Time Series Modelling of Volatility Forecasting in the Return of Tehran Cement Share Price

Investing in stock markets usually is involved in more risks than the bounds and bank deposits. It is expected that resulting returns (capital gain plus yields) from trading in a stock market to be more than those of in a risk free investment. Therefore, developing accurate techniques of estimation and forecasting in volatility analysis of financial markets is inevitable. Sum squares of weekly returns provide an unbiased measure for realized volatility. In this paper, returns is modelled by an ARIMA process, and volatility is modelled by ARIMA_XRL, ARMA-SCRL, GARCH, GARCH_C and a Risk_Metric processes. The main propose of present research is the estimation and forecasting of volatility in the weekly returns of Tehran Cement Company’ share during 1381/01/03 to 1385/07/26. Our models consist of Leverage Effects, Lagged Returns Effects, and also Structural Breaks. Our findings confirm, among all the techniques, that the accuracy of ARIMA–SCRL process in volatility modelling is considerable. Furthermore it was resulted that, bad and good news are of symmetric leverage effects on the return of Tehran cement share price.