Cross-Country Differences in Return and Volatility Metrics of World Equity Indices

IF 0.5 Q4 ECONOMICS
Iskandar Sheraliev, R. Ślepaczuk
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引用次数: 0

Abstract

Abstract This research seeks to determine whether the cross-country differences in return and volatility metrics in various country equity indices can be explained by differences in economic development. We base the study on the MSCI IMI net income indices on two samples: a 51-country sample from the period 31 May 2002 to 28 February 2022, and a 75-country sample from the period 30 November 2010 to 28 February 2022. In this study, countries are grouped into four categories: frontier, emerging, early-developed, and developed, based on gross domestic product (GDP) per capita. The Kruskal–Wallis rank sum test is used to find cross-group differences, and the results are further analyzed with the pairwise Wilcoxon rank sum test with the Holm–Bonferroni p value adjustment method. The results are relatively unintuitive and show that there is no significant cross-group difference in daily and monthly returns. There is evidence of a considerable difference in volatility metrics, especially in the case of the emerging market group, which is significantly different from the three other groups. The results are slightly sensitive to time period change and very sensitive to changes in income categories of some countries.
世界股票指数收益与波动指标的跨国差异
摘要本研究旨在确定各国股票指数中收益和波动性指标的跨国差异是否可以用经济发展差异来解释。我们对MSCI IMI净收入指数的研究基于两个样本:2002年5月31日至2022年2月28日期间的51个国家样本,以及2010年11月30日至2022年2月28日期间的75个国家样本。在这项研究中,根据人均国内生产总值(GDP),将国家分为四类:前沿、新兴、早期发达和发达。采用Kruskal-Wallis秩和检验发现组间差异,进一步采用两两Wilcoxon秩和检验和Holm-Bonferroni p值调整法分析结果。结果相对不直观,显示日和月收益没有显著的跨组差异。有证据表明,波动性指标存在相当大的差异,尤其是在新兴市场组的情况下,它与其他三个组明显不同。这些结果对时间变化略有敏感,对一些国家收入类别的变化非常敏感。
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来源期刊
CiteScore
0.60
自引率
0.00%
发文量
9
期刊介绍: The Central European Journal of Economic Modelling and Econometrics (CEJEME) is a quarterly international journal. It aims to publish articles focusing on mathematical or statistical models in economic sciences. Papers covering the application of existing econometric techniques to a wide variety of problems in economics, in particular in macroeconomics and finance are welcome. Advanced empirical studies devoted to modelling and forecasting of Central and Eastern European economies are of particular interest. Any rigorous methods of statistical inference can be used and articles representing Bayesian econometrics are decidedly within the range of the Journal''s interests.
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