We consider the problem of designing a financial instrument aimed at mitigating the joint exposure of energy-linked commitments to random price and volume delivery fluctuations. We formulate a functional optimization problem over a set of regular payoff functions: one is written on energy price, while the other is issued over any index exhibiting statistical correlation to volumetric load. On theoretical grounds, we derive closed-form expressions for both payoff structures under suitable conditions about the statistical properties of the underlying variables; we pursue analytical computations in the context of a lognormal market model and deliver explicit formulas for the optimal derivative instruments. On practical grounds, we first develop a comparative analysis of model output through simulation experiments; next, we perform an empirical study based on data quoted at EPEX SPOT power market. Our results suggest that combined price-volume hedging performance improves along with an increase of the correlation between load and index values. This outcome paves the way for a new class of effective strategies for managing volumetric risk upon extreme temperature waves. Link to the article
ID BRIK, R. and RONCORONI, A. (2016). Static Mitigation of Volumetric Risk. Journal of Energy Markets, 9(2), pp. 111-150.