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This paper concerns the forecasting of seasonal intraday time series. An extension of Holt-Winters exponential smoothing has been proposed that smoothes an intraday cycle and an intraweek cycle. A recently proposed exponential smoothing method involves smoothing a different intraday cycle for...
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In this paper, we consider the introduction of Markov-switching (MS) processes to both the permanent and transitory components of the Beveridge-Nelson (BN) decomposition. This new class of MS models within the context of BN decomposition provides an alternative framework in the study of business...
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Organizations with large-scale inventory systems typically have a large proportion of items for which demand is intermittent and low volume. We examine different approaches to forecasting for such products, paying particular attention to the need for inventory planning over a multi-period...
Persistent link: https://www.econbiz.de/10008508605
The Beveridge-Nelson vector innovations structural time series framework is a new formulation that decomposes a set of variables into their permanent and transitory components. The proposed framework is flexible, modelling inter-series relationships and common features in a simple manner. In...
Persistent link: https://www.econbiz.de/10008473677
This paper considers Beveridge-Nelson decomposition in a context where the permanent and transitory components both follow a Markov switching process. Our approach insorporates Markov switching into a single source of error state-space framework, allowing business cycle asymmetries and regime...
Persistent link: https://www.econbiz.de/10010904222
This paper is concerned with identifying an effective method for forecasting the lead time demand of slow-moving inventories. Particular emphasis is placed on prediction distributions instead of point predictions alone. It is also placed on methods which work with small samples as well as large...
Persistent link: https://www.econbiz.de/10010860402
The use of the Beveridge Nelson decomposition in macroeconomic analysis involves the truncation and estimation of infinite weighted sums of random variables, whereas the single source of error (SSE) state space approach provides a simple and effective framework that leads to exactly the same...
Persistent link: https://www.econbiz.de/10005342170
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