 Time Series Modeling and Forecasting of CPI of BangladeshS. M. Abu Saeed, Md. Sabuj Ali, Mst. Dilara Pervin and Md. Ziaul Hassan International Journal of Science and Business, 2018, vol. 2, issue 4, 530-537 Abstract: Time series data is very important in the case of financial development of any economy. But it is very difficult to deal with time series data. This study is consists of time series modeling and forecasting of some economic variables of Bangladesh. For this study we have considered CPI as selected economic variables of Bangladesh. The variable was collected from the “Monthly Economic Trends” published by the Bangladesh Bank. For modeling purpose we have used Box-Jenkins Methodology which is very popularly known in the sector of time series modeling. On the study at first we have checked the stationarity. For checking stationarity we have used both graphical method and Dickey Fuller test. Then to find the appropriate model for CPI we have used the ACF, PACF curves. After finding the appropriate models we have performed the diagnostic checking for each of the fitted model, which was good. Then by using the best fitted model we have find some forecasted values for each of the variables. Keywords: Stationarity; Box-Jenkins Methodology; Dickey Fuller test; ACF; PACF; ARIMA model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:aif:journl:v:2:y:2018:i:4:p:530-537 Access Statistics for this article International Journal of Science and Business is currently edited by Dr. Md Shamim Hossain More articles in International Journal of Science and Business from IJSAB International |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.