Estimation of volatility in stock price process

Abstract

In describing the stock price process, it is one of the most important to estimate volatility at. We explain the behavior of stock price process by using some simplified version of generalized Wiener process. First, we estimate volatility from real data, Korea Composite Stock Price Index(KOSPI) 200. Also we review three famous methods(autoregressive conditional heteroscedasticity(ARCH) model, exponentially weighted moving average(EWMA) model and generalized autoregressive conditional heteroscedasticity(GARCH) (1,1) model) for estimating the cur-rent level of volatility. Employing EWMA model, we estimate the cur-rent level of KOSPI 200.