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Erik Haugom - One of the best experts on this subject based on the ideXlab platform.
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Determinants of the Forward Premium in the Nord Pool Electricity Market
Energies, 2020Co-Authors: Erik Haugom, Peter Molnár, Magne Ødegaard TysdahlAbstract:Nord Pool is the leading power market in Europe. It has been documented that the forward contracts traded in this market exhibit a significant forward premium, which could be a sign of market inefficiency. Efficient power markets are important, especially when there is a goal to increase the share of the power mix stemming from renewable energy sources. We therefore contribute to the understanding of this topic by examining how the forward premium in the Nord Pool market depend on several economic and physical conditions. We utilise two methods: ordinary least squares and quantile regression. The results show that the reservoir level and the basis (the difference between the forward and spot price) have a significant impact on the forward premium. The realised volatility of futures prices and the implied volatility of the stock market have strong effects on both the conditional lower and upper tails of the forward premium. We also find that, as the market has matured, the forward premium has decreased, indicating an increase in market efficiency.
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the forward premium in the Nord Pool power market
Emerging Markets Finance and Trade, 2018Co-Authors: Erik Haugom, Peter Molnár, Guttorm Andre Hoff, Maria Mortensen, Sjur WestgaardAbstract:This article investigates the forward premium of futures contracts in the Nordic power market for the time period from January 2004 to December 2013. We find that futures prices are biased predictors of the subsequent spot prices and that there is a significant forward premium in the Nord Pool market, particularly during the winter and autumn. We analyze the impact from several factors on the forward premium. The spot price, and the deviation of water inflow from its usual level, positively affect the forward premium. The variance of the spot price also has a positive effect on the forward premium, but only for the contract closest to delivery.
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the forward premium in the Nord Pool power market
Emerging Markets Finance and Trade, 2018Co-Authors: Erik Haugom, Peter Molnár, Guttorm Andre Hoff, Maria Mortensen, Sjur WestgaardAbstract:ABSTRACTThis article investigates the forward premium of futures contracts in the Nordic power market for the time period from January 2004 to December 2013. We find that futures prices are biased ...
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covariance estimation using high frequency data an analysis of Nord Pool electricity forward data
Journal of energy and power engineering, 2012Co-Authors: Gudbrand Lien, Erik Haugom, Sjur Westgaard, Per Bjarte SolibakkeAbstract:The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM (Capital Asset Pricing Model betas), derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution (both distributional properties and temporal dependencies) of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.
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realized volatility and the influence of market measures on predictability analysis of Nord Pool forward electricity data
Energy Economics, 2011Co-Authors: Erik Haugom, Sjur Westgaard, Per Bjarte Solibakke, Gudbrand LienAbstract:This is the first paper to utilize intra-daily high-frequency data and to apply known market measures for the prediction of volatility in the Nord Pool electricity forward market. The work is based on recent methods of separating realized volatility into two components: continuous and jump volatilities. In addition, the link between future price volatility and current observable economic variables is examined. The measures—trading volume, time-to-maturity, asymmetric effect from negative shocks, and intra-week seasonality—are assessed to identify improvements in day-ahead predictions. The model where the total variation is separated into its continuous and jump components is compared with the simpler heterogeneous autoregressive model of realized variation both in- and out-of-sample. The results show a strong degree of persistence in realized volatility, and significant impacts from the mentioned market measures when predicting Nord Pool forward price volatility. Hence, there is a clear preference for models accounting for the systematic impact of market measures to improve volatility assessment for tomorrow. Moreover, separating the total variation into continuous and jump components seems potentially useful when predicting day-ahead volatility.
Sjur Westgaard - One of the best experts on this subject based on the ideXlab platform.
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the forward premium in the Nord Pool power market
Emerging Markets Finance and Trade, 2018Co-Authors: Erik Haugom, Peter Molnár, Guttorm Andre Hoff, Maria Mortensen, Sjur WestgaardAbstract:This article investigates the forward premium of futures contracts in the Nordic power market for the time period from January 2004 to December 2013. We find that futures prices are biased predictors of the subsequent spot prices and that there is a significant forward premium in the Nord Pool market, particularly during the winter and autumn. We analyze the impact from several factors on the forward premium. The spot price, and the deviation of water inflow from its usual level, positively affect the forward premium. The variance of the spot price also has a positive effect on the forward premium, but only for the contract closest to delivery.
