The Impact Of The 52 Week High And 52 Week Low On The Volatility Of China Stock Markets

The 52-week high price and low price are the special points of the stock price.The stock volatility can reflect the volatility of the stock price and the size of the investment risk.When investing in stocks,the majority of investors in China will refer to these two aspects of information.At the same time,these special information have also attracted the attention of economic and financial researchers.The research object of this paper is 3467 listed companies in the Chinese A-share market,and the stock data is monthly data from January 2003 to December 2017.First the dummy variable was introduced:close to the 52-week high price,close to the 52-week low price,breaking the 52-week high price,and breaking the 52-week low price.The control variables are the monthly data of turnover rate,price-earnings ratio,book-to-book ratio,and market value.Volatility is the explanatory variable and a regression model is established.All companies were divided into two categories according to whether their time-to-market was more than five years and they were studied separately.Introducing individual effects and using Stata software to perform fixed effect panel analysis on the model.The empirical results show that when the stock price approaches the 52-week high price or close to the 52-week low price,the volatility rate shows a downward trend;when the stock price breaks the 52-week high price,the volatility rate Upward trend.When all companies and corporate stocks that have been listed for more than five years break the 52-week low,the volatility will rise;when the share price of companies that have been listed for less than five years breaks the 52-week low,the volatility will fall.Change the locator points in the definition of dummy variables and perform a robustness test.The coefficient of the dummy variable and the control variable in the test result is the same as that before the change.That is,it passed the robustness test.It is shown that the relationship between the high price of 52 weeks,the low price and the volatility is very robust.Secondly,an empirical analysis of this model is carried out using the method of machine learning-optimized particle swarm algorithm.After comparing the machine learning results with the panel results,it is found that the coefficient of the dummy variables in the machine learning results is consistent with the panel results.However,the results of the machine learning method have a higher coefficient of goodness of judgment and improve the panel results.Finally,the influence of 52-week high and low prices on stock returns is further studied.The result of the fixed-effects panel shows that when stocks approach high prices and break through high prices,earnings increase;when stocks approach low prices and break through low prices,earnings decrease.The 52-week high price and low price can indeed be used as reference standards in the stock investment.In the investment,both the income and the risk should be identified.