A responsive multiplicative Holt-Winters approach for enhanced forecasting accuracy

In today's competitive business world, the quest for a more reliable forecasting method is an ongoing process. As a classical and reliable technique the Conventional Multiplicative Holt-Winters (CMHW) approach has been widely used in which three different recursion processes are incorporated to estimate the level, growth rate and the seasonal parameter. A set of estimated initial values having the number of elements equivalent to the seasonal length is used to initiate recursion for seasonal parameter. But the recursion processes of level and growth rate, initiated by using the individual single stationary values, might reflect a strong adherence to the preceding patterns of data sets compromising the forecasting accuracy. In this context the CMHW approach is modified with a periodic updating procedure in recursion process of the level and growth rate values. The proposed Responsive Multiplicative Holt-Winters (RMHW) method with a dynamic adjustment feature is validated through various sets of data.