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the forward premium in the Nord Pool power market
Emerging Markets Finance and Trade, 2018Co-Authors: Erik Haugom, Peter Molnár, Guttorm Andre Hoff, Maria Mortensen, Sjur WestgaardAbstract:ABSTRACTThis article investigates the forward premium of futures contracts in the Nordic power market for the time period from January 2004 to December 2013. We find that futures prices are biased ...
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On the Estimation of Extreme Values for Risk Assessment and Management: The ACER Method
International journal of business, 2015Co-Authors: Kai Erik Dahlen, Sjur Westgaard, Per Bjarte Solibakke, Arvid NaessAbstract:ABSTRACTIn this paper we use an Average Conditional Exceedance Rate (ACER) method to model the tail of the price change distribution of daily spot prices in the Nordic electricity market, Nord Pool Spot. We use an AR-GARCH model to remove any seasonality, serial correlation and heteroskedasticity from the data before modelling the residuals from this filtering process with the ACER method. We show that using the conditional ACER method for Value-at-Risk forecasts give significant improvement over a standard AR-GARCH model with normal or Student's-t distributed errors. Compared to a conditional generalized Pareto distribution (GPD) fitted with the Peaks-over-Threshold (POT) method, the conditional ACER method produces slightly more accurate quantile forecasts for the highest quantiles.JEL Classifications: C4, Q4Keywords: commodity markets, electric energy, electricity, risk analysis, volatility forecasting.(ProQuest: ... denotes formulae omitted.)I. INTRODUCTIONDuring the recent years we have seen a move from regulated to deregulated electricity markets. Following the deregulation of the British electricity market in the early 1990s, the Norwegian government ruled for a deregulation of the national electricity market in 1991. In 1993 Statnett Marked AS was established, and in 1996 the Nord Pool market was created as a common electricity market for both Norway and Sweden, making it the first market for trading power in the world1. Finland joined the Nord Pool market area in 1998, and western and eastern part of Denmark joined in 1999 and 2000 respectively. In 2002 the electricity and energy derivatives markets were separated into Nord Pool Spot and Nord Pool ASA (now NASDAQ OMX Commodities Europe). Today Nord Pool Spot runs the spot (day-ahead) market as well as the intraday market (Elbas) in the Nordic region and Estonia, and it is the largest market of its kind.The spot market is an auction based day-ahead market where the participants place bids on hourly production and consumption, at a given price and volume, with deadline 12.00CET scheduled for delivery the next day. The system price is then calculated as the price where the supply curve meets the demand curve, without any regard for possible bottlenecks in the transmission grid. To deal with congestion in the transmission grid, the local transmission system operators (TSO) can divide their area into different bidding areas. A congested line from bidding area one to bidding area two can then be dealt with by raising the price in the second bidding area. This is done in order to lower demand and increase the production incentive in the relevant bidding area. Today Norway is divided into 5, Sweden into 4 and Denmark into 2 bidding areas. Finland and Estonia are not divided into any bidding areas.The intraday market functions as a supplement to the spot market to secure balance in the supply and demand for the electricity market, with trading available up to one hour before delivery. With the increasing fraction of unpredictable wind power in the Nordic region (and Germany, also covered by Elbas), leading to more unpredictable supply, the importance of the intraday market is increasing.In the Nordic market region, during a year with average precipitation, almost half of the electricity is produced by hydropower. In Norway hydropower counts for almost 98% of the total electricity production, while in Sweden and Finland the production is a mixture of hydro, nuclear and thermal power. In Denmark thermal power (mainly coal fueled) is the largest source of electricity generation with an increasing installed capacity of wind power.Due to the difficulties and costs of storing electricity (electricity in itself is in practice un-storable, but resources for electricity generation, e.g., water in a reservoir, can be stored) and the observed price inelasticity of consumers (Fezzi and Bunn, 2010), the observed spot prices are highly volatile. …
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covariance estimation using high frequency data an analysis of Nord Pool electricity forward data
Journal of energy and power engineering, 2012Co-Authors: Gudbrand Lien, Erik Haugom, Sjur Westgaard, Per Bjarte SolibakkeAbstract:The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM (Capital Asset Pricing Model betas), derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution (both distributional properties and temporal dependencies) of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.
