This paper investigates the weekly stock market data of the Hungarian stock index BUX, the Czech stock index PX and the Polish stock index WIG20 spanning from January 7, 2001 to April 18, 2021. The period of more than 20 years enabled to analyse the behaviour of returns and their volatility during both the calm as well as various crises/turmoil periods. Besides the traditional GARCH-type models (GARCH and GJR-GARCH) the two-regime Markov Switching GARCHtype models (MS-GARCH and MS-GJR-GARCH) were estimated in order to examine the volatility switches of the Central European transition stock markets. The t-distribution of error terms was used to capture the dynamics of analysed returns more precisely. The results proved high volatility persistence of individual markets which substantially differed across the both regimes. Furthermore, the GJR-GARCH and MS-GJR-GARCH models clearly confirmed the presence of the leverage effect. Consideration of the MS-GARCH-type models enabled to capture various volatility switches during the analysed period attributable mainly to the global financial crisis 2008–2009, to European debt crisis in 2011 and to the Covid-19 pandemic in 2020. Interesting results were received for the Czech market with the strong leverage effect indicating completely different specification of volatility regimes by the MS-GJR-GARCH model.

中文翻译：

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部分中欧股票收益的波动性机制：马尔可夫切换 GARCH 方法

本文研究了匈牙利股票指数 BUX、捷克股票指数 PX 和波兰股票指数 WIG20 从 2001 年 1 月 7 日到 2021 年 4 月 18 日的每周股票市场数据。能够分析 20 多年的行为在平静以及各种危机/动荡时期的回报及其波动性。除了传统的 GARCH 型模型（GARCH 和 GJR-GARCH）外，还估计了两政体马尔可夫转换 GARCH 型模型（MS-GARCH 和 MS-GJR-GARCH），以检查中欧转型股票市场的波动率转换。误差项的 t 分布用于更精确地捕捉分析回报的动态。结果证明，各个市场的高波动性持续存在，这两种制度之间存在很大差异。此外，GJR-GARCH 和 MS-GJR-GARCH 模型清楚地证实了杠杆效应的存在。考虑 MS-GARCH 型模型能够在分析期间捕获主要归因于 2008-2009 年全球金融危机、2011 年欧洲债务危机和 2020 年 Covid-19 大流行的各种波动率变化。收到了有趣的结果对于具有强杠杆效应的捷克市场，表明 MS-GJR-GARCH 模型对波动率机制的规范完全不同。