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A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method

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  • Brix, Anne Floor
  • Lunde, Asger
  • Wei, Wei

Abstract

We investigate a large set of energy models that account for the stylized properties in energy prices, especially stochastic volatility and spikes. The models under consideration belong to the class of factor models while our full model features a two-factor price process and a two-component stochastic volatility process. The first factor in the price process captures the normal variations; the second accounts for spikes. The two-component volatility allows for a flexible autocorrelation structure. Instead of using various filtering techniques for splitting the factors, as often found in the literature, we estimate the model in one step using the particle MCMC method. We fit the models to both the spot market and the forward market for UK natural gas. We find that the inclusion of stochastic volatility is crucial for the statistical fit of spot prices whereas the spikes are important for explaining forward prices.

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  • Brix, Anne Floor & Lunde, Asger & Wei, Wei, 2018. "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method," Energy Economics, Elsevier, vol. 72(C), pages 560-582.
    • Handle: RePEc:eee:eneeco:v:72:y:2018:i:c:p:560-582
    DOI: 10.1016/j.eneco.2018.03.037
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    References listed on IDEAS

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    Cited by:

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    More about this item

    Keywords

    Energy prices; Forward prices; Multi-factor model; Stochastic volatility; Spikes;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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