Modeling the distribution of day-ahead electricity returns: a comparison

Sapio, Sandro

doi:10.1080/14697688.2010.502540

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…This confirms H2. The presented analysis, inspired by [41,42] when it comes to modelling the distribution of day-ahead electricity returns, acknowledges the complexity and the unique characteristics of electricity price dynamics in European day-ahead markets. The standard deviation is a widely recognized measure of volatility, capturing the average degree of variation or dispersion of a set of values from the mean.…”

Section: Resultsmentioning

confidence: 99%

“…In the literature, price volatility has been measured quite often as the standard deviation of logarithmic or arithmetic returns [41,42]. One extreme spike, either upward or downward, could, however, completely dominate the standard deviation.…”

Section: Methodsmentioning

confidence: 99%

“…One extreme spike, either upward or downward, could, however, completely dominate the standard deviation. For instance, there may be a significant impact on the first six and last two hours if only one day is removed [42]. Some authors employed the historical volatility concept to analyze the volatility of electricity market prices [43][44][45].…”

Section: Methodsmentioning

confidence: 99%

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The Volatility Dynamics of Prices in the European Power Markets during the COVID-19 Pandemic Period

Stanković,

Rajic,

Božić

et al. 2024

Sustainability

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Surging electricity demand, its limited supply, and the pandemic crisis are just some of the key factors that resulted in changes in electricity prices on the power exchanges. This topic brings about a notable economic influence on both producers and consumers. The main purpose of this paper is to explore power price volatility during the four-year period from 1 January 2018 to 31 December 2021, in 28 power exchanges in Europe, measured using daily velocity data. In addition, based on the fixed and chain base index numbers, as well as their relative merits, this paper was designed to measure the gap and convergence in trends. Considering that the price volatility varies depending on the observation period, this paper performs a comparative analysis of electricity price volatility on a daily, monthly, quarterly, and annual level for all examined countries. The obtained results indicate that electricity price volatility is higher on a daily basis. Related to this, convergent trends are demonstrated on all 28 observed markets, and there is a growing trend of hourly spot prices in the analyzed four-year period. The results of this paper also confirm a higher power price volatility during the pandemic period in 2020 and 2021 compared to the prepandemic period during 2018 and 2019.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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The Volatility Dynamics of Prices in the European Power Markets during the COVID-19 Pandemic Period

Stanković,

Rajic,

Božić

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…In non-storage commodity markets, such as electricity, trading mechanisms must continually provide market clearing. Day-ahead prices are determined by using a single price auction so that all electricity is sold and bought at the market price [36]. Volatility processes are key elements in risk management, as they present price fluctuations over a period, and when evaluated properly they can be used in portfolio optimization and asset allocation [37].…”

Section: Literature Reviewmentioning

confidence: 99%

Power Exchange Prices: Comparison of Volatility in European Markets

Bozic

Dobromirov

Arsić³

et al. 2020

Energies

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Power exchanges in Europe have been operating since the 1990s, while in the region of Southeast Europe (SEE) they are only a few years old. Volatility is considered to be one of the indicators that define the level of market development. In this paper, the authors examine 15 power markets in Europe with the novelty of special attention dedicated to the SEE markets, in terms of their volatility. The aim of this paper is to investigate volatility on SEE markets, and their correlation with developed European markets. Power price volatility is measured by price velocity concepts, the daily velocity based on daily/monthly/quarterly/yearly and overall average power prices. The outcomes reveal that power price volatility is higher in new SEE markets than in more mature European markets. The least volatile market is the Greek pool, followed by Switzerland and Austria. The Bulgarian market is the most volatile, followed by that of Romania, and these markets are nearly twice as volatile as the ones previously mentioned. A correlation matrix is carried out and confirms positive correlation between all markets in terms of their average prices. However, a correlation matrix of measured volatilities depicts a negative correlation, in some cases, between SEE and Central European (CE) markets.

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“…The key variable on which we focused, in order to investigate the effects of the CPM, is the volatility of electricity price (Sapio, 2012). This choice is motivated by the fact that its behavior, which is usually characterized by a periodic pattern and regular low-volatility periods interspersed by high-volatility clusters, showed a decrease in magnitude as well as a persistence of these clusters when the CPM was in force.…”

Section: Our Contributionmentioning

confidence: 99%

Effects of Carbon Tax on Electricity Price Volatility: Empirical Evidences from the Australian Market

Comincioli

Vergalli

2020

SSRN Journal

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Among the wide variety of policy options adopted worldwide to control carbon emissions, one of the most environmentally effective and economically efficient is represented by carbon tax, that aims to recoup the damage arising from polluting production processes. In this paper, we focus on the Australian Carbon Pricing Mechanism (CPM) and on the effects that its introduction had on the electricity market. The most relevant effect is the reduction of the level of electricity price's volatility. This effect has been investigated after having removed, from electricity data time series, the periodic behavior, through a multiple linear regression. Then, to study volatility dynamics, we fit a two-states Markov-switching model to represent a high-volatility and a low-volatility states of the world. This model highlighted that in both states the level of volatility is lower and that the persistence of the second state is increased by the presence of the CPM. This result is particularly important in investment evaluation: knowing the different dynamics of price volatility in presence of a carbon tax or not, can provide crucial information in investment decision and its timing.

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Modeling the distribution of day-ahead electricity returns: a comparison

Cited by 6 publications

References 21 publications

The Volatility Dynamics of Prices in the European Power Markets during the COVID-19 Pandemic Period

The Volatility Dynamics of Prices in the European Power Markets during the COVID-19 Pandemic Period

Power Exchange Prices: Comparison of Volatility in European Markets

Effects of Carbon Tax on Electricity Price Volatility: Empirical Evidences from the Australian Market

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