Extreme Events: Summary

Extreme events - A Summary [12]

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Bullet points include: Output results are notoriously sensitive to input assumptions. Possible responses: Treat quant models with scepticism (the fundamental manager’s approach?). Use robust approaches, Bayesian priors/anchors, e.g. Black-Litterman, ‘Shrinkage’, Position limit ‘priors’ (e.g. 1/N, long-only etc.), Resampling, Focus on reverse optimisation

Bullet points include: Output results are notoriously sensitive to input assumptions. Possible responses: Treat quant models with scepticism (the fundamental manager’s approach?). Use robust approaches, Bayesian priors/anchors, e.g. Black-Litterman, ‘Shrinkage’, Position limit ‘priors’ (e.g. 1/N, long-only etc.), Resampling, Focus on reverse optimisation

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