CMAF Friday Forecasting Talk: A new taxonomy of vector exponential smoothing and its application to seasonal time series
Friday 11 February 2022, 2:00pm to 3:00pm
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Event Details
CMAF Friday Forecasting Talk
The abstract: In the context of short-term demand forecasting, businesses are often required to forecast the demand of seasonal products, based on very few complete seasonal cycles of data. This makes the forecasting task difficult, but one possible solution is to make use of the readily available cross-sectional information from a homogeneous group. We propose a framework based on vector ETS (VETS), and provide a conceptual contribution by devising a taxonomy of pure additive and multiplicative ETS models, bringing together the factors of parameters, initial values and components (PIC). This framework is general in the sense that it is not limited to, although inspired from, the modelling of seasonal components. It can be applied to level, trend (including damped trend) and any possible combination of these features. Insights drawn from this research on the impact from improved efficiency and flexibility of estimation on multivariate forecasting will be discussed.
Speaker
University of Portsmouth
Dr Huijing Chen is a Senior Lecturer in Operations Management and holds a PhD in short-term seasonal demand forecasting. She has published in high quality journals such as European Journal of Operational Research, International Journal of Forecasting and Journal of the Operational Research Society. She has won an EPSRC-funded research project examining hierarchical seasonal demand forecasting, and recently a knowledge transfer project (KTP) from Innovate UK to investigate the potential of preven
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Name | Teresa Aldren |
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