Analysis Of Volatility Of Stock Market Return

The study of stock market volatility is a meaning thing in the field of economic and finance.To study the volatility and to analysis the the uncertainty and risk of the stock market hasbecome the focus of attention of many academics and financial market participants.This paper first introduces GARCH modeling and steps. In order to facilitate more detailedstudy on Chinese stock market volatility characteristics, dividing Chinese stock market intothree periods, before the financial crisis, during financial crisis and after financial crisis andselecting the Shanghai Composite Index closing price data and volume data for study.In the third chapter, I take return data for statistical analysis, modeling, and draw: theGARCH models can fit the first phase and third phases of the return data, failing in the secondphase of data on GARCH modeling, indicating that during the financial abnormal crisis, thestock market time is not a valid. Respectively, during the use of the GARCH, EGARCH,TARCH, EGARCH-M model for fitting the first and the third data, I draw the conclusiondifferent from the usual: the same degree for good news and bad news, before the financialcrisis, good news has bigger impact on the market than bad news, bad news bigger than goodnews after the financial crisis. Another conclusion is that before the financial crisis the benefitis proportional to risk in the use of EGARCH-M analysis, but he benefit has nothing to dowith risk after the financial crisis. Therefore the benefit is proportional to the risk wegenerally approve of has condition. At the same time, a reasonable analysis and interpretationfor these phenomena is made with behavioral finance theory, Chinese stock market status andinvestor characteristics factors in this paper.In the fourth chapter, I examine an indicator which have effect on volatility–volume,using the classical approach to deal with the volume, and I get the trading volume ofcastration, sueprise trading volume, the unsurprise trading volume. Then different volume isadded to GARCH models equation based on the first and the third data to explore thepersistence and asymmetric effects which these transactions have on the volatility of thereturn. Empirical research also has a conclusion different from the mature and developedmarkets: persistent explanation of fluctuations on these volumes is limited and the unsurprise trading volume has the strongest explanation for volatility, surprise trading volume theweakest. Considering the asymmetric impact, the first stage results show all these tradingvolume have strong explanation for asymmetry, or even fully explanatory, for the asymmetriceffect, and the third stage unsurprise trading volume has big explanation but surprise tradingvolume did not, indicating that expected information can play a role in Chinese stock marketand the stock market is not mature. Finally I make a summary and a outlook.