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realized volatility and the influence of market measures on predictability analysis of Nord Pool forward electricity data
Energy Economics, 2011Co-Authors: Erik Haugom, Sjur Westgaard, Per Bjarte Solibakke, Gudbrand LienAbstract:This is the first paper to utilize intra-daily high-frequency data and to apply known market measures for the prediction of volatility in the Nord Pool electricity forward market. The work is based on recent methods of separating realized volatility into two components: continuous and jump volatilities. In addition, the link between future price volatility and current observable economic variables is examined. The measures—trading volume, time-to-maturity, asymmetric effect from negative shocks, and intra-week seasonality—are assessed to identify improvements in day-ahead predictions. The model where the total variation is separated into its continuous and jump components is compared with the simpler heterogeneous autoregressive model of realized variation both in- and out-of-sample. The results show a strong degree of persistence in realized volatility, and significant impacts from the mentioned market measures when predicting Nord Pool forward price volatility. Hence, there is a clear preference for models accounting for the systematic impact of market measures to improve volatility assessment for tomorrow. Moreover, separating the total variation into continuous and jump components seems potentially useful when predicting day-ahead volatility.
Tarjei Kristiansen - One of the best experts on this subject based on the ideXlab platform.
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Forecasting Nord Pool day-ahead prices with Python
2018Co-Authors: Tarjei KristiansenAbstract:This paper presents a Nord Pool forecast model for hourly day-ahead prices, utilizing the Python software. The model is an autoregressive model based on [1] and the data spans the period from 2004 to 2011. The targets (i.e. dependent variables) are the hourly day-ahead prices for a certain hour during the day while the features (i.e. independent variables) are the prices for the same hour the previous two days and the previous week, the minimum price for the previous day, four weekday dummy variables, including the demand and wind for the actual hour. We test the model in a simple linear regression framework with cross-validation. Next, we utilize regularized regressions including Ridge and Lasso. Finally, we utilize a Keras neural network. The models are evaluated with the mean absolute percentage error (MAPE) criterion, R-square and scatterplots. The results demonstrate that the models perform well and could add value for a market player.
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a time series spot price forecast model for the Nord Pool market
International Journal of Electrical Power & Energy Systems, 2014Co-Authors: Tarjei KristiansenAbstract:Abstract We present three relatively simple spot price forecast models for the Nord Pool market based on historic spot and futures prices including data for inflow and reservoir levels. The models achieve a relatively accurate forecast of the weekly spot prices. The composite regression model achieves a mean absolute percentage error (MAPE) of around 7.5% and under-forecasts the actual spot price by some 1.4 NOK/MW h in the sample period. Out of sample testing achieves a MAPE of around 7.4% including a match of the actual spot price. A myopic model using the previous week’s spot price as a predictor for the next week’s spot price achieves a MAPE of 7.5% and under-forecasts the actual spot price by some 0.9 EUR/MW h. A futures model using the futures price for next week as a predictor for next week’s spot price achieves a MAPE of 5.3% and over-forecast the actual spot price by some 4.3 EUR/MW h.
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Forecasting Nord Pool day-ahead prices with an autoregressive model
Energy Policy, 2012Co-Authors: Tarjei KristiansenAbstract:This paper presents a model to forecast Nord Pool hourly day-ahead prices. The model is based on Weron and Misiorek (2008) but reduced in terms of estimation parameters (from 24 sets to 1) and modified to include Nordic demand and Danish wind power as exogenous variables. We model prices across all hours in the analysis period rather than across each single hour of 24hours. By applying three model variants on Nord Pool data, we achieve a weekly mean absolute percentage error (WMAE) of around 6–7% and an hourly mean absolute percentage error (MAPE) ranging from 8% to 11%. Out of sample results yields a WMAE and an hourly MAPE of around 5%. The models enable analysts and traders to forecast hourly day-ahead prices accurately. Moreover, the models are relatively straightforward and user-friendly to implement. They can be set up in any trading organization.
