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Using Affine Jump Diffusion Models for Modelling and Pricing Electricity Derivatives

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  • N. K. Nomikos
  • O. Soldatos

Abstract

A seasonal affine jump diffusion spike model with regime switching in the long-run equilibrium level is applied to model spot and forward prices in the Scandinavian power market. The spike part of the model incorporates different coefficients of mean reversion in the spike and normal variables and thus improves the spot-forward relationship, particularly at time periods when spikes occur. The regime switching part of the model contains two separate regimes to distinguish between periods of high and low water levels in the reservoirs, reflecting the availability of hydropower in the market. The performance of the models is compared with that of other models proposed in the literature in terms of fitting the observed term structure, as well as by generating simulated price paths that have the same statistical properties as the actual prices observed in the market. In particular, the model performs well in terms of capturing the spikes and explaining their fast mean reversion as well as in terms of reflecting the seasonal volatility observed in the market. These issues are very important for the pricing and hedging of derivative instruments.

Suggested Citation

  • N. K. Nomikos & O. Soldatos, 2008. "Using Affine Jump Diffusion Models for Modelling and Pricing Electricity Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(1), pages 41-71.
    • Handle: RePEc:taf:apmtfi:v:15:y:2008:i:1:p:41-71
    DOI: 10.1080/13504860701427362
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    Citations

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    Cited by:

    1. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    2. Fred Espen Benth, 2021. "Pricing of Commodity and Energy Derivatives for Polynomial Processes," Mathematics, MDPI, vol. 9(2), pages 1-30, January.
    3. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool," Energy Policy, Elsevier, vol. 38(10), pages 5671-5683, October.
    4. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market," Energy Economics, Elsevier, vol. 32(2), pages 302-312, March.
    5. Nomikos, Nikos & Andriosopoulos, Kostas, 2012. "Modelling energy spot prices: Empirical evidence from NYMEX," Energy Economics, Elsevier, vol. 34(4), pages 1153-1169.
    6. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    7. Mehrdoust, Farshid & Noorani, Idin & Kanniainen, Juho, 2024. "Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 215(C), pages 228-269.
    8. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.

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    More about this item

    Keywords

    Regime-switching spike model; affine jump diffusion models; electricity derivatives; seasonal risk premium; JEL Classification: G13; G12 and G33;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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