astudyonthevolatilityofthebangladeshstockmarketbasedongarchtypemodels

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	astudyonthevolatilityofthebangladeshstockmarketbasedongarchtypemodels
	Roni Bhowmik 1; Wu Chao 1; Jewel Roy Kumar 2; Wang Shouyang1
刊名	journalofsystemsscienceandinformation
	2017
卷号	000 期号:003 页码:193
ISSN号	1478-9906
英文摘要	The generalized autoregressive conditional heteroskedasticity(GARCH) type models are used to investigate the volatility of Bangladesh stock market. The findings of the study demonstrate that the index volatility characteristics changes over time. The article shows that the data are divided into three sub-periods: pre crisis, crisis, and post crisis. Accordingly, the results of the findings indicate changes in the GARCH-type models parameter, risk premium and persistence of volatility in different periods. A significant 'low-yield associated with high-risk' phenomenon is detected in the crisis period and the 'leverage effect' occurs in each periods. The investors are irrational which is based on assumption of risk and return characteristics of assets. Consequently, the market is not as mature as developed market. It is found in the article that the threshold generalized autoregressive conditional heteroskedasticity(TGARCH) model is more accurate for the model accuracy. Additionally, statistic error measurements indicate that GARCH model is more efficient than others and it has also more forecasting ability.
语种	英语
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/36203]
专题	系统科学研究所
作者单位	1.中国科学院数学与系统科学研究院 2.Jatiya Kabi Kazi Nazrul Islam University
推荐引用方式 GB/T 7714	Roni Bhowmik,Wu Chao,Jewel Roy Kumar,et al. astudyonthevolatilityofthebangladeshstockmarketbasedongarchtypemodels[J]. journalofsystemsscienceandinformation,2017,000(003):193.
APA	Roni Bhowmik,Wu Chao,Jewel Roy Kumar,&Wang Shouyang.(2017).astudyonthevolatilityofthebangladeshstockmarketbasedongarchtypemodels.journalofsystemsscienceandinformation,000(003),193.
MLA	Roni Bhowmik,et al."astudyonthevolatilityofthebangladeshstockmarketbasedongarchtypemodels".journalofsystemsscienceandinformation 000.003(2017):193.