Article: Comparison of Several Combined Methods for Forecasting Tehran Stock Exchange Index

 Ali Raoofi, Amir Hossein Montazer Hojat, Pouyan Kiani

 ABSTRACT: Forecasting economic and financial variables is of high interest to economic policymakers in all countries. In this paper, the Tehran Stock Exchange Price Index (TEPIX) is estimated and forecasted using daily data for the period 05/22/2011 to 08/11/2011. To achieve that goal, various forecasting methods will be applied, including ARIMA, FARIMA, ANN and ANFIS models. Comparing the forecast accuracy of the models mentioned above, using forecast accuracy measures such as RMSE, MAE, MAPE and U-Thiel Implied that the combined models of ANFIS and FARIMA have outperformed other models of forecasting daily stock indices. However, statistical comparison of forecast accuracy of different models using statistics such as Harvey, Leybourne & Newbold, shows no significant difference between the forecast accuracy of these models.

Keywords: Forecasting, Neural Network (ANN), ANFIS fuzzy neural network, FARIMA, Stock Index.

Article · Jun 2016 · International Journal of Business Forecasting and Marketing Intelligence