Lambda Value at Risk and Regulatory Capital: A Dynamic Approach to Tail Risk
Department of Statistics and Quantitative Methods, University of Milan Bicocca, U7, Via Bicocca degli Arcimboldi 8, Milan 20126, Italy
Department of Accounting and Finance, University of Greenwich, Old Royal Naval College, Park Row, London SE10 9LS, UK
Department of Economics, Mathematics and Statistics, Birkbeck University of London, Malet St, Bloomsbury, London WC1E 7HX, UK
Author to whom correspondence should be addressed.
Received: 17 January 2018 / Revised: 24 February 2018 / Accepted: 1 March 2018 / Published: 6 March 2018
This paper presents the first methodological proposal of estimation of the
. Our approach is dynamic and calibrated to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk measures. We also propose a simple backtesting methodology by extending the
hypothesis-testing framework. Hence, we test our
proposals under extreme downward scenarios of the financial crisis and different assumptions on the profit and loss distribution. The findings show that our
estimations are able to capture the tail risk and react to market fluctuations significantly faster than the
and expected shortfall. The backtesting exercise displays a higher level of accuracy for our
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MDPI and ACS Style
Hitaj, A.; Mateus, C.; Peri, I. Lambda Value at Risk and Regulatory Capital: A Dynamic Approach to Tail Risk. Risks 2018, 6, 17.
Hitaj A, Mateus C, Peri I. Lambda Value at Risk and Regulatory Capital: A Dynamic Approach to Tail Risk. Risks. 2018; 6(1):17.
Hitaj, Asmerilda; Mateus, Cesario; Peri, Ilaria. 2018. "Lambda Value at Risk and Regulatory Capital: A Dynamic Approach to Tail Risk." Risks 6, no. 1: 17.
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