Tail fitting, quantile interpolation [23]

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Bullet points include: Typically smaller errors if we adjust simulations to match 1st and 2nd moments of distribution. E.g. by using principal components to arrange for simulations to have the same means, standard deviations and correlations as the assumed underlying distribution. Low discrepancy (Halton). Again relative appeal of quantile interpolation perhaps improves as simulation numbers rise

Bullet points include: Typically smaller errors if we adjust simulations to match 1st and 2nd moments of distribution. E.g. by using principal components to arrange for simulations to have the same means, standard deviations and correlations as the assumed underlying distribution. Low discrepancy (Halton). Again relative appeal of quantile interpolation perhaps improves as simulation numbers rise

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