Modeling and evaluating conditional quantile dynamics in VaR forecasts

F. Cipollini, Giampiero Gallo () and A. Palandri
Authors registered in the RePEc Author Service: Alessandra Faggian

Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia

Abstract: We focus on the time-varying modeling of VaR at a given coverage τ, assessing whether the quantiles of the distribution of the returns standardized by their conditional means and standard deviations exhibit predictable dynamics. Models are evaluated via simulation, determining the merits of the asymmetric Mean Absolute Deviation as a loss function to rank forecast performances. The empirical application on the Fama–French 25 value–weighted portfolios with a moving forecast window shows substantial improvements in forecasting conditional quantiles by keeping the predicted quantile unchanged unless the empirical frequency of violations falls outside a data-driven interval around τ.

Keywords: asymmetric loss function; forecast evaluation; Risk management; Value at Risk; dynamic quantile (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-ecm, nep-mfd and nep-rmg
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Working Paper: Modeling and evaluating conditional quantile dynamics in VaR forecasts (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:cns:cnscwp:202308

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