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亚洲新兴经济体股市联动:基于小波的方法。

Stock market comovements among Asian emerging economies: A wavelet-based approach.

机构信息

School of Economics and Management, Nanjing University of Science and Technology, Nanjing, PR China.

School of Economics Finance and Banking (SEFB), Universiti Utara Malaysia (UUM), Sintok, Malaysia.

出版信息

PLoS One. 2020 Oct 12;15(10):e0240472. doi: 10.1371/journal.pone.0240472. eCollection 2020.

DOI:10.1371/journal.pone.0240472
PMID:33044995
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7549817/
Abstract

Stock market, is one of the most important financial market which has a close relationship with a country's economy, due to which it is often called the barometer of the economy. Over the past 25 years, the stock markets have been affected by different global economic shocks. Various researchers have analyzed different aspects of these effects one by one, however, this study is an assessment of stock market interrelationship of emeriging Asian economies which include most of the East Asian, and Southeast Asian emerging economies with special focus on China for past decades during which different crisis occurred. We used Morgan Stanley capital international (MSCI) daily indices data for each stock market and compared Chinese stock market with the stock markets of India, Pakistan, Malaysia, Singapore, and Indonesia. We analyzed the data through the individual wavelet power spectrum, cross-wavelet transform and wavelet coherence, to determine the correlation and volatility among the selected stock markets. These model have the power to analyze co-movements among these countries with respect to both frequency and time spaces. Our findings show that there are co-movement patterns of higher frequencies during the crises periods of 1997, 2008 and 2015. The dependency strength among the considered economies is noted to increase in the crisis periods, which implies increased short- and long-term benefits for the investors. From a financial point of view, it has been determined that the co-movement strength among the emerging economies of Asia may have an effect on the VaR (Value at Risk) levels of a multi-country portfolio. Furthermore, the stock market of China shows a high correlation with the other six Asian stock emerging markets in both high and low-frequency spectrums. The association of the south and east Asian stock market with Chinese stock markets show the interconnection of these economies with the economy of China since past two decades. These findings are useful for investors, portfolio managers and the policymaker around the globe.

摘要

股票市场是最重要的金融市场之一,与一个国家的经济密切相关,因此常被称为经济的晴雨表。在过去的 25 年中,股票市场受到了不同的全球经济冲击的影响。不同的研究人员已经逐一分析了这些影响的不同方面,然而,这项研究是对新兴亚洲经济体的股票市场相互关系的评估,其中包括大多数东亚和东南亚新兴经济体,特别关注过去几十年中国发生的不同危机期间的情况。我们使用摩根士丹利资本国际(MSCI)的每日指数数据对每个股票市场进行分析,并将中国股票市场与印度、巴基斯坦、马来西亚、新加坡和印度尼西亚的股票市场进行比较。我们通过单个小波功率谱、交叉小波变换和小波相干性来分析数据,以确定所选股票市场之间的相关性和波动性。这些模型具有分析这些国家在频率和时间空间方面共同运动的能力。我们的研究结果表明,在 1997 年、2008 年和 2015 年的危机期间存在较高频率的共同运动模式。在所考虑的经济体之间的依存关系在危机期间有所增强,这意味着投资者的短期和长期利益增加。从金融角度来看,已经确定亚洲新兴经济体之间的共同运动强度可能会对多国投资组合的 VaR(风险价值)水平产生影响。此外,中国的股票市场与其他六个亚洲新兴股票市场在高频和低频谱上都表现出高度相关性。过去二十年来,南亚和东南亚股票市场与中国股票市场的关联表明,这些经济体与中国经济之间存在联系。这些发现对全球投资者、投资组合经理和政策制定者都很有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/2714f7c07d41/pone.0240472.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/61a5ab010661/pone.0240472.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/7e88255f598e/pone.0240472.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/708f40d57f51/pone.0240472.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/00a430a8d527/pone.0240472.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/2714f7c07d41/pone.0240472.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/61a5ab010661/pone.0240472.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/7e88255f598e/pone.0240472.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/708f40d57f51/pone.0240472.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/00a430a8d527/pone.0240472.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c790/7549817/2714f7c07d41/pone.0240472.g005.jpg

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本文引用的文献

1
Wavelet coherence of EEG signals for a visual oddball task.脑电信号的小波相干性在视觉Oddball 任务中的应用。
Comput Biol Med. 2013 Jan;43(1):23-31. doi: 10.1016/j.compbiomed.2012.10.008. Epub 2012 Nov 27.
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Between-brain coherence during joint n-back task performance: a two-person functional near-infrared spectroscopy study.两人合作 n 回任务表现时的大脑间相干性:一项功能性近红外光谱研究。
Behav Brain Res. 2012 Oct 1;234(2):212-22. doi: 10.1016/j.bbr.2012.06.024. Epub 2012 Jun 29.
马来西亚股票市场与新兴市场和经合组织贸易伙伴的风险和因果关系共同变动。基于小波方法的证据。
PLoS One. 2024 Jan 25;19(1):e0296712. doi: 10.1371/journal.pone.0296712. eCollection 2024.
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Economy and elderly population, complementary or contradictory: A cross-continental wavelet coherence and cross-country Granger causality study.经济与老年人口:互补还是矛盾?——一项跨洲的小波相干性和跨国的格兰杰因果关系研究。
PLoS One. 2023 Jan 26;18(1):e0278716. doi: 10.1371/journal.pone.0278716. eCollection 2023.