Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters

Mount, Timothy D.; Ning, Yumei; Cai, Xiaobin

doi:10.1016/j.eneco.2005.09.008

Cited by 194 publications

(110 citation statements)

References 9 publications

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“…However, there was no full convergence at the end of this period, since significant price differentials for peak 3 Many papers analyze the price level itself as electricity has some characteristics that result in a different pricing behavior compared with other products (e.g. Knittel andRoberts, 2005 andMount et al 2006). As long as electricity producers belong to the same market this literature does not interfere with our study.…”

Section: Introductionmentioning

confidence: 93%

Defining European Wholesale Electricity Markets: An 'And/Or' Approach

Dijkgraaf

Janssen

2009

SSRN Journal

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Abstract. An important question in the dynamic European wholesale markets for electricity is whether to define the geographical market at the level of an individual member state or more broadly. We show that if we currently take the traditional approach by considering for each member state whether there is one single other country that provides a substitute for domestic production, the market in each separate member state has still to be considered a separate market. However, if we allow for the possibility that at different moments in time there is another country that provides a substitute for domestic production, then the conclusion should be that certain member states do not constitute a separate geographical market. This is in particular true for Belgium, but also for The Netherlands, France, and to some extent also for Germany and Austria. We call this alternative approach the "and/or" approach.

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Section: Introductionmentioning

confidence: 93%

Defining European Wholesale Electricity Markets: An 'And/Or' Approach

Dijkgraaf

Janssen

2009

SSRN Journal

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“…The usefulness of MRS models for power market applications has already been recognized. However, their effectiveness for forecasting has been vaguely proven, and only lately has this issue been approached in the literature [39,41,51].…”

Section: Markov Regime-switching Modelmentioning

confidence: 99%

“…Several studies have been conducted in order to detail the explanatory variables affecting spot market prices [28,[38][39][40] and price spikes [41]. However, none of these references focus on the appearance of extremely low priced hours in the medium term.…”

Section: Explanatory Variablesmentioning

confidence: 99%

Medium-Term Probabilistic Forecasting of Extremely Low Prices in Electricity Markets: Application to the Spanish Case

2016

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Abstract:One of the most relevant challenges that have arisen in electricity markets during the last few years is the emergence of extremely low prices. Trying to predict these events is crucial for market agents in a competitive environment. This paper proposes a novel methodology to simultaneously accomplish punctual and probabilistic hourly predictions about the appearance of extremely low electricity prices in a medium-term scope. The proposed approach for making real ex ante forecasts consists of a nested compounding of different forecasting techniques, which incorporate Monte Carlo simulation, combined with spatial interpolation techniques. The procedure is based on the statistical identification of the process key drivers. Logistic regression for rare events, decision trees, multilayer perceptrons and a hybrid approach, which combines a market equilibrium model with logistic regression, are used. Moreover, this paper assesses whether periodic models in which parameters switch according to the day of the week can be even more accurate. The proposed techniques are compared to a Markov regime switching model and several naive methods. The proposed methodology empirically demonstrates its effectiveness by achieving promising results on a real case study based on the Spanish electricity market. This approach can provide valuable information for market agents when they face decision making and risk-management processes. Our findings support the additional benefit of using a hybrid approach for deriving more accurate predictions.

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“…A considerable number of models have been proposed in the literature to attempt to capture the dynamics of electricity prices. One class of models includes stochastic models, regime-switching models, cointegration analysis, mean-reverting models and other empirical models (see De Vany and Walls 1999;Higgs and Worthington 2008;Huisman and Mahieu 2003;Huisman and Kilic 2013;Haldrup and Nilsen 2006;Knittel and Roberts 2005;Li and Flynn 2004;Lindstrøm and Regland 2012;Mount et al 2006;Robinson 2000;Robinson and Baniak 2002;Rubin and Babcock 2011;Tashpulatov 2013;Weron 2006Weron , 2008. These models fail to capture the full volatility dynamics of electricity prices as well as the price and volatility interrelationships.…”

Section: The Electricity System Price For the Nordic Spot Electricitymentioning

confidence: 99%

The Nordic/Baltic spot electric power system price: univariate nonlinear impulse-response analysis

Solibakke¹

2018

JEM

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This paper revisits the conditional mean and volatility density characteristics of the system price settled by the Nordic/Baltic spot electric power market . The main aim of this paper is an analysis of the nonlinear impulse-response features (shocks) in the nonstorable commodity market. Initially, we extract all deterministic seasonality and nonstationary trend and scale features from the series. A strictly stationary model reports serial correlation for the mean, and clustering, asymmetry and level effects for the volatility. For the mean, the impulse-response analysis reports linear and symmetric mean reversion for any price movements. For the volatility, small price movements show symmetric and decreasing volatility. In contrast, for larger absolute price movements, the volatility shows a nonlinear increase as well as fast-growing negative asymmetries. The impulse persistence is therefore relatively short. With the entrance of renewables into the energy market, the subperiod 2008-17 reports major systematic changes in the mean, volatility, asymmetry and persistence. In fact, the renewables era has changed the fundamental features of the Nordic/Baltic electricity market.

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Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters

Cited by 194 publications

References 9 publications

Defining European Wholesale Electricity Markets: An 'And/Or' Approach

Defining European Wholesale Electricity Markets: An 'And/Or' Approach

Medium-Term Probabilistic Forecasting of Extremely Low Prices in Electricity Markets: Application to the Spanish Case

The Nordic/Baltic spot electric power system price: univariate nonlinear impulse-response analysis

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