Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets

Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders’ short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners.

[1]  M. Brennan A theory of price limits in futures markets , 1986 .

[2]  L. Telser,et al.  Margins and futures contracts , 1981 .

[3]  P. Hsieh,et al.  The magnet effect of price limits: A logit approach , 2009 .

[4]  D. Sornette,et al.  The Nasdaq crash of April 2000: Yet another example of log-periodicity in a speculative bubble ending in a crash , 2000 .

[5]  Yong Zeng,et al.  Can Price Limits Help When the Price is Falling? Evidence from Transactions Data on the Shanghai Stock Exchange , 2009 .

[6]  Didier Sornette,et al.  Antibubble and prediction of China's stock market and real-estate , 2004 .

[7]  Wei-Xing Zhou,et al.  Universal price impact functions of individual trades in an order-driven market , 2007, 0708.3198.

[8]  Avanidhar Subrahmanyam,et al.  Circuit Breakers and Market Volatility: A Theoretical Perspective , 1994 .

[9]  G. C. Tiao,et al.  The magnet effect of price limits: evidence from high-frequency data on Taiwan Stock Exchange , 2003 .

[10]  M. Nowak Five Rules for the Evolution of Cooperation , 2006, Science.

[11]  Attila Szolnoki,et al.  Coevolutionary Games - A Mini Review , 2009, Biosyst..

[12]  R. Olsen,et al.  Approximating a Truncated Normal Regression with the Method of Moments , 1980 .

[13]  Wei-Xing Zhou,et al.  Universal Price Impact Functions of Individual Trades in an Order-Driven Market , 2012 .

[14]  Wei‐Xing Zhou Determinants of immediate price impacts at the trade level in an emerging order-driven market , 2012, 1201.5448.

[15]  Attila Szolnoki,et al.  Correlation of positive and negative reciprocity fails to confer an evolutionary advantage: Phase transitions to elementary strategies , 2013, ArXiv.

[16]  Christopher K. Ma,et al.  Volatility, price resolution, and the effectiveness of price limits , 1989 .

[17]  R. Cook,et al.  Do Daily Price Limits Act as Magnets? The Case of Treasury Bond Futures , 1997 .

[18]  F. Lillo,et al.  Econophysics: Master curve for price-impact function , 2003, Nature.

[19]  D. Sornette,et al.  Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese Stock Market Bubbles , 2009, 0909.1007.

[20]  S. Rhee,et al.  An Anatomy of the Magnet Effect: Evidence from the Korea Stock Exchange High-Frequency Data , 2006 .

[21]  Attila Szolnoki,et al.  Evolutionary dynamics of group interactions on structured populations: a review , 2013, Journal of The Royal Society Interface.

[22]  Marcus Lim,et al.  The immediate price impact of trades on the Australian Stock Exchange , 2005 .

[23]  Wei-Xing Zhou,et al.  Empirical shape function of limit-order books in the Chinese stock market , 2008, 0801.3712.

[24]  D. Sornette,et al.  Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese Stock Market Bubbles , 2009 .

[25]  D. Sornette,et al.  The US 2000‐2002 market descent: How much longer and deeper? , 2002, cond-mat/0209065.

[26]  H. Berkman,et al.  The influence of daily price limits on trading in Nikkei futures , 1998 .