Open Access
December 2017 Elicitability and backtesting: Perspectives for banking regulation
Natalia Nolde, Johanna F. Ziegel
Ann. Appl. Stat. 11(4): 1833-1874 (December 2017). DOI: 10.1214/17-AOAS1041
Abstract

Conditional forecasts of risk measures play an important role in internal risk management of financial institutions as well as in regulatory capital calculations. In order to assess forecasting performance of a risk measurement procedure, risk measure forecasts are compared to the realized financial losses over a period of time and a statistical test of correctness of the procedure is conducted. This process is known as backtesting. Such traditional backtests are concerned with assessing some optimality property of a set of risk measure estimates. However, they are not suited to compare different risk estimation procedures. We investigate the proposal of comparative backtests, which are better suited for method comparisons on the basis of forecasting accuracy, but necessitate an elicitable risk measure. We argue that supplementing traditional backtests with comparative backtests will enhance the existing trading book regulatory framework for banks by providing the correct incentive for accuracy of risk measure forecasts. In addition, the comparative backtesting framework could be used by banks internally as well as by researchers to guide selection of forecasting methods. The discussion focuses on three risk measures, Value at Risk, expected shortfall and expectiles, and is supported by a simulation study and data analysis.

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Copyright © 2017 Institute of Mathematical Statistics
Natalia Nolde and Johanna F. Ziegel "Elicitability and backtesting: Perspectives for banking regulation," The Annals of Applied Statistics 11(4), 1833-1874, (December 2017). https://doi.org/10.1214/17-AOAS1041
Received: 1 May 2016; Published: December 2017
Vol.11 • No. 4 • December 2017
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