Retailers' risk management and vertical arrangements in electricity markets

Boroumand, Raphaël Homayoun; Zachmann, Georg

doi:10.1016/j.enpol.2011.10.041

Cited by 42 publications

(15 citation statements)

References 15 publications

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“…For retailers or load serving entities, though, there is another layer of uncertainty that stems from load fluctuations, usually referred to as volumetric risk or quantity risk. Boroumand and Zachmann (2012) argue that purely contractual portfolios consisting of forward and futures contracts are not efficient risk management devices for hedging the volumetric risk. Several papers in the literature address hedging the joint price and quantity risk faced by load serving entities or retailers (e.g., Boroumand et al 2015, Oum and Oren 2009, 2010, Oum et al 2006).…”

Section: Risk Management In the Electric Power Industrymentioning

confidence: 99%

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Parker

Tan

Kazan

2019

Production and Operations Management

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The electric power industry is undergoing dramatic change driven by rapid technological transformation, concern over climate change, and evolving market structures. As a result, there is a need for new models to help the industry better utilize resources in a time of increasing uncertainty and to help government policy makers better understand the impacts of their regulatory decisions. We provide a structured review of the operations research and management science literatures to describe the current operational and policy issues in the electric power industry, with a particular focus on issues surrounding electricity market design, renewable integration, effects of climate policy on electric power infrastructure, rise of electric powered vehicles, energy storage, and the growing interdependence between natural gas and electric power sectors. We identify the current research frontier and classify the existing research into clusters with respect to managerial issues addressed. We offer a forecast for where the electric power industry is going and describe some important public policy issues. Finally, we highlight research opportunities and discuss how the management science community can contribute by considering the interaction between operational considerations and electric power policy.

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Section: Risk Management In the Electric Power Industrymentioning

confidence: 99%

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Parker

Tan

Kazan

2019

Production and Operations Management

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“…The main objective of liberalising electricity supply was to create competitive decentralised retail markets where asset-light suppliers would compete on price (Boroumand and Zachmann, 2012). In countries which have made serious attempts to liberalise their electricity industries, often the development of retail competition has failed to give the expected results, particularly for residential and commercial consumers.…”

Section: Introductionmentioning

confidence: 99%

Electricity retail competition: the case of the UK

Boroumand

Cartwright

2018

IJGEI

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The objective of liberalising electricity supply was to create competitive retail markets where asset-light suppliers would compete on price. This paper explores the quantitative and dynamic relationship between domestic retail prices and the wholesale price since one would expect a symmetric pattern with a stable and low retail margin. In this article, taking the UK market for analysis, a time-series approach is applied to calculate the extent and timing of pass through between wholesale and retail price variations. The preliminary results indicate that the impact effect and long-run effects from the wholesale to the retail market is quite low.

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“…Value at risk (VaR), initially suggested by Baumol (1963), provides recapitulative and comprehensive advantages in estimating extreme risk in markets. We choose VaR to estimate the price risk of oil markets because it is a good measure of the downside risk (Boroumand and Zachmann 2012). The VaR can be divided into static and dynamic VaR.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of oil price from static and dynamic modelling approaches

Wei

Tang

et al. 2016

Applied Economics

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The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns

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Retailers' risk management and vertical arrangements in electricity markets

Cited by 42 publications

References 15 publications

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Electricity retail competition: the case of the UK

Risk assessment of oil price from static and dynamic modelling approaches

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