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Lambda value at risk and regulatory capital : a dynamic approach to tail risk

Hitaj, Asmerilda; Mateus, Cesario; Peri, Ilaria - In: Risks : open access journal 6 (2018) 1, pp. 1-18

This paper presents the first methodological proposal of estimation of the VaR. Our approach is dynamic and calibrated … measures. We also propose a simple backtesting methodology by extending the VaR hypothesis-testing framework. Hence, we test … our VaR proposals under extreme downward scenarios of the financial crisis and different assumptions on the profit and …

Persistent link: https://www.econbiz.de/10011811561

A severity function approach to scenario selection

Mokinski, Frieder - 2017

The severity function approach (abbreviated SFA) is a method of selecting adverse scenarios from a multivariate density. It requires the scenario user (e.g. an agency that runs banking sector stress tests) to specify a "severity function", which maps candidate scenarios into a scalar severity...

Persistent link: https://www.econbiz.de/10011755965

Quantile Regression in Risk Calibration

Chao, Shih-Kang; Härdle, Wolfgang Karl; Wang, Weining - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2012

stress affects other factors. The CoVaR (Conditional VaR) framework has been developed for this purpose. The basic technical …

Persistent link: https://www.econbiz.de/10009651900

Risk Measure Estimates in Quiet and Turbulent Times : An Empirical Study

Chotard, Rosnan - 2017

In this study we empirically explore the capacity of historical VaR to correctly predict the future risk of a financial … risk measure, the Sample Quantile Process, which is a generalization of the VaR calculated on a rolling sample, and study …

Persistent link: https://www.econbiz.de/10012965577

Quantile Regression in Risk Calibration

Chao, Shih-Kang - 2017

stress affects other factors. The CoVaR (Conditional VaR) framework has been developed for this purpose. The basic technical …

Persistent link: https://www.econbiz.de/10012966323

Surrogate Data Models : Interpreting Large-Scale Machine Learning Crisis Prediction Models

Chan-Lau, Jorge A.; Hu, Ruofei; Ivanyna, Maksym; Qu, Ritong - 2023

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs model interpretability and their ability to provide adequate guidance in the design of crisis...

Persistent link: https://www.econbiz.de/10014256873

Estimación de capital por riesgo de precio: Evaluandometodologías para el caso peruano

Del Carpio, Carlos; Zevallos, Mauricio - In: Revista Estudios Económicos (2010) 19, pp. 47-62

Recientemente la Superintendencia de Banca, Seguros y AFP publicó el reglamento sobre requerimientos de capital por riesgo de mercado con el objetivo de adecuar la legislación peruana a los estándares recomendados por el Comité de Supervisión Bancaria de Basilea. Esta disposición exige que...

Persistent link: https://www.econbiz.de/10008788647

Indicadores tendenciales de inflación y su relevancia como variables indicativas de política monetaria

Armas, Adrián; Vallejos, Lucy; Vega, Marco - In: Revista Estudios Económicos (2011) 20, pp. 27-56

El Banco Central de Reserva del Perú opera bajo un esquema de metas explícitas de inflación. Esto implica el compromiso de situar el nivel de inflación en un promedio cercano a 2 por ciento a lo largo del tiempo. Sin embargo, la inflación total presenta alta volatilidad debido...

Persistent link: https://www.econbiz.de/10009018143

Which are the SIFIs? A Component Expected Shortfall approach to systemic risk

Banulescu, Georgiana-Denisa; Dumitrescu, Elena-Ivona - In: Journal of Banking & Finance 50 (2015) C, pp. 575-588

This paper proposes a component approach to systemic risk which allows to decompose the risk of the aggregate financial system (measured by Expected Shortfall) while accounting for the firm characteristics. Developed by analogy with the Component Value-at-Risk concept, our new systemic risk...

Persistent link: https://www.econbiz.de/10011118060

Detecting excessive credit growth : an approach based on structural counterfactuals

Saß, Magnus - 2024

The Basel credit-to-GDP gap is the single most popular measure of excessive credit growth and the financial cycle in general. It is based, however, on a purely statistical understanding of excessiveness: Growth is excessive if the credit-to-GDP ratio (i.e. the ratio of credit to nominal GDP) is...

Persistent link: https://www.econbiz.de/10015053486