• Media type: E-Article
  • Title: A novel stochastic modeling framework for coal production and logistics through options pricing analysis
  • Contributor: Alfeus, Mesias [VerfasserIn]; Collins, James [VerfasserIn]
  • imprint: 2023
  • Published in: Financial innovation ; 9(2023), 1, Artikel-ID 54, Seite 1-19
  • Language: English
  • DOI: 10.1186/s40854-022-00440-8
  • ISSN: 2199-4730
  • Identifier:
  • Keywords: Closed-form solution ; Coal ; Fast Fourier transform method ; Monte-Carlo ; Real option analysis ; Stochastic volatility ; Aufsatz in Zeitschrift
  • Origination:
  • Footnote:
  • Description: 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.
  • Access State: Open Access
  • Rights information: Attribution (CC BY)