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componentacdmodelanditsapplicationinstudyingthepricerelatedfeedbackeffectininvestortradingbehaviorsinchinesestockmarket
Huang Zhiyuan1; Han Ai2; Wang Shouyang1
2018
Source Publicationjournalofsystemsscienceandcomplexity
ISSN1009-6124
Volume031Issue:003Pages:677
AbstractThis paper explores the investors' feedback to the price change by modelling the price- related dynamics of trading intensity. A component decomposition duration modeling approach, called the component autoregressive conditional duration (CACD) model, is proposed to capture the variation of trading intensity across time intervals between price change events. Based on the CACD model, an empirical analysis is carried out on the Chinese stock market that covers different market statuses. The empirical results suggest that the CACD model can capture the price-related dynamics of trading intensity, which supports the existence of the feedback effect and is robust across different market statuses. The authors also study how the investors react to the price change by examining the driven factors of the price-related dynamics of trading intensity. The authors find that the trading can be triggered by the fast rise in the price level and the high trading volume. Besides, investors are more sensitive to the price change direction in the sideways market than in the upward or downward markets.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/46218
Collection系统科学研究所
Affiliation1.中国科学院
2.中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Huang Zhiyuan,Han Ai,Wang Shouyang. componentacdmodelanditsapplicationinstudyingthepricerelatedfeedbackeffectininvestortradingbehaviorsinchinesestockmarket[J]. journalofsystemsscienceandcomplexity,2018,031(003):677.
APA Huang Zhiyuan,Han Ai,&Wang Shouyang.(2018).componentacdmodelanditsapplicationinstudyingthepricerelatedfeedbackeffectininvestortradingbehaviorsinchinesestockmarket.journalofsystemsscienceandcomplexity,031(003),677.
MLA Huang Zhiyuan,et al."componentacdmodelanditsapplicationinstudyingthepricerelatedfeedbackeffectininvestortradingbehaviorsinchinesestockmarket".journalofsystemsscienceandcomplexity 031.003(2018):677.
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