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Electricity futures price models: Calibration and forecasting

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  • Islyaev, Suren
  • Date, Paresh

Abstract

A new one factor model with a random volatility parameter is presented in this paper for pricing of electricity futures contracts. It is shown that the model is more tractable than multi-factor jump diffusion models and yields an approximate closed-form pricing formula for the electricity futures prices. On real market data, it is shown that the performance of the new model compares favourably with two existing models in the literature, viz. a two factor jump diffusion model and its jump free version, i.e., a two factor linear Gaussian model, in terms of ability to predict one day ahead futures prices. Further, a multi-stage procedure is suggested and implemented for calibration of the two factor jump diffusion model, which alleviates the difficulty in calibration due to a large number of parameters and pricing formulae which involve numerical evaluation of integrals. We demonstrate the utility of our new model, as well as the utility of the calibration procedure for the existing two factor jump diffusion model, by model calibration and price forecasting experiments on three different futures price data sets from Nord pool electricity data. For the jump diffusion model, we also investigate empirically whether it performs better in terms of futures price prediction than a corresponding, jump-free linear Gaussian model. Finally, we investigate whether an explicit calibration of jump risk premium in the jump diffusion model adds value to the quality of futures price prediction. Our experiments do not yield any evidence that modelling jumps leads to a better price prediction in electricity markets.

Suggested Citation

  • Islyaev, Suren & Date, Paresh, 2015. "Electricity futures price models: Calibration and forecasting," European Journal of Operational Research, Elsevier, vol. 247(1), pages 144-154.
  • Handle: RePEc:eee:ejores:v:247:y:2015:i:1:p:144-154
    DOI: 10.1016/j.ejor.2015.05.063
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    References listed on IDEAS

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    Cited by:

    1. Maria Cristina Recchioni & Yu Sun & Gabriele Tedeschi, 2016. "Can negative interest rates really affect option pricing? Empirical evidence from an explicitly solvable stochastic volatility model," Working Papers 2016/23, Economics Department, Universitat Jaume I, Castellón (Spain).
    2. repec:eee:rensus:v:81:y:2018:i:p2:p:2870-2878 is not listed on IDEAS
    3. Recchioni, M.C. & Sun, Y., 2016. "An explicitly solvable Heston model with stochastic interest rate," European Journal of Operational Research, Elsevier, vol. 249(1), pages 359-377.
    4. Spodniak, Petr & Bertsch, Valentin, 2017. "Determinants of power spreads in electricity futures markets: A multinational analysis," Papers WP580, Economic and Social Research Institute (ESRI).
    5. repec:eee:ejores:v:261:y:2017:i:2:p:715-734 is not listed on IDEAS

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