Abstract

Exponential smoothing methods have been commonly used for time series forecasting. Holt’s linear trend exponential smoothing is a well-known exponential smoothing method and it can give successful forecasting results for time series which have trend component. In this study, a new modified Holt method is introduced. In modified Holt method, update formulas have second order lagged terms apart from classical Holt method. Moreover, initial values for trend and level and smoothing parameters are estimated by using particle swarm optimization. Strong and weak sides of the modified Holt method are investigated by using real-world data sets and simulated data sets.

Keywords: Forecasting; Exponential smoothing; Holt’s linear trend method; Particle swarm optimization