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Huang Zhiyuan1; Han Ai2; Wang Shouyang1
Source Publicationjournalofsystemsscienceandcomplexity
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.
Document Type期刊论文
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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