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• W2483669809 abstract "Over recent years, a new class of methods has been developed, belonging to the blind source separation (BSS) area of research, whose promise is to reveal the driving forces which underlie an observed data sequence. Actually, each measured signal depends on several distinct underlying factors, being essentially a mixture of them. It is these factors or source signals that are of primary interest, but they are buried within a large set of measured signal mixtures. Separating a relatively small number of distinct time-varying causal factors becomes crucial in multivariate financial time series analysis, when attempting to explain past comovements and to predict future evolutions. In this paper, BSS techniques are addressed for revealing fundamental factors behind 16 parallel series of foreign exchange rates. More accurate predictions can be performed via these independent components, after their separation, using different forecasting strategies and settings. Denoising and change-point detection can be also carried out for each independent component in turn." @default.
• W2483669809 created "2016-08-23" @default.
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• W2483669809 date "2011-02-20" @default.
• W2483669809 modified "2023-09-26" @default.
• W2483669809 title "Seeking for fundamental factors behind the co-movement of foreign exchange time series, using blind source separation techniques" @default.
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