文献类型：期刊文献

英文题名：Modelling asset returns in the presence of price limits with Markov-switching mixture of truncated normal GARCH distribution: evidence from China

作者：Wang, Donghua[1];Ding, Jin[1];Chu, Guoqing[2];Xu, Dinghai[3];Wirjanto, Tony S.[4,5]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai, Peoples R China;[2]Hejiang Seaport Grp Finance Co Ltd, Zhoushan, Zhejiang, Peoples R China;[3]Univ Waterloo, Dept Econ, Waterloo, ON, Canada;[4]Univ Waterloo, Sch Accounting & Finance, Waterloo, ON, Canada;[5]Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON, Canada

年份：2021

卷号：53

期号：7

起止页码：781

外文期刊名：APPLIED ECONOMICS

收录：;WOS:【SSCI(收录号:WOS:000567609500001)】；

基金：This work was supported by the National Natural Science Foundation of China [71171083,71771087]; University of Waterloo.

语种：英文

外文关键词：Price limits; bound effects; markov Switching; mixture Models; value-at-Risk

摘要：This article proposes a general framework of a Markov Switching GARCH model with a mixture of truncated Gaussian to model asset returns with price limits in China. Theoretically, while retaining many convenient statistical properties of the Gaussian distribution, the proposed model also assumes a flexible time-varying volatility structure to accommodate the feature of the return data under price restrictions in China, such as the clusters near the bounds (due to the 'bound effect'). Empirically, we apply the model to eight representative stocks from Shanghai and Shenzhen stock markets in China. Lastly, we find that our proposed model dominates the conventional volatility models in terms of Value-at-Risk measures.