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A1956
Title: Semiparametric modeling of multiple quantiles Authors:  Leopoldo Catania - Aarhus BBS (Denmark) [presenting]
Alessandra Luati - Imperial College London (United Kingdom)
Abstract: A semiparametric model is developed to track a large number of quantiles of a time series. The model satisfies the condition of non-crossing quantiles and the defining property of fixed quantiles. A key feature of the specification is that the updating scheme for time-varying quantiles at each probability level is based on the gradient of the check loss function, which forms a martingale difference sequence. Consistency of the associated M-estimator of the fixed parameters is established. The model can be applied for filtering and prediction. We also illustrate a number of possible applications, such as: i) semiparametric estimation of dynamic moments of the observables, ii) density prediction, and iii) quantile predictions.