Comparison of forecasting techniques for short-term and long-term real life problems

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.