Logo
Munich Personal RePEc Archive

Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?

Weron, Rafal and Misiorek, Adam (2007): Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts? Published in: Prace Naukowe Akademii Ekonomicznej we Wroclawiu , Vol. 1076, (2007): pp. 472-480.

[img]
Preview
PDF
MPRA_paper_2292.pdf

Download (317kB) | Preview

Abstract

This paper is a continuation of our earlier studies on short-term price forecasting of California electricity prices with time series models. Here we focus on whether models with heavy-tailed innovations perform better in terms of forecasting accuracy than their Gaussian counterparts. Consequently, we limit the range of analyzed models to autoregressive time series approaches that have been found to perform well for pre-crash California power market data. We expand them by allowing for heavy-tailed innovations in the form of α-stable or generalized hyperbolic noise.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.