A Comparison of Extreme Value Theory Approaches for Determining Value at Risk

By Chris Brooks, A. Clare, J. W. Dalle Molle, G. Persand. 2005

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Extreme Value Theory for Finance: A Survey (2012, background): “See for instance Bao et al. (2006), Bali (2007), Bekiros and Georgoutsos (2005), Brooks et al. (2005), Gençay and Selçuk (2004), Ho et al. (2000), Kuester et al. (2006), Lee and Saltoğlu (2002), Manganelli and Engle (2004), Tolikas et al. (2007).”
A comprehensive review of Value at Risk methodologies (2014, methodology): “There is substantial empirical evidence that the standardised distribution of financial returns is not iid (see Hansen, 1994; Harvey and Siddique, 1999; Jondeau and Rockinger, 2003; Bali and Weinbaum, 2007; Brooks et al., 2005).”
Bias-corrected maximum likelihood estimation of the parameters of the generalized Pareto distribution (2016, unknown): “Hosking and Wallis (1987) discussed the method of moments (MOM) and probability-weighted moments (PWM) estimators of θ ; Castillo and Hadi (1997) propose the “elemental percentile method”; Luceño (2006) considered various “maximum goodness of fit” estimators, based on the empirical distribution…”
Value-at-Risk Prediction: A Comparison of Alternative Strategies (2005, methodology): “…heteroskedasticity (GARCH), mixed normal-GARCH (MN-GARCH), extreme value theory (EVT), and conditional autoregressive VaR (CAViaR), are used; and Brooks et al. (2005), who also use a variety of models (but none of which is identical to those in our study), including variants of the…”