Precision Level of Forecasting Methods : An Empirical Investigation from Indian Stock Market

The ultimate objective of any forecasting model is whether or not it is capable of predicting future events with minimum error. Therefore it becomes important to analyse the accuracy of forecasting methods. The study has conducted a comparative analysis, starting from naïve models to highly sophisticated models like ARIMA family of models. Precision of forecasting models were judged with the help of accuracy measure (MAD, MSE, and MAPE). The study has used Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) to determine the level of differencing and AR and MA terms in the ARIMA model. The study concludes that the naive and exponential models are better than complex models