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http://dx.doi.org/10.5351/KJAS.2020.33.3.257

Multivariate exponential smoothing models with application to exchange rates  

Lee, Yeonha (Department of Applied Statistics, Chung-Ang University)
Seong, Byeongchan (Department of Applied Statistics, Chung-Ang University)
Publication Information
The Korean Journal of Applied Statistics / v.33, no.3, 2020 , pp. 257-267 More about this Journal
Abstract
We introduce multivariate exponential smoothing models based on a vector innovations structural time series framework. The models enable us to exploit potential inter-series dependencies to improve the fit and forecasts of multivariate (vector) time series. Models are applied to forecast the exchange rates of the UK pound (UKP) and US dollar (USD) against the Korean won (KRW) observed on monthly basis; subseqently, we compare their performance with alternative models. We observe that the multivariate exponential smoothing models are superior to alternatives.
Keywords
exponential smoothing methods; vector innovations structural time series frameworks; multivariate time series; state space models;
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