Good risk measures, bad statistical assumptions, ugly risk forecasts

Michael Michaelides and Niraj Poudyal

The Financial Review, 2024, vol. 59, issue 2, 519-543

Abstract: This paper proposes the time‐heterogeneous Student's t autoregressive model as an alternative to the various volatility forecast models documented in the literature. The empirical results indicate that: (i) the proposed model has better forecasting performance than other commonly used models, and (ii) the problem of reliable risk measurement arises primarily from the model risk associated with risk forecast models rather than the particular risk measure for computing risk. Based on the results, the paper makes recommendations to regulators and practitioners.

Date: 2024
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