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Electricity suppliers typically charge their customers a set price for power, but the cost to the companies for the electrical energy they sell can vary dramatically. When the demand spikes during a heat wave, for example, suppliers may need to buy power from electricity wholesalers at much higher prices than usual to keep the power flowing. 

To deal with the challenges posed by fluctuating consumption and energy prices, risk managers at the companies develop hedging strategies aimed at managing risk and generating optimal financial returns. A new tool developed at Illinois Institute of Technology aims to help them improve their strategies.

In a research paper published in the Journal of Energy Markets, Associate Professor of Finance Sang Baum Kang from Illinois Tech’s Stuart School of Business and his co-authors present a framework they have created that enables risk managers in the energy sector to more comprehensively assess the cost-efficiency of a complex hedging deal. 

Their model, the economic value of the incremental expected shortfall (EVIES), is detailed in the paper titled “.” Kang conducted the research and wrote the paper in collaboration with Stuart alumna Jialin Zhao (Ph.D. MSC ’17) and Michael K. Ong, formerly a professor of finance at Stuart.

According to Kang, Zhao, and Ong, the EVIES framework can be used to solve a range of customized risk-management purposes and, compared to the current standard models that electricity suppliers use, provides more precision for practitioners in devising hedging strategies that will achieve specific risk-management targets. EVIES is also valuable in evaluating complex hedging instruments such as electricity quanto contracts, which are useful for mitigating price-volume joint risk but are expensive.

“EVIES summarizes both the economic benefits of financial risk reduction and the costs of hedging into one number,” the authors write in the paper. “Meanwhile, in estimating the net economic impacts of hedging strategies, EVIES accounts for a firm’s customized financial conditions, such as the weighted average cost of capital (WACC) and the corporate income tax rate. These input parameters are readily observable to real-world financial risk managers, and our proposed measure is thus straightforward to implement and interpret.” 

“If an energy firm has an integrated trading and risk management system, it would be relatively easy to calculate and use the EVIES,” Kang says.

According to Kang, the initial idea for this research grew out of his experience working in industry for nearly a decade, where he rose to become director of structure and pricing at PacifiCorp Energy, with responsibility for asset valuation, derivative pricing, and hedging transaction evaluation. 

After completing his doctorate and joining the faculty at Stuart, Kang shared his ideas for this project with Zhao, who at the time was a student in the school’s Ph.D. program in management science. With Kang as her adviser, Zhao developed the research into an academic paper and they have continued to collaborate on research projects. She is now an assistant professor of quantitative management with Greehey School of Business at St. Mary’s University.

Photo: Illinois Institute of Technology Associate Professor of Finance Sang Baum Kang