Time Series Analysis: the Multiplicative Decomposition Method
Time Series Analysis: The Multiplicative Decomposition Method
Table of Contents Page Abstract………………………………………………………………………………………………………………………………………….3
Introduction………………………………………………………………………………………………………………………...…4-5
Methodology: Multiplicative Decomposition……………………………………………….…5-7
Advantages/Disadvantages of Multiplicative Method………………………………7-8
Conclusion…………………………………………………………………………………………………………………………………..8
Abstract
One of the most essential pieces of information useful to compute sales, and the ability to forecast them is strategically important. Forecasts can provide useful information to cut costs, increase efficient use of resources, and improve the capability to compete in a frequently changing environment. This study tests complicated, yet simple to use time series models to forecast sales. The results will show that, with minor rearrangement of past sales data, easy-to-use time series models can accurately forecast gross sales .Forecasters often need to guesstimate doubtful quantities, but with restricted time and resources. Decomposition is a method for dealing with such problems by breaking down the estimation task down into a set of components that can be more readily estimated, and then combining the component estimates to generate an objective estimate. Estimators can effectively apply decomposition to either multiplicative or segmented forecasts, though multiplicative decomposition is especially sensitive to associated errors in component values. Decomposition is most used for highly unsure estimates, such as ones having a large numerical value or quantities. Decomposition should be used only when the estimation can make component estimates more accurately or more confidently than the target estimate.
Introduction
In today’s business world, businesses must strategically choose a methodology which is best suited for the company when unforeseeable haphazard’s cause economical disasters. In this case, a
Table of Contents Page Abstract………………………………………………………………………………………………………………………………………….3
Introduction………………………………………………………………………………………………………………………...…4-5
Methodology: Multiplicative Decomposition……………………………………………….…5-7
Advantages/Disadvantages of Multiplicative Method………………………………7-8
Conclusion…………………………………………………………………………………………………………………………………..8
Abstract
One of the most essential pieces of information useful to compute sales, and the ability to forecast them is strategically important. Forecasts can provide useful information to cut costs, increase efficient use of resources, and improve the capability to compete in a frequently changing environment. This study tests complicated, yet simple to use time series models to forecast sales. The results will show that, with minor rearrangement of past sales data, easy-to-use time series models can accurately forecast gross sales .Forecasters often need to guesstimate doubtful quantities, but with restricted time and resources. Decomposition is a method for dealing with such problems by breaking down the estimation task down into a set of components that can be more readily estimated, and then combining the component estimates to generate an objective estimate. Estimators can effectively apply decomposition to either multiplicative or segmented forecasts, though multiplicative decomposition is especially sensitive to associated errors in component values. Decomposition is most used for highly unsure estimates, such as ones having a large numerical value or quantities. Decomposition should be used only when the estimation can make component estimates more accurately or more confidently than the target estimate.
Introduction
In today’s business world, businesses must strategically choose a methodology which is best suited for the company when unforeseeable haphazard’s cause economical disasters. In this case, a
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