Corpus ID: 233324479

Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability

  title={Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability},
  author={Tobias Fissler and Yannick Hoga},
Backtesting risk measure forecasts requires identifiability (for model validation) and elicitability (for model comparison). The systemic risk measures CoVaR (conditional value-atrisk), CoES (conditional expected shortfall) and MES (marginal expected shortfall), measuring the risk of a position Y given that a reference positionX is in distress, fail to be identifiable and elicitable. We establish the joint identifiability of CoVaR, MES and (CoVaR, CoES) together with the value-at-risk (VaR) of… Expand

Figures and Tables from this paper


Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures
This paper proposes an original approach for backtesting systemic risk measures. This backtesting approach makes it possible to assess the systemic risk measure forecasts used to identify theExpand
Basel Framework
  • Basel. basel_framework/index.htm?export=pdf.
  • 2019
Elicitability and backtesting: Perspectives for banking regulation
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 forecastingExpand
Tests of Conditional Predictive Ability
This work proposes an alternative framework for out-of-sample comparison of predictive ability which delivers more practically relevant conclusions and is based on inference about conditional expectations of forecasts and forecast errors rather than the unconditional expectations that are the focus of the existing literature. Expand
Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures
An early warning system indicator for future systemic crises deduced from backtesting systemic risk measures makes it possible to assess the systemic risk measure forecasts used to identify the financial institutions that contribute the most to the overall risk in the financial system. Expand
We propose a measure for systemic risk: CoVaR, the value at risk (VaR) of the financial system conditional on institutions being under distress. We define an institution's contribution to systemicExpand
Quantiles as optimal point forecasts
Loss functions play a central role in the theory and practice of forecasting. If the loss function is quadratic, the mean of the predictive distribution is the unique optimal point predictor. If theExpand
Making and Evaluating Point Forecasts
Typically, point forecasting methods are compared and assessed by means of an error measure or scoring function, with the absolute error and the squared error being key examples. The individualExpand
Measuring Systemic Risk
The ability of components of SES to predict emerging systemic risk during the financial crisis of 2007-2009 is demonstrated, in particular, the outcome of stress tests performed by regulators; the decline in equity valuations of large financial firms in the crisis; and the widening of their credit default swap spreads. Expand
Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary [Previous title: "A Regression-based Joint Encompassing Test for Value-at-Risk and Expected Shortfall Forecasts"]
We propose forecast encompassing tests for the Expected Shortfall (ES) jointly with the Value at Risk (VaR) based on flexible link (or combination) functions. Our setup allows testing encompassingExpand