A Security Price Volatile Trading Conditioning Model

Leilei Shi, Yiwen Wang, Ding Chen, Liyan Han, Yan Piao and Chengling Gou
Additional contact information
Leilei Shi: Complex System Research Group, Department of Modern Physics University of Science and Technology of China
Yiwen Wang: Department of Finance, Beijing University of Aeronautics and Astronautics
Ding Chen: Harvest Fund Management Co. Ltd
Liyan Han: Department of Finance, Beijing University of Aeronautics and Astronautics
Yan Piao: Department of Physics, Beijing University of Aeronautics and Astronautics
Chengling Gou: Department of Physics, Beijing University of Aeronautics and Astronautics

Papers from arXiv.org

Abstract: We develop a theoretical trading conditioning model subject to price volatility and return information in terms of market psychological behavior, based on analytical transaction volume-price probability wave distributions in which we use transaction volume probability to describe price volatility uncertainty and intensity. Applying the model to high frequent data test in China stock market, we have main findings as follows: 1) there is, in general, significant positive correlation between the rate of mean return and that of change in trading conditioning intensity; 2) it lacks significance in spite of positive correlation in two time intervals right before and just after bubble crashes; and 3) it shows, particularly, significant negative correlation in a time interval when SSE Composite Index is rising during bull market. Our model and findings can test both disposition effect and herd behavior simultaneously, and explain excessive trading (volume) and other anomalies in stock market.

Date: 2010-01, Revised 2010-02
New Economics Papers: this item is included in nep-tra
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/1001.0656 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1001.0656

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().