Multi-item sales forecasting with total and split exponential smoothing

Multi-item sales forecasting with total and split exponential smoothing

Efficient supply chain management relies on accurate demand forecasting. Typically, forecasts are required at frequent intervals for many items. Forecasting methods suitable for this application are those that can be relied upon to produce robust and accurate predictions when implemented within an automated procedure. Exponential smoothing methods are a common choice. In this empirical case stu...

Forecasting with exponential smoothing methods and bootstrap

The Boot.EXPOS procedure is an algorithm that combines the use of exponential smoothing methods with the bootstrap methodology for obtaining forecasts. In previous works the authors have studied and analyzed the interaction between these two methodologies. The initial sketch of the procedure was developed, modified and evaluated until its final form designated as Boot.EXPOS.

Forecasting for Inventory Control with Exponential Smoothing

Volatility Forecasting with Smooth Transition Exponential Smoothing

Adaptive exponential smoothing methods allow smoothing parameters to change over time, in order to adapt to changes in the characteristics of the time series. This paper presents a new adaptive method for predicting the volatility in financial returns. It enables the smoothing parameter to vary as a logistic function of user-specified variables. The approach is analogous to that used to model t...

Robust forecasting with exponential and holt-winters smoothing

Robust versions of the exponential and Holt–Winters smoothing method for forecasting are presented. They are suitable for forecasting univariate time series in the presence of outliers. The robust exponential and Holt–Winters smoothing methods are presented as recursive updating schemes that apply the standard technique to pre-cleaned data. Both the update equation and the selection of the smoo...