Estimates Of Volatility And Risk Control

In the 21st century, China’s economy is undergoing tremendous changes, at the same time, China’s stock market which is called "barometer of the national economy," has undergone dramatic changes. During this time, the stock market has experienced both the 2007 and the 2009 bull market, also experienced the 2008 bear market, in 2014 fourth quarter, the stock market once again usher in a new round of rally, by the early in 2015, the broader market of Shanghai stand back above 3,000 points again, up to 3406.79 points, reached a new high since 2009. The large fluctuations of the stock market began to receive the attention of investors and academics, more and more research concerned about the financial risks, financial market volatility has also become one of the core content of modern financial theory.The volatility is not only the deciding factor of the financial assets, but also the key parameter of the financial derivatives pricing, whether can make accurate characterization and prediction of the market variables volatility, will be directly related to the effectiveness of risk management and rationality of derivatives pricing. There are two kind of volatility in the financial markets:one is implied volatility, which is based on the option price of the underlying asset, for example, a particular stock exist option trading, that is indicate this stock is the underlying asset of the option, then we can get the option price from the market directly, and through an iterative approach to get the volatility of the underlying stock by Black-Sholes formula, This volatility is called implied volatility of the underlying stock; the other is historical volatility, this volatility based on the historical data of the variables, at this time, the volatility usually defined as the standard deviation of the underlying variable rate of return.Traditional historical simulation method is not do packet processing to historical data, all the data as a set, and then we can get a time-varying volatility curve, which can use to analyze the risk of the assets. In this paper, we divide historical data into different set and calculate the standard deviation of each set, and then we can get two time-varying volatility curves:the maximum and minimum volatility curve. By analyzing the difference between the above two curves, we can get a new measurement of the financial variable’s risks. Further more, we will do some expanding research on this new measurement, smoothing above risk measure by stationary test, then we will discuss the connection between the smoothly time sequence and the trend of stock prices, to find the best trading point of financial assets and give the investment proposal of financial asset. Finally, in the empirical analysis phase, by analyzing the historical data of stock and stock index, to find the best parameter of the above risk investment strategy, that mean we will do the correlation analysis from a statistical point of view and give the confidence interval of value at risk investment, to ensure that the model is accurate and precise. At the same time, we will find the defect based on the empirical results and put forward the corresponding improvement and optimization strategies, to ensure the risk investment strategy is complete.