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Gas Storage Valuation: A Comparative Simulation Study

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  • Bastian Felix

    () (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen)

Abstract

The purpose of this paper is the comparative analysis of four natural gas storage valuation approaches. In competitive natural gas markets the optimal valuation and operation of natural gas storages is a key task for natural gas companies operating storages. Within this paper, four spot based valuation approaches are analyzed regarding computational time and accuracy. In particular, explicit and implicit finite differences, multinomial recombining trees, and Least Squares Monte Carlo Simulation are compared. These approaches are applied to the valuation of a gas storage facility considering three different underlying price processes. Major characteristics of historical natural gas prices are: seasonality, mean reversion and jumps. Therefore, we consider a mean reversion process as underlying price process. In a first step, we extend this mean reversion process to a mean reversion jump diffusion process, to account for jumps, occurring in historical gas spot price time series. Moreover, we consider a more general price process accounting for mean reversion as well as seasonal patterns as observed in the historical time series. Besides the analysis of the numerical results, the benefits and drawbacks of the methodologies are discussed.

Suggested Citation

  • Bastian Felix, 2012. "Gas Storage Valuation: A Comparative Simulation Study," EWL Working Papers 1201, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Apr 2014.
  • Handle: RePEc:dui:wpaper:1201
    as

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    References listed on IDEAS

    as
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    5. Byers, Joe Wayne, 2006. "Commodity storage valuation: A linear optimization based on traded instruments," Energy Economics, Elsevier, vol. 28(3), pages 275-287, May.
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    More about this item

    Keywords

    natural gas valuation; limited liquidity;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L95 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Gas Utilities; Pipelines; Water Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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