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Valeur à risque conditionnelle (Expected Shortfall)×Modèle ARIMA (Autoregressive Integrated Moving Average)×Exponential GARCH (EGARCH)×
DomaineFinanceÉconométrieÉconométrie
FamilleRegression modelRegression modelRegression model
Année d'origine200020151991
Auteur d'origineRockafellar & Uryasev (2000); Acerbi & Tasche (2002)Box & Jenkins (Box-Jenkins methodology)Nelson
TypeCoherent tail-risk measureUnivariate time-series modelConditional volatility model (asymmetric GARCH variant)
Source fondatriceRockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
AliasCVaR, expected shortfall, average value-at-risk, tail VaRBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeliexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Apparentées554
RésuméConditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it has replaced VaR as the regulatory standard under Basel III/IV.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.
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ScholarGateComparer des méthodes: Conditional Value-at-Risk · ARIMA · EGARCH. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare