Dynamic hedging for the real option management of hydropower production with exchange rate risks

Joakim Dimoski, Stein-Erik Fleten, Nils Löhndorf () and Sveinung Nersten
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Joakim Dimoski: Norwegian University of Science and Technology
Nils Löhndorf: University of Luxembourg
Sveinung Nersten: Norwegian University of Science and Technology

OR Spectrum: Quantitative Approaches in Management, 2023, vol. 45, issue 2, No 6, 525-554

Abstract: Abstract We study the risk management problem of a hydropower producer that hedges risk by trading currency and power futures contracts. The model considers three types of risks: operational risk due to supply uncertainty, profit risk due to power price variability, and exchange rate risk when operation and trading take place in different currencies. We cast the problem as a Markov decision process and propose a sequential solution approach that separates operational management from trading. To solve the problem, we first reduce the high-dimensional Markovian process that models inflows, exchange rates, and future curve dynamics to a scenario lattice and then employ stochastic dual dynamic programming under a risk measure. We find that dynamic hedging leads to significant risk reduction and that it performs better than static hedge ratios that are often used in practice. We also find that a sequential approach leads to better outcomes than an integrated approach across various metrics, which supports the functional separation of operation and hedging that is common practice in most power companies.

Keywords: Risk management; Mathematical optimization; Hydropower; Real options; Dynamic programming (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s00291-023-00709-z

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