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Valuation of mining projects under dynamic model framework

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Abstract

The proper solution to the optimal investment decision plays an important role in the decision-making process. Compared to the classical net present value rule, the real option approach captures the value of the flexibility embedded in the investment opportunity. In this paper we study relevant dynamic models interpreting the project as well as flexibility value as the option premium, namely investment projects from the mining industry. Specifically, the problem we face is described by systems of partial differential equations of the Black-Scholes type in terms of time and output price, equipped with the terminal condition enforced at time instants resulting from the specific timing and type of the flexibility that such an investment provides. As a result of that, the comprehensive methodological concept, based on the discontinuous Galerkin approach, is proposed to improve the numerical valuation process. The resulting numerical procedure is sufficiently robust to cope with an early exercise constraint as well as a wide range of model parameters. Finally, the performance of the solving procedure is accompanied within the conceptual case study arising from mining industry, supplemented by comments of practical importance.

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References

  • Alexander, C., & Chen, X. (2021). Model risk in real option valuation. Annals of Operations Research, 299, 1025–1056.

    Article  Google Scholar 

  • Andalaft-Chacur, A., Ali, M. M., & Salazar, J. G. (2011). Real options pricing by the finite element method. Computers & Mathematics with Applications, 61(9), 2863–2873.

    Article  Google Scholar 

  • Ballestra, L. V., Pacelli, G., & Radi, D. (2017). Valuing investment projects under interest rate risk: Empirical evidence from european firms. Applied Economics, 49(56), 5662–5672.

    Article  Google Scholar 

  • Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81, 637–659.

    Article  Google Scholar 

  • Boyle, P. P. (1977). Options: A Monte Carlo approach. Journal of Financial Economics, 4(3), 323–338.

    Article  Google Scholar 

  • Brennan, M. J., & Schwartz, E. S. (1977). The valuation of American put options. The Journal of Finance, 32(2), