正态性检验及其对另类分布的影响:新兴亚洲股票指数收益的实证分析。

Muneer Shaik
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引用次数: 0

摘要

在本文中,我们使用蒙特卡罗模拟实验研究了各种正态性检验对替代分布的能力。我们使用了7种不同的正态性检验,分别是矩检验、相关和回归检验,以及针对6种对称和4种非对称替代分布的经验分布函数检验。我们还对正态性检验的幂进行了秩分析。此外,我们对五个新兴亚洲股票指数(印度、印度尼西亚、马来西亚、新加坡和台湾)进行实证分析,以了解2000年1月至2020年1月期间的收益是否服从正态分布。我们发现,无论数据的频率如何,新兴亚洲股票指数的回报都不遵循正态分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Normality Tests and its Power against Alternative Distributions: An Empirical Analysis on Emerging Asian Stock Index Returns.
In this paper, we investigate the power of various normality tests against alternative distributions using Monte Carlo simulation experiments. We use seven different normality tests classified as moments tests, correlation and regression tests, and empirical distribution functional tests against six symmetric and four asymmetric alternative distributions. We also perform the rank analysis for the power of the normality tests. Furthermore, we conduct an empirical analysis of five emerging Asian stock indices (India, Indonesia, Malaysia, Singapore, and Taiwan) to understand whether the returns follow a normal distribution or not during the period from January 2000 to January 2020. We find that emerging Asian stock index returns do not follow normal distribution irrespective of the different frequencies of the data.
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