Cookies?
Library Header Image
LSE Research Online LSE Library Services

Modelling electricity day-ahead prices by multivariate Lévy semistationary processes

Veraart, Almut E. D. and Veraart, Luitgard A. M. ORCID: 0000-0003-1183-2227 (2014) Modelling electricity day-ahead prices by multivariate Lévy semistationary processes. In: Benth, Fred Espen, Kholodnyi, Valery A. and Laurence, Peter, (eds.) Quantitative Energy Finance. Springer Berlin / Heidelberg, New York, USA, pp. 157-188. ISBN 9781461472476

[img] Text - Accepted Version
Registered users only

Download (2MB)

Abstract

This paper presents a new modelling framework for day-ahead electricity prices based on multivariate Levy semistationary (MLSS) processes. Day-ahead prices specify the prices for electricity delivered over certain time windows on the next day and are determined in a daily auction. Since there are several delivery periods per day, we use a multivariate model to describe the different day-ahead prices for the different delivery periods on the next day. We extend the work by Barndorff-Nielsen et al. (2010) on univariate Levy semistationary processes to a multivariate setting and discuss the probabilistic properties of the new class of stochastic processes. Furthermore, we provide a detailed empirical study using data from the European Energy Exchange (EEX) and give new insights into the intra-daily correlation structure of electricity day-ahead prices in the EEX market. The flexible structure of MLSS processes is able to reproduce the stylized facts of such data rather well. Furthermore, these processes can be used to model negative prices in electricity markets which started to occur recently and cannot be described by many classical models.

Item Type: Book Section
Official URL: http://www.springer.com/gb/
Additional Information: © 2014 Springer Science+Business Media New York
Divisions: Mathematics
Subjects: H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HF Commerce
Q Science > QA Mathematics
Date Deposited: 29 Sep 2017 16:06
Last Modified: 08 Dec 2024 20:09
URI: http://eprints.lse.ac.uk/id/eprint/84377

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics