ROBUST BACKTESTING TESTS FOR VALUE-AT-RISK MODELS

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Optimally Harnessing Inter-Day and Intra-Day Information for Daily Value-at-Risk Prediction (2013, unknown): “Escanciano and Olmo (2011) circumvent the bias induced by the latter in the context, for instance, of Kupiec’s (2005) unconditional coverage test statistic by deriving the correct asymptotic variance in the presence of model risk (and estimation uncertainty); a block-bootstrap is suggested as a…”
A review of backtesting for value at risk (2018, background): “…p S are maximum likelihood estimates of ( φ, p E 1 , . . . , p E k , p S ) and T 1 , 1 , T 0 , 1 , T 1 , 0 , T 0 , 0 are as deﬁned in Section 2.13 The asymptotic null distributions of both statistics are normal with zero means and certain variances, see Theorem 2 in Escanciano and Olmo (2011).”
Frontiers in VaR forecasting and backtesting (2016, methodology): “Later, Escanciano and Olmo (2011) analyze the effects of model misspecification on the UC and LRcc tests and propose using a block-bootstrap procedure to implement robust backtests.”