Market Crowds Trading Behaviors,Agreement Price,and Volume Implications
It has been long that literature in finance focuses mainly on price and return but much less even completely ignoring on trading volume.There is no trading volume in neoclassical finance models.Contrary to the prediction of rational models of investment in a neoclassical paradigm,however,trading volume is very high on the worlds stock market.Here we extend Shis price-volume differential equation and measure the frequency of market crowds trading action at a price by trading volume probability in the equation in terms of behavior analysis.We develop three kinds of market crowd’s trading behavioral models according to the equation,and test two behavioral hypotheses relevant to the volume uncertainty associated with price using high frequency data in China stock market.It is hardly surprising that we find: 1) market crowd,whole traders who interact among themselves with a variety of heterogeneous beliefs,preferences,and biases,accept,prefer to trade most,and reach agreement on a stationary equilibrium price widely over a trading price range on a daily basis; 2) market crowd adapt to gain and loss by volume increase or decrease in interaction with environment in an interactive feedback loop,and restore market to stationary equilibrium without delay after their trading action results in a large supply-demand imbalance,a stationary equilibrium price jump,and an expected return from time to time; 3) while significant herd and disposition anomalies disappear simultaneously by learning experience in a certain circumstance,other behavioral anomalies,for examples,greed and panic,pronounce significantly in decision making.The interaction between three terms in the course of gain and loss,which includes a variety of internal and external causes,produces excessive trading volume.The volume probability behavioral annotation suggests a key link and a new mathematical method for quantitative behavioral finance.
quantitative behavioral finance trading volume differential equation equilibrium price jump behavior analysis crowds trading behaviors
Leilei Shi Liyan Han Yingzi Zhu Bing Han Yiwen Wang Yan Piao
Complex System Research Group,Department of Modern Physics,University of Science and Technology of C School of Economics and Management,Beihang University School of Economics and Management,Tsinghua University McCombs School of Business,The University of Texas at Austin School of Economics,Fudan University
国际会议
2013 China Finance Review International Conference(第六届(2013)中国金融评论国际研讨会)
上海
英文
845-897
2013-07-08（万方平台首次上网日期，不代表论文的发表时间）