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Thursday 16 May 2019, 1:00pm to 2:00pm
Fotios Petropoulous from the University of Bath will present a seminar to the Management Science Department
Abstract: The existing portfolio of models within a forecasting software is, very often, not able to capture the true data generating process (DGP). This had led many researchers to combine the forecasts from two or more forecasting models and, on average, achieve better accuracy. One approach to forecasting combination is bootstrapping and aggregation, or bagging. In this approach, the remainder of the data from a decomposition method is bootstrapped and then used to create new instances of the original series. Each new series is forecasted separately and the forecasts are then combined. In this talk, we present a new approach where instead of bootstrapping the remainder to create a new series, we use a large database tofind similar time series. These similar series are either forecasted using familiar models, explicitly assuming a DGP, or their “future” values are directly taken as forecasts in which case no DGP is assumed. Our approach is tested on real data and shows promising improvements over standard benchmarks,especially when historical information is limited.
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