Hedging strategies in energy markets: The case of electricity retailers

Abstract

As market intermediaries, electricity retailers buy electricity from the wholesale market or self generate for re(sale) on the retail market. Electricity retailers are uncertain about how much electricity their residential customers will use at any time of the day until they actually turn switches on. While demand uncertainty is a common feature of all commodity markets, retailers generally rely on storage to manage demand uncertainty. On electricity markets, retailers are exposed to joint quantity and price risk on an hourly basis given the physical singularity of electricity as a commodity. In the literature on electricity markets, few articles deals on intra-day hedging portfolios to manage joint price and quantity risk whereas electricity markets are hourly markets. The contributions of the article are twofold. First, we define through a VaR and CVaR model optimal portfolios for specific hours (3am, 6am, . . . ,12pm) based on electricity market data from 2001 to 2011 for the French market. We prove that the optimal hedging strategy differs depending on the cluster hour. Secondly, we demonstrate the significantly superior efficiency of intra-day hedging portfolios over daily (therefore weekly and yearly) portfolios. 1clearly show that the losses of an optimal daily portfolio are at least nine times higher than the losses of optimal intra-day portfolios.

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

“…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). There are also papers that look at risk management for retailers through non-market mechanisms.…”

Conditional-Robust-Profit-Based Optimization Model for Electricity Retailers with Shiftable Demand

“…The decision-making with probabilistic methods is commonly based on risk-reward trade-off analysis when the probability distribution function of uncertain data is known [12]. In such a type of analysis, the risk is quantified by a measure of the loss such as the value-at-risk (VaR) [13] or the conditional value-at-risk (CVaR) [14,15]. In [13], the VaR method is used to determine a retailer's optimal electricity portfolio strategy under uncertain market price and demand.…”

“…In such a type of analysis, the risk is quantified by a measure of the loss such as the value-at-risk (VaR) [13] or the conditional value-at-risk (CVaR) [14,15]. In [13], the VaR method is used to determine a retailer's optimal electricity portfolio strategy under uncertain market price and demand. However, the VaR is only coherent when underlying risk factors are normally distributed and suffers from being intractable when it is calculated using scenarios [16].…”

Potential benefits of optimal intra-day electricity hedging for the environment: The perspective of electricity retailers

“…Hedging should be against variations in total costs, which is complex within hourly markets. Consequently, suppliers need to engage in risk management strategies on an intra-day basis given the significantly superior efficiency of intra-day hedging over daily (and therefore weekly, monthly and yearly) hedging (Boroumand et al, 2015). As a consequence of electricity liberalization, a wide variety of hedging instruments have emerged (Geman, 2008;Hull, 2005;Hunt, 2002).…”