Why risk is so hard to measure

Danielsson, JonORCID logo; and Zhou, Chen (2015) Why risk is so hard to measure. [Working paper]
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This paper analyzes the robustness of standard risk analysis techniques, with a special emphasis on the specifications in Basel III. We focus on the difference between Value– at–Risk and expected shortfall, the small sample properties of these risk measures and the impact of using an overlapping approach to construct data for longer holding periods. Overall, risk forecasts are extremely uncertain at low sample sizes. By comparing the estimation uncertainty, we find that Value–at–Risk is superior to expected shortfall and the time-scaling approach for risk forecasts with longer holding periods is preferable to using overlapping data.


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