Estimation and Application of Fully Parametric Multifactor Quantile Regression with Dynamic Coefficients

Item Type Monograph (Working Paper)
Abstract

This paper develops and applies a novel estimation procedure for quantile regressions with time-varying coefficients based on a fully parametric, multifactor specification. The algorithm recursively filters the multifactor dynamic coefficients with a Kalman filter and parameters are estimated by maximum likelihood. The likelihood function is built on the Skewed-Laplace assumption. In order to eliminate the non-differentiability of the likelihood function, it is reformulated into a non-linear optimisation problem with constraints. A relaxed problem is obtained by moving the constraints into the objective, which is then solved numerically with the Augmented Lagrangian Method. In the context of an application to electricity prices, the results show the importance of modelling the time-varying features and the explicit multi-factor representation of the latent coefficients is consistent with an intuitive understanding of the complex price formation processes involving fundamentals, policy instruments and participant conduct.

Authors Paraschiv, Florentina; Bunn, Derek & Westgaard, Sjur
Language English
Subjects other research area
HSG Classification contribution to scientific community
Date 3 March 2016
Publisher SoF - HSG
Place of Publication St. Gallen
Series Name School of Finance Working Paper Series
Volume 2016
Number 7
Number of Pages 28
Official URL http://papers.ssrn.com/sol3/papers.cfm?abstract_id...
Contact Email Address florentina.paraschiv@unisg.ch
Depositing User Geraldine Frei-Böbel
Date Deposited 07 Mar 2016 13:36
Last Modified 18 Jun 2021 00:23
URI: https://www.alexandria.unisg.ch/publications/247892

Download

[img]
Preview
Text
16_07_Paraschiv et al_Estimation and Application of Fully Parametric Multifactor Quantile Regression.pdf

Download (1MB) | Preview

Citation

Paraschiv, Florentina; Bunn, Derek & Westgaard, Sjur: Estimation and Application of Fully Parametric Multifactor Quantile Regression with Dynamic Coefficients. School of Finance Working Paper Series, 2016, 7.

Statistics

https://www.alexandria.unisg.ch/id/eprint/247892
Edit item Edit item
Feedback?