Abstract

This study investigates the influence of increasing the forecast horizon on correlation between the forecast returns and the actual returns. ARMA and EGARCH models are used in this paper to capture univariate asset returns. ARMA model is conditional mean model and EGARCH model is conditional variance model and both of them are used for forecasting, parameter estimation and simulation of time series. The persistence in the volatility of the time series is usually exemplified by a highly persistent fitted EGARCH model. Traditional stationary ARMA processes are often used to capture high degree of persistence in financial time series. In this paper, a hybrid of EGARCH and ARMA model is used to forecast stock returns based on their actual returns then we have analysed the correlation trend between actual and forecasted returns by varying the forecast horizon. Results shown in this paper are depicting that correlation between actual and forecast returns undergoes a decaying pattern on increasing forecast horizon. Stock prices of three companies CIPLA, GAIL and LIC have been taken on daily basis from April 1997 to April 2010 and prediction has been done for next 150 days.

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