Comparison of Forecasting Techniques for Short-term and Long-term Real Life Problems

Authors

  • Nandita Barman Department of ICT, Bangladesh University of Professionals, Mirpur Dhaka-1216, Bangladesh
  • M Babul Hasan Department of Mathematics, Dhaka University, Dhaka-1000, Bangladesh

DOI:

https://doi.org/10.3329/dujs.v65i2.54523

Keywords:

Exponential Smoothing; Holt’s Method; Smoothing Constants; Forecast Error Holt-Winter‘s Method etc.

Abstract

In this paper, we analyze the most appropriate short-term and long term forecasting methods for our practical life where several methods of time series forecasting are available such as the Moving Averages method, Linear Regression with Time, Exponential Smoothing, Holt‘s Method, Holt-Winter‘s Method etc. This paper mainly concentrates on the Holt- Winters Exponential Smoothing technique as applied to time series that exhibit seasonality. The accuracy of the out-of-sample forecast is measured using MSE, MAPE, MAD. We will observe that the empirical results from the study indicate that the Holt-Winter‘s Multiplicative Forecasting Method processes as the most appropriate forecasting method for the sets of real life data that will be analyzed.

Dhaka Univ. J. Sci. 65(2): 139-144, 2017 (July)

Downloads

Download data is not yet available.
Abstract
23
PDF
26

Downloads

Published

2017-07-05

How to Cite

Barman, N., & Hasan, M. B. (2017). Comparison of Forecasting Techniques for Short-term and Long-term Real Life Problems. Dhaka University Journal of Science, 65(2), 139–144. https://doi.org/10.3329/dujs.v65i2.54523

Issue

Section

Articles