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Extreme events: blending PCA and ICA [14]

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Bullet points include: This is the basic idea behind independent components analysis. Again assume output (i.e. here, observed returns) come from a linear combination of input signals. But now focus on meaningfulness, e.g. ‘Independence’, ‘non-Normality’ or ‘complexity’. If source signals have some property X and signal mixtures do not (or have less of it) then given a set of signal mixtures we should attempt to extract signals with as much X as possible, since these extracted signals are then likely to correspond as closely as possible to the original source signals

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