TY - JOUR ID - 19979 TI - Forecasting of Tehran Securities Price Index Using ARFIMA Model JO - Journal of Economic Research (Tahghighat- E- Eghtesadi) JA - JTE LA - en SN - 0039-8969 AU - Erfani, Alireza AD - Y1 - 2010 PY - 2010 VL - 44 IS - 1 SP - EP - KW - Long memory KW - rescaled range analysis KW - modified rescaled range analysis KW - ARFIMA model KW - ARIMA Model DO - N2 - In this paper we investigate the long memory of Tehran Securities Price Index and fit ARFIMA model using 970 daily data since 1382/1/6 until 1386/4/17. Furthermore, we compare the forecasting performance of ARFIMA and ARIMA models. The results show that the series is a long memory one and therefore it can become stationary by fractional differencing. We obtaine the fractional differencing parameter . Having done the fractional differencing and determination of the number of lags of autoregressive and moving average components, the model is specified as . We estimate the parameters of the model using 900 in-sample data and use this estimates for forecasting 70 out-sample data. Comparing forecasting performance of two models illustrate that forecasting performance of ARFIMA model is better than ARIMA model. JEL Classification: A12 UR - https://jte.ut.ac.ir/article_19979.html L1 - https://jte.ut.ac.ir/article_19979_43089800a2bb34943720070761f69828.pdf ER -