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A novel stochastic modeling framework for coal production and logistics through options pricing analysis

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Listed:
  • Mesias Alfeus

    (University of Stellenbosch)

  • James Collins

    (INSEAD Asia Campus)

Abstract

We propose a novel stochastic modeling framework for coal production and logistics using option pricing theory. The problem of valuing the inherent real optionality a coal producer has when mining and processing thermal coal is modelled as pricing spread options of three assets under the stochastic volatility model. We derive a three-dimensional Fast Fourier Transform (“FFT”) lower bound approximation to value the inherent real optionality and for robustness check, we compare the semi-analytical pricing accuracy with the Monte Carlo simulation. Model parameters are estimated from the historical monthly data, and stochastic volatility parameters are obtained by matching the Kurtosis of the low-ash diff data to the Kurtosis of the stochastic volatility process which is assumed to follow Cox–Ingersoll–Ross (“CIR”) model.

Suggested Citation

  • Mesias Alfeus & James Collins, 2023. "A novel stochastic modeling framework for coal production and logistics through options pricing analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-19, December.
    • Handle: RePEc:spr:fininn:v:9:y:2023:i:1:d:10.1186_s40854-022-00440-8
    DOI: 10.1186/s40854-022-00440-8
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    References listed on IDEAS

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