THE NORMAL INVERSE GAUSSIAN DISTRIBUTION AND SPOT PRICE MODELLING IN ENERGY MARKETS

Fred Espen Benth () and Jūratė Šaltytė-Benth ()
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Fred Espen Benth: Centre of Mathematics for Applications, Department of Mathematics, University of Oslo P.O. Box 1053, Blindern, N–0316 Oslo, Norway;
Jūratė Šaltytė-Benth: Centre of Mathematics for Applications, Department of Mathematics, University of Oslo, P.O. Box 1053, Blindern, N–0316 Oslo, Norway;

International Journal of Theoretical and Applied Finance (IJTAF), 2004, vol. 07, issue 02, 177-192

Abstract: We model spot prices in energy markets with exponential non-Gaussian Ornstein–Uhlenbeck processes. We generalize the classical geometric Brownian motion and Schwartz' mean-reversion model by introducing Lévy processes as the driving noise rather than Brownian motion. Instead of modelling the spot price dynamics as the solution of a stochastic differential equation with jumps, it is advantageous from a statistical point of view to model the price process directly. Imposing the normal inverse Gaussian distribution as the statistical model for the Lévy increments, we obtain a superior fit compared to the Gaussian model when applied to spot price data from the oil and gas markets. We also discuss the problem of pricing forwards and options and outline how to find the market price of risk in an incomplete market.

Keywords: Energy markets; heavy tails; price jumps; normal inverse Gaussian distribution; Lévy processes; incomplete markets; arbitrage-free pricing of derivatives (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (17)

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DOI: 10.1142/S0219024904002360

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