Estimating Stock Market Volatility Using Non-linear Models

Stock market price changes are negatively correlated with changes in volatility.A drop in the value of a stock (negative return) increases the financial leverage; this makes the stock riskier and thus increases its volatility.This effect is known as leverage effect.The volatility of asset returns can be seen as measurement of the risk for investment and provides essential information for the investors to make the correct decisions.The study focuses on developing a GARCH model for the daily closing price of S & P 500 stock price.The Akaike and Bayesian Information Criteria (AIC & BIC) techniques are used to estimate the p and q values of GARCH (p.q) model.The results show that GRCH (1, 1) is an appropriate model for the time series.