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The Political Economy of Financial Innovation: Evidence from Local Governments
In: Review of Financial Studies, Forthcoming
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Working paper
Sources of Time Variation in the Covariance Matrix of Interest Rates*
In: The journal of business, Volume 79, Issue 3, p. 1535-1549
ISSN: 1537-5374
The Fairness of Credit Scoring Models
In: HEC Paris Research Paper No. FIN-2021-1411
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Working paper
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Working paper
The Risk Map: A New Tool for Validating Risk Models
This paper presents a new method to validate risk models: the Risk Map. This method jointly accounts for the number and the magnitude of extreme losses and graphically summarizes all information about the performance of a risk model. It relies on the concept of a super exception, which is de.ned as a situation in which the loss exceeds both the standard Value-at-Risk (VaR) and a VaR de.ned at an extremely low coverage probability. We then formally test whether the sequences of exceptions and super exceptions are rejected by standard model validation tests. We show that the Risk Map can be used to validate market, credit, operational, or systemic risk estimates (VaR, stressed VaR, expected shortfall, and CoVaR) or to assess the performance of the margin system of a clearing house.
BASE
The Risk Map: A New Tool for Validating Risk Models
This paper presents a new method to validate risk models: the Risk Map. This method jointly accounts for the number and the magnitude of extreme losses and graphically summarizes all information about the performance of a risk model. It relies on the concept of a super exception, which is de.ned as a situation in which the loss exceeds both the standard Value-at-Risk (VaR) and a VaR de.ned at an extremely low coverage probability. We then formally test whether the sequences of exceptions and super exceptions are rejected by standard model validation tests. We show that the Risk Map can be used to validate market, credit, operational, or systemic risk estimates (VaR, stressed VaR, expected shortfall, and CoVaR) or to assess the performance of the margin system of a clearing house.
BASE
The Risk Map: A New Tool for Validating Risk Models
This paper presents a new method to validate risk models: the Risk Map. This method jointly accounts for the number and the magnitude of extreme losses and graphically summarizes all information about the performance of a risk model. It relies on the concept of a super exception, which is de.ned as a situation in which the loss exceeds both the standard Value-at-Risk (VaR) and a VaR de.ned at an extremely low coverage probability. We then formally test whether the sequences of exceptions and super exceptions are rejected by standard model validation tests. We show that the Risk Map can be used to validate market, credit, operational, or systemic risk estimates (VaR, stressed VaR, expected shortfall, and CoVaR) or to assess the performance of the margin system of a clearing house.
BASE
The Risk Map: A New Tool for Validating Risk Models
This paper presents a new method to validate risk models: the Risk Map. This method jointly accounts for the number and the magnitude of extreme losses and graphically summarizes all information about the performance of a risk model. It relies on the concept of a super exception, which is de.ned as a situation in which the loss exceeds both the standard Value-at-Risk (VaR) and a VaR de.ned at an extremely low coverage probability. We then formally test whether the sequences of exceptions and super exceptions are rejected by standard model validation tests. We show that the Risk Map can be used to validate market, credit, operational, or systemic risk estimates (VaR, stressed VaR, expected shortfall, and CoVaR) or to assess the performance of the margin system of a clearing house.
BASE
The Economics of Computational Reproducibility
In: HEC Paris Research Paper No. FIN-2019-1345
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Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring
In: HEC Paris Research Paper No. FIN-2022-1463
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Computational Reproducibility in Finance: Evidence from 1,000 Tests
In: HEC Paris Research Paper No. FIN-2022-1467
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Risk Management Research Report - Spring 2010
In: Risk Management Research Report, Spring 2010
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