Abdul Basit
State Bank of Pakistan, Pakistan
Title: Estimation of differencing parameter of arima models
Biography
Biography: Abdul Basit
Abstract
Forecasting of key economic indicators has an important role in the policymaking. Statisticians and economist are still trying to find out the techniques and models which provides a more accurate forecast. There are different time series models are available in the literature like Auto-Regressive (AR) model, Moving Average (MA) model, Auto-Regressive Moving Average (ARMA) model, Auto-Regressive Integrated Moving Average (ARIMA) model, Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model, and many others. ARIMA and ARFIMA mostly used for the analysis of time series. In this study, we are trying to estimate the differencing parameter’ using the information function and entropy. The comparison of classical time series models and a new time series model is also included in this study. The new estimator of the differencing parameter will give us a more accurate forecast as compared to the classical time series models.