Modelling Electricity Prices: International Evidence*

AuthorJ. Ignacio Peña,Pablo Villaplana,Alvaro Escribano
Date01 October 2011
Publication Date01 October 2011
©Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2011. Published by Blackwell Publishing Ltd,
9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.
doi: 10.1111/j.1468-0084.2010.00632.x
Modelling Electricity Prices: International EvidenceÅ
Alvaro Escribano, J. Ignacio Pe˜
na‡ and Pablo Villaplana§
Department of Economics, Universidad Carlos III de Madrid, 28903 Getafe, Madrid, Spain
Department of Business Administration, Universidad Carlos III de Madrid, 28903 Getafe,
Madrid, Spain (e-mail:
§Comisión Nacional de Energía, C/Alcalá, 47, 28014 Madrid, Spain (e-mail:
This article analyses the evolution of electricity prices in deregulated markets. Wepresent a
general class of models that simultaneously takes into account several factors: seasonality,
mean reversion, GARCH behaviour and time-dependent jumps. The models are applied
to daily equilibrium spot prices of eight electricity markets. Eight different nested models
were estimated to compare the relative importance of each factor in each of the eight
markets. We nd strong evidence that electricity equilibrium prices are mean-reverting,
with volatility clustering (GARCH) and with jumps of time-dependent intensity, even after
adjusting for seasonality.
I. Introduction
Until early 90s the electricity sector has been a vertically integrated industry, where
regulators xed prices as a function of generation, transmission and distribution costs
and therefore there was little uncertainty in prices. In last years electricity markets in many
countries have experienced a deregulation process, with the aim of introducing competition
in generation and supply activities (not in transmission and distribution since they are
considered natural monopolies). One of the main consequences of this reform is that
prices are determined by the interaction between supply (generators) and demand (sup-
pliers, who are agents that buy energy and sell it to the consumers) in what is usually
called a pool. In this context generators compete to sell electricity in the market pool while
the suppliers to consumers purchase electricity from the pool at equilibrium prices set
ÅThe authors are grateful to the insightful comments received on the rst versions of this article from theAssociate
Editor and from two anonymous referees. We also thankAngel Leon, Craig Pirrong, Cristopher R. Knittel, Michael
Roberts, Vicente Meneu and the participants at the I Workshop in Electricity Derivatives (Valencia, Spain), IX
Foro Finanzas (Pamplona, Spain), EFA(Berlin), EARIE (Madrid), I Commodities Modelling Workshop (Birkbeck,
London). Escribano acknowledges nancial support provided by MICIN grant ECO2009-08308 and by the Bank of
Spain Excellence Program and J.I. Pe˜naby MCIN grant ECO2009-12551. P. Villaplana also acknowledges nancial
support provided by Energy Economics Laboratory, of the Universidad Carlos III de Madrid and Fundacion Ramon
Areces. The views expressed in this article are those of the authors, and not those of the Comisi´on Nacional de
JEL Classication numbers: C22, L9, L94, G10.
Modelling electricity prices 623
by the intersection of aggregated demand and supply on an hourly (or half-hourly) basis.
Due to the idiosyncrasies of wholesale electricity markets, like the instantaneous nature
(non-storability) of the commodity, these new deregulated prices have been characterized
in all the markets by having an extremely high volatility, and their forecasting, even at
the day-ahead horizon, remains an important challenge, see Karakatsani and Bunn (2008)
and Weron (2006). In fact, one of the principal features of electricity prices are the abrupt
and partially unanticipated extreme changes in spot (day ahead) prices known as spikes or
jumps, the modelling of this characteristic is one of the main goals and contributions of
this article.
The peculiar characteristics of electricity prices, and in particular the existence of spikes,
implies the need to develop specic electricity price models for the pricing of physical and
nancial contracts, and for the valuation of real assets.
The characterization and understanding of the behaviour of electricity prices is a
necessary task and is the basis for the valuation and risk management of real assets and
nancial claims on the commodity. Some initial recent contributions are Johnson and Barz
(1999), Bhanot (2000), Lucia and Schwartz (2002), Knittel and Roberts (2005), Geman
and Roncoroni (2006) and De Jong (2006).
We extend this literature by proposing and estimating a general and exible model
for day-ahead (spot) prices and applying it to a comprehensive set of markets, Argentina,
Australia (Victoria), Canada (Alberta), New Zealand (Hayward), Netherlands (Amsterdam
Power Exchange), Scandinavia (NordPool), Spain, and U.S. (Pennsylvania – New Jersey
– Maryland, PJM hereafter). Because market structures and price dynamics differ widely
across regions, enough different markets need to be tested, to analyse if a model provides
enough exibility to cope with different price dynamics.
This will allow us to compare the different behaviour observed in deregulated mar-
kets and quantify the role of different characteristics (importance of seasonality, mean-
reversion, volatility and/or jumps) in each individual market. Our goal is to propose a
general (benchmark) model that encompasses the main features present in all markets.
The main innovation of this article is the estimation of a general and exible model
to a comprehensive set of markets, taking into account the interaction between jumps
and GARCH behaviour, and among jumps, GARCH and mean reversion. Our results
stress the importance of including those three elements simultaneously to isolate the
main features of the behaviour of electricity prices in deregulated markets. Given the
importance of understanding and modelling price spikes, the model we propose expli-
citly deals with price spikes capturing its dynamics trough supply and demand related
variables. Although we focus on equilibrium prices from electricity markets, this model-
ling strategy could also be applied to other commodity prices like for instance, natural
The article is organized as follows. Section II describes the main characteristic factors
of electricity prices and discusses some related literature. Section III presents the model
and the econometric methodology. Section IV describes our data sets and presents some
descriptive statistics and unit root tests. Section V presents the empirical results from
the estimated models. Section VI presents the out-of-sample analysis. Finally, section VII
includes some conclusions and provides some insights for future risk management research
based on our empirical ndings.
©Blackwell Publishing Ltd and the Department of Economics, University of Oxford 2011

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT