Pricing of Swing Options in a Mean Reverting Model with Jumps

Mats Kjaer

34 citations0/0 files storedApplied Mathematical Finance

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Stochastic processes and financial applications Electric Power System Optimization Energy Load and Power Forecasting

Abstract

We investigate the pricing of swing options in a model where the logarithm of the spot price is the sum of a deterministic seasonal trend and an Ornstein–Uhlenbeck process driven by a jump diffusion. First we calibrate the model to Nord Pool electricity market data. Second, the existence of an optimal exercise strategy is proved, and we present a numerical algorithm for computation of the swing option prices. It involves dynamic programming and the solution of multiple parabolic partial integro‐differential equations by finite differences. Numerical results show that adding jumps to a diffusion may result in 2–35% higher swing option prices, depending on the moneyness and timing flexibility of the option.

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References

1993A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options 1976Option pricing when underlying stock returns are discontinuous 2003Financial Modelling with Jump Processes 2008A General Version of the Fundamental Theorem of Asset Pricing (1994)1994A general version of the fundamental theorem of asset pricing 1990Stochastic Integration and Differential Equations 2003Affine processes and applications in finance 2002Electricity Prices and Power Derivatives: Evidence from the Nordic Power Exchange

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2020Revenue Risk Allocation Mechanism in Public-Private Partnership Projects: Swing Option Approach 2021A survey of electricity spot and futures price models for risk management applications 2016Modelling electricity prices: a time change approach

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