Empirical And Simulation Study About Price Limits In Stock Market

Price limits, as one of the most important price stability mechanisms in stock market, is widely used in emerging markets. For example, China’s stock market place10%price limits for ordinary shares, and implement a5%price limit to ST shares. Despite that, the mechanism is widely used all over the world, consensus has not been reached. Since it is difficult to deal with abnormal data and impossible to compare different limits under one market, to analyze every character of price limit seems to be with difficulty. Therefore, agent-based computational finance is also introduced to study the price limits.When talking about empirical research on pirce limts, it usually comes to three hypothesis:Trading interference hypotheisis, Volatility spillover hypothesis, Delayed price discovery hypothesis. In this paper, grouping method and event study methodology is used together to exam the three hypothesis and overtrading phenomenon. It shows that, decline limits does not support the first and third hypothesis, but it does cause volatility spillover and it may have effect on overreaction reducing. While increase limits dose not support the third hypothesis, partially support the first hypothesis, has no effect reducing overreaction, and it Is unable to judge whether or not it support the second hypothesis.A limit order market under continuous double auction mechanism is built to simulate the stock market, heterogeneity investor is considered. Each investor’s investment strategy is determined by the combination of three method, fundamental analysis, technical strategies, stochastic investment. Different investors have different weight on each method. By simulating under different price limits, it is found that strict price limit will reduce price volatility, and that it delayed the price discovery process. But proper price limit could be chosen, which may reduce price deviation as well as price volatility.Latest data is used to analyze price limit in China stock market, agent-based computational finance is introduced to study the impact of price limit margin. The result is meaningful to improve price limit system.