The Estimation Of Stock Returns And Systematic Risk

The two key points of this article is stock returns and systematic risk factor. The rate of returns can easily measure the earnings of the capital based on the day before and can also measure the volatility of the stock at the same time. Systematic risk ? factor is the measurement of the influence caused by the market of the individual capital, reflects sensitivity of securities yield level on the changes of the average level of return on the market and is a measure of an index of the level of how securities can bear the systematic risk. Systematic risk factor of the Portfolio Theory is a very important role in theory and investment practice. Its research can effectively provide an basis for decision making of asset pricing and risk management.The main issues discussed in the article is volatility modeling of stock returns in capital market and dynamic estimation of systematic risk factor, the main tool is GARCH family model in time series analysis and multiple GARCH model. Research is mainly used in the analysis of time series analysis tool. Financial time series showing a relatively stable stage and periodical volatility under normal circumstances. We use volatility modeling like ARCH family model and GARCH family models to estimate. In addition, we also need to estimate the correlation sequence of dynamic conditions between a single stock and market index when we study the systemic risk factors. The article picked the DCC-MVGARCH two-step modeling to achieve the estimate of the correlation coefficient sequence of dynamic conditions.The article select the SSE 50 Index constituent stocks of the daily transactions as samples and modeled upon completion of the non-return data normality test, stability test and basic ARCH Tests on data modeling. After comparing the model AIC, BIC, R squared and Squared residuals and other indicators, I determined that the optimal model is GARCH Models, achieved a good fit for the SSE 50 Index return series.In the end, I discussed the time-varying systemic risk coefficient on the basis of the article on the return series modeling. According to DCC-MVGARCH dynamic model obtained a correlation coefficient sequence yield stocks and index stocks yields and the respective conditional variance sequence. With the data given by the model, we can obtain a systemic risk coefficient sequence. The results show that most stocks coefficient yields have fluctuated between 0.5 and 1.5. Overall, the factor in the second quarter of 2015 have smaller fluctuations, and the trends of the various stock is close to the market at the same time. Above all the stocks, the Moutai's coefficient is smaller and more stable which is the least risky blue chips in SSE 50 Index. While China Merchants Securities' coefficient is large, there may be a very high risk.