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the relationship between spot and futures prices in the Nord Pool electricity market
Energy Economics, 2010Co-Authors: Audun Botterud, Tarjei Kristiansen, Marija IlicAbstract:We analyze 11 years of historical spot- and futures prices from the hydro-dominated Nord Pool electricity market. We find that futures prices tend to be higher than spot prices. The average convenience yield is therefore negative, but varies by season and depends on the storage levels in hydro reservoirs. The average realized return on holding a long position in the futures market is also negative. The negative convenience yield and risk premium contrast empirical findings in most other commodity markets. We argue that differences between the supply and demand sides in terms of risk preferences and the ability to take advantage of short-term price variations can contribute to explain the observed relationship between spot- and futures prices. In addition, our analysis shows that the relationship between spot and futures prices is clearly linked to the physical state of the system, such as hydro inflow, reservoir levels, and demand.
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pricing of monthly forward contracts in the Nord Pool market
Energy Policy, 2007Co-Authors: Tarjei KristiansenAbstract:This paper investigates whether the pricing of forward contracts in the Nord Pool market is efficient. Monthly forward contracts were introduced in the Nord Pool market in 2003. Likewise, quarterly contracts that will replace seasonal contracts were introduced in 2004. For a transition period these contracts together with the pre-existing seasonal and yearly contracts constitute the forward market. In an efficient forward market the price of a seasonal forward contract should equal the time-weighted average of the underlying monthly forward contracts. In this paper we use historic forward price information to evaluate whether this relationship holds true and find that there are inefficiencies in the pricing.
Gudbrand Lien - One of the best experts on this subject based on the ideXlab platform.
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covariance estimation using high frequency data an analysis of Nord Pool electricity forward data
Journal of energy and power engineering, 2012Co-Authors: Gudbrand Lien, Erik Haugom, Sjur Westgaard, Per Bjarte SolibakkeAbstract:The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM (Capital Asset Pricing Model betas), derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution (both distributional properties and temporal dependencies) of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.
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realized volatility and the influence of market measures on predictability analysis of Nord Pool forward electricity data
Energy Economics, 2011Co-Authors: Erik Haugom, Sjur Westgaard, Per Bjarte Solibakke, Gudbrand LienAbstract:This is the first paper to utilize intra-daily high-frequency data and to apply known market measures for the prediction of volatility in the Nord Pool electricity forward market. The work is based on recent methods of separating realized volatility into two components: continuous and jump volatilities. In addition, the link between future price volatility and current observable economic variables is examined. The measures—trading volume, time-to-maturity, asymmetric effect from negative shocks, and intra-week seasonality—are assessed to identify improvements in day-ahead predictions. The model where the total variation is separated into its continuous and jump components is compared with the simpler heterogeneous autoregressive model of realized variation both in- and out-of-sample. The results show a strong degree of persistence in realized volatility, and significant impacts from the mentioned market measures when predicting Nord Pool forward price volatility. Hence, there is a clear preference for models accounting for the systematic impact of market measures to improve volatility assessment for tomorrow. Moreover, separating the total variation into continuous and jump components seems potentially useful when predicting day-ahead volatility.
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Modelling day ahead Nord Pool forward price volatility: Realized volatility versus GARCH models
2010 7th International Conference on the European Energy Market, 2010Co-Authors: Erik Haugom, Sjur Westgaard, Per Bjarte Solibakke, Gudbrand LienAbstract:Traditionally, and still within electricity futures/forward markets, daily data has been utilized as the unit of analyses when modelling and making predictions of volatility. However, over the recent past it is argued that better volatility estimates can be obtained by using standard time series techniques on non-parametric volatility measures constructed from high-frequency intradaily returns. Liquidity in financial electricity markets has increased rapidly over the recent years, which make it possible to apply these relatively new methods for measuring market volatility. In this paper high-frequency data and the concept of realized volatility is utilized to make day ahead predictions of Nord Pool forward price volatility. Such short term volatility predictions are especially important for operators and other participants in the electricity sector. We compare the results obtained from standard time-series techniques with the more traditional GARCH-framework which utilizes daily returns. Additionally, we examine whether different approaches of decomposing the total variation into a continuous - and jump measure improves the model fit or not. The paper provides new insights to how the financial electricity market at Nord Pool works, and how we efficiently can model and make predictions of the price movements in this market.
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Covariance estimation using high-frequency data: Analysis of Nord Pool electricity forward data
2010 7th International Conference on the European Energy Market, 2010Co-Authors: Gudbrand Lien, Erik Haugom, Sjur Westgaard, Per Bjarte SolibakkeAbstract:Volatility and correlation modelling is important in order to calculate hedge ratios, value at risk estimates, CAPM betas, derivate pricing and for risk management in general. Historically, these measures have usually been obtained by analyzing daily data. Recently access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange (quarterly and yearly forward contracts), makes it possible to apply new and promising methods for analyzing volatility and correlation. We apply the concept of realized volatility and realized correlation, and as the first study statistically describe the distribution (both distributional properties and temporal dependencies) of electricity forward data from 2005 to 2009. The overall main findings show that the logarithmic realized volatility are approximately normal distributed, while realized correlation seems not. Further, realized volatility and realized correlation has a long memory feature, and there seem to be a high correlation between realized correlation and volatilities. These results are to a large extent consistent with earlier stylized facts studies of other financial and commodity markets.
Henrik Madsen - One of the best experts on this subject based on the ideXlab platform.
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consumption management in the Nord Pool region a stability analysis
Applied Energy, 2015Co-Authors: Erik Lindstrom, Vicke Noren, Henrik MadsenAbstract:Integration of fluctuating renewables like wind and solar power is nowadays a hot topic, but this comes at a cost of decreased stability of the power system. The deterioration often translates into so-called spikes and drops in the electricity spot price, very large (even extreme) deviations from the regular spot price, followed by a reversion to roughly the original level a few days later. We use the spikes and drops as an strong indication that there is an imbalance in the physical power system in this paper. Independent Spike Models (ISM) is a popular class of models for the electricity spot price that uses regime switching, typically having three regimes (base regime, spikes and drops). We fit a such model to Nord Pool spot data to characterize the size and intensity of these deviations, and proceed by augmenting the standard second generation, three factor Independent Spike Model by relating the spike and drop intensity to several factors and find strong statistical support for relating the consumption to the spike and drop intensity. The model is then used to quantitatively evaluate the effects when modifying the consumption in order to mimic how additional renewables are integrated into the power system or conversely the effects when smoothing consumption using 'strategies that can be implemented in smart grids. We use this tool to obtain a direct measure of how much the spike and drop intensity can be reduced by smoothing the consumption and see that even a small increase in the variability of the consumption translates into decreased stability (more spikes and/or drops) of the power system. (c) 2015 Elsevier Ltd. All rights reserved. (Less)
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Consumption management in the Nord Pool region: A stability analysis
Applied Energy, 2015Co-Authors: Erik Lindstrom, Vicke Noren, Henrik MadsenAbstract:Integration of fluctuating renewables like wind and solar power is nowadays a hot topic, but this comes at a cost of decreased stability of the power system. The deterioration often translates into so-called spikes and drops in the electricity spot price, very large (even extreme) deviations from the regular spot price, followed by a reversion to roughly the original level a few days later. We use the spikes and drops as an strong indication that there is an imbalance in the physical power system in this paper.
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Determining reserve requirements in DK1 area of Nord Pool using a probabilistic approach
Energy, 2014Co-Authors: Javier Saez-gallego, Juan M. Morales, Henrik Madsen, Tryggvi JónssonAbstract:Allocation of electricity reserves is the main tool for transmission system operators to guarantee a reliable and safe real-time operation of the power system. Traditionally, a deterministic criterion is used to establish the level of reserve. Alternative criteria are given in this paper by using a probabilistic framework where the reserve requirements are computed based on scenarios of wind power forecast error, load forecast errors and power plant outages. Our approach is first motivated by the increasing wind power penetration in power systems worldwide as well as the current market design of the DK1 area of Nord Pool, where reserves are scheduled prior to the closure of the day-ahead market. The risk of the solution under the resulting reserve schedule is controlled by two measures: the LOLP (Loss-of-Load Probability) and the CVaR (Conditional Value at Risk). Results show that during the case study period, the LOLP methodology produces more costly and less reliable reserve schedules, whereas the solution from the CVaR-method increases the safety of the overall system while decreasing the associated reserve costs, with respect to the method currently used by the Danish TSO (Transmission System Operator).
