题：
《Analysis of cyclical behavior in time series of stock market returns》
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作者：
Djordje Stratimirovic, Darko Sarvan, Vladimir Miljkovic, Suzana Blesic
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最新提交年份：
2017
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英文摘要：
  In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet spectral analysis to study SMI returns data, and the Hurst exponent formalism to study local behavior around market cycles and trends. We have found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we have found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We also report on the possibilities to differentiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude for the peaks in the small scales region could be used for partial differentiation between market economies. Finally, we propose a way to quantify the level of development of a stock market based on the Hurst scaling exponent approach. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.
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中文摘要：
本文分析了三种股票市场指数（SMI）时间序列的标度特性和周期性行为：发达经济体、新兴经济体和欠发达或转型经济体的股票市场数据。我们使用了两种数据分析技术来获得并验证我们的发现：小波谱分析用于研究SMI回报数据，赫斯特指数形式主义用于研究围绕市场周期和趋势的局部行为。我们在分析的所有SMI数据集中都发现了周期性行为。此外，我们发现，在我们的数据集中，周期区间的位置和边界对于所有市场都是常见的。我们在SMI数据中列出并说明了九个这样的周期。我们还报告了通过统计分析表征特定峰值行为的小波谱特性来区分所分析市场增长水平的可能性。我们的结果表明，小尺度区域峰值的相对WT能量含量和相对WT振幅等指标可用于市场经济之间的部分差异。最后，我们提出了一种基于赫斯特标度指数方法量化股票市场发展水平的方法。根据为我们的九个峰值区域计算的局部标度指数，我们定义了我们所称的发展指数，这证明，至少在我们的数据集的情况下，它适合于对我们分析的三个不同组的SMI序列进行排序。
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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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