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  • 1.
    Ai Jun, Hou
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School.
    Sandy, Suardi
    A nonparametric GARCH model of crude oil price return volatility2012In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 34, no 2, p. 618-626Article in journal (Refereed)
    Abstract [en]

    The use of parametric GARCH models to characterise crude oil price volatility is widely observed in the empirical literature. In this paper, we consider an alternative approach involving nonparametric method to model and forecast oil price return volatility. Focusing on two crude oil markets, Brent and West Texas Intermediate (WTI), we show that the out-of-sample volatility forecast of the nonparametric GARCH model yields superior performance relative to an extensive class of parametric GARCH models. These results are supported by the use of robust loss functions and the Hansen's (2005) superior predictive ability test. The improvement in forecasting accuracy of oil price return volatility based on the nonparametric GARCH model suggests that this method offers an attractive and viable alternative to the commonly used parametric GARCH models.

  • 2. Heydari, Somayeh
    et al.
    Siddiqui, Afzal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility2010In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 32, no 3, p. 709-725Article in journal (Refereed)
    Abstract [en]

    Energy prices are often highly volatile with unexpected spikes. Capturing these sudden spikes may lead to more informed decision-making in energy investments, such as valuing gas-fired power plants, than ignoring them. In this paper, non-linear regime-switching models and models with mean-reverting stochastic volatility are compared with ordinary linear models. The study is performed using UK electricity and natural gas daily spot prices and suggests that with the aim of valuing a gas-fired power plant with and without operational flexibility, non-linear models with stochastic volatility, specifically for logarithms of electricity prices, provide better out-of-sample forecasts than both linear models and regime-switching models. 

  • 3.
    Lindell, Andreas
    et al.
    Stockholm University, Faculty of Science, Department of Mathematics.
    Raab, Mikael
    Strips of hourly power options - Approximate hedging using average-based forward contracts2009In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 31, no 3, p. 348-355Article in journal (Refereed)
    Abstract [en]

    We study approximate hedging strategies for a contingent claim consisting of a strip of independent hourly power options. The payoff of the contingent claim is a sum of the contributing hourly payoffs. As there is no forward market for specific hours, the fundamental problem is to find a reasonable hedge using exchange-traded forward contracts, e.g. average-based monthly contracts. The main result is a simple dynamic hedging strategy that reduces a significant part of the variance. The idea is to decompose the contingent claim into mathematically tractable components and to use empirical estimations to derive hedging deltas. Two benefits of the method are that the technique easily extends to more complex power derivatives and that only a few parameters need to be estimated. The hedging strategy based on the decomposition technique is compared with dynamic delta hedging strategies based on local minimum variance hedging, using a correlated traded asset.

  • 4. Marzo, Massimiliano
    et al.
    Zagaglia, Paolo
    Stockholm University, Faculty of Social Sciences, Department of Economics.
    A note on the conditional correlation between energy prices: Evidence from future markets2008In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 30, no 5, p. 2454-2458Article in journal (Refereed)
    Abstract [en]

    We model the joint movements of daily returns on one-month future for crude oil, heating oil and natural gas through the multivariate GARCH with dynamic conditional correlations and elliptical distributions introduced by Pelagatti and Rondena [Pelagatti, M.M., Rondena, S., 2007. ""Dynamic Conditional Correlation with Elliptical Distributions"", unpublished manuscript. Universita di Milano - Bicocca, August]. Futures prices of crude and heating oil covary strongly. The conditional correlation between the futures prices of natural gas and crude oil has been rising over the last 5 years. However, this correlation has been low oil average over two thirds of the sample, suggesting that future markets have no established tradition of pricing natural gas as a function of developments on oil markets.

  • 5. Rintamäki, Tuomas
    et al.
    Siddiqui, Afzal S.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. University College, UK.
    Salo, Ahti
    Does renewable energy generation decrease the volatility of electricity prices? An analysis of Denmark and Germany2017In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 62, p. 270-282Article in journal (Refereed)
    Abstract [en]

    Although variable renewable energy (VRE) technologies with zero marginal costs decrease electricity prices, the literature is inconclusive about how the resulting shift in the supply curves impacts price volatility. Because the flexibility to respond to high peak and low off-peak prices is crucial for demand-response applications and may compensate for the losses of conventional generators caused by lower average prices, there is a need to understand how the penetration of VRE affects volatility. In this paper, we build distributed lag models with Danish and German data to estimate the impact of VRE generation on electricity price volatility. We find that in Denmark wind power decreases the daily volatility of prices by flattening the hourly price profile, but in Germany it increases the volatility because it has a stronger impact on off-peak prices. Our analysis suggests that access to flexible generation capacity and wind power generation patterns contribute to these differing impacts. Meanwhile, solar power decreases price volatility in Germany. By contrast, the weekly volatility of prices increases in both areas due to the intermittency of VRE. Thus, policy measures for facilitating the integration of VRE should be tailored to such region-specific patterns.

  • 6.
    Siddiqui, Afzal
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Fleten, Stein-Erik
    How to proceed with competing alternative energy technologies: A real options analysis2010In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 32, no 4, p. 817-830Article in journal (Refereed)
    Abstract [en]

    Concerns about CO2 emissions create incentives for the development and deployment of energy technologies that do not use fossil fuels. Indeed, such technologies would provide tangible benefits in terms of avoided fossil-fuel costs, which are likely to increase as restrictions on CO2 emissions are imposed. However, a number of challenges need to be overcome prior to market deployment, and the commercialisation of alternative energy technologies may require a staged approach given price and technical risk. We analyse how a firm may proceed with staged commercialisation and deployment of competing alternative energy technologies. An unconventional new alternative technology is one possibility, where one could undertake cost-reducing production enhancement measures as an intermediate step prior to deployment. By contrast, the firm could choose to deploy a smaller-scale existing renewable energy technology, and, using the real options framework, we compare the two projects to provide managerial implications on how one might proceed.

  • 7.
    Takama, Takeshi
    et al.
    Stockholm University, Stockholm Resilience Centre, Stockholm Environment Institute.
    Tsephel, Stanzin
    Johnson, Francis X.
    Stockholm University, Stockholm Resilience Centre, Stockholm Environment Institute.
    Evaluating the relative strength of product-specific factors in fuel switching and stove choice decisions in Ethiopia: A discrete choice model of household preferences for clean cooking alternatives2012In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 34, no 6, p. 1763-1773Article in journal (Refereed)
    Abstract [en]

    Switching from conventional stoves to modern clean, safe, and efficient stoves will improve health and social welfare for the 2.7 billion people worldwide that lack reliable access to modern energy services. In this paper, we critically review some key theoretical dimensions of household consumer behaviour in switching from traditional biomass cooking stoves to modern efficient stoves and fuels. We then describe the results of empirical research investigating the determinants of stove choice, focusing on the relative strength of product-specific factors across three wealth groups. A stated preference survey and discrete choice model were developed to understand household decision-making associated with cooking stove choice in Addis Ababa, Ethiopia. The study found that, with the exception of price and usage cost factors for the high wealth group, the product-specific factors that were investigated significantly affect stove and fuel choices. The relative strength of factors was assessed in terms of Marginal Willingness to Pay and provides some evidence that consumer preference for higher quality fuels and stoves tends to increase with increasing wealth.

  • 8. Višković, Verena
    et al.
    Chen, Yihsu
    Siddiqui, Afzal S.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. University College London, United Kingdom; HEC Montréal, Canada.
    Implications of the EU Emissions Trading System for the South-East Europe Regional Electricity Market2017In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 65, p. 251-261Article in journal (Refereed)
    Abstract [en]

    As part of its climate policy, the European Union (EU) aims to reduce greenhouse gas (GHG) emissions levels by 20% by the year 2020 compared to 1990 levels. Although the EU is projected to reach this goal, its achievement of objectives under its Emissions Trading System (ETS) may be delayed by carbon leakage, which is defined as a situation in which the reduction in emissions in the ETS region is partially offset by an increase in carbon emissions in the non-ETS regions. We study the interaction between emissions and hydropower availability in order to estimate the magnitude of carbon leakage in the South-East Europe Regional Electricity Market (SEE-REM) via a bottom-up partial equilibrium framework. We find that 6.3% to 40.5% of the emissions reduction achieved in the ETS part of SEE-REM could be leaked to the non-ETS part depending on the price of allowances. Somewhat surprisingly, greater hydropower availability may increase emissions in the ETS part of SEE-REM. However, carbon leakage might be limited by demand response to higher electricity prices in the non-ETS area of SEE-REM. Such carbon leakage can affect both the competitiveness of producers in ETS member countries on the periphery of the ETS and the achievement of EU targets for CO2 emissions reduction. Meanwhile, higher non-ETS electricity prices imply that the current policy can have undesirable outcomes for consumers in non-ETS countries, while non-ETS producers would experience an increase in their profits due to higher power prices as well as exports. The presence of carbon leakage in SEE-REM suggests that current EU policy might become more effective when it is expanded to cover more countries in the future.

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