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Analysis of extreme events [39]

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Bullet points include: Most important (predictable) single contributor to fat tails seems to be time-varying volatility. So: Calculate covariance matrix between return series after stripping out effect of time-varying volatility Optimise as you think fit (standard, “robust”, Bayesian, BL, ...), using adjusted covariance matrix Adjust risk aversion/risk budget appropriately Then unravel time-varying volatility adjustment Or derive implied alphas using same adjusted covariance matrix Implicitly assumes all adjusted return series ‘equally’ fat-tailed

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