Creating portfolio risk and return models [30]

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Bullet points include: Ways of reducing Monte Carlo sample sizes including: Changing variables and importance sampling Stratified sampling Quasi- (that is sub-) random sequences Weighted Monte Carlo For multivariate series (will in practice usually be the focus): For Gaussian type innovations / random variables use Cholesky decomposition Fat-tailed marginals catered for by using inverse of cdf Fat-tailed copulas more tricky

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