Robust Estimation in VaR Modelling - Univariate Approaches using Bounded Innovation Propagation and Regression Quantiles Methodology
AbstractIn the paper we present robust estimation methods based on bounded innovation propagation filters and quantile regression, applied to measure Value at Risk. To illustrate advantage connected with the robust methods, we compare VaR forecasts of several group of instruments in the period of high uncertainty on the financial markets with the ones modelled using traditional quasi-likelihood estimation. For comparative purpose we use three groups of tests i.e. based on Bernoulli trial models, on decision making aspect, and on the expected shortfall.
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Bibliographic InfoArticle provided by CEJEME in its journal Central European Journal of Economic Modelling and Econometrics.
Volume (Year): 5 (2013)
Issue (Month): 1 (March)
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Web page: http://cejeme.org/
Robust estimation; quantile regression; CAViaR; ARMA-GARCH models;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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