Resumen

MARINO USTACARA, Daniel  y  MELO VELANDIA, Luis Fernando. Dynamic quantile regression for the measurement of a value at risk: An application to Colombian data. Cuad. Econ. [online]. 2019, vol.38, n.76, pp.23-49. ISSN 0121-4772.  https://doi.org/10.15446/cuad.econ.v37n76.57654.

This document contains the results for the estimation of Value at Risk (VaR) based on linear and non-linear quantile regression techniques. In particular, several CAViaR (conditional autoregressive value at risk) models are implemented for this purpose. These models can replicate the empirical properties of asset returns without requiring distributional assumptions. In addition, these methods are compared with traditional VaR techniques for the Colombian peso exchange rate, a public debt market price index and the Colombian stock price index during the periods of December 2007 and November 2015. In general, the quantile regression-based techniques show a good performance with respect to the traditional models.

JEL: C32, C52, G10.

Palabras clave : Value at Risk; quantile regression; non-linear quantile regression; CAViAR model..

        · resumen en Español | Francés | Portugués     · texto en Español     · Español ( pdf )