峰度
计量经济学
估计员
马尔可夫链
单变量
蒙特卡罗方法
ARCH模型
随机波动
经济衰退
马尔科夫蒙特卡洛
波动性(金融)
数学
经济
应用数学
统计
多元统计
凯恩斯经济学
标识
DOI:10.1080/07350015.2021.1974459
摘要
In this article, we derive neat matrix formulas in closed form for computing higher order moments and kurtosis of univariate Markov switching GARCH models. Then we provide asymptotic theory for sample estimators of higher order moments and kurtosis which can be used for testing normality. We also check our theory statements numerically via Monte Carlo simulations. Finally, we take advantage of our theoretical results to recognize different periods of high volatility stressing the stock markets, such as financial crisis and pandemic.
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