• Medientyp: E-Artikel
  • Titel: A novel stochastic modeling framework for coal production and logistics through options pricing analysis
  • Beteiligte: Alfeus, Mesias; Collins, James
  • Erschienen: Springer Science and Business Media LLC, 2023
  • Erschienen in: Financial Innovation, 9 (2023) 1
  • Sprache: Englisch
  • DOI: 10.1186/s40854-022-00440-8
  • ISSN: 2199-4730
  • Schlagwörter: Management of Technology and Innovation ; Finance
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  • Beschreibung: AbstractWe 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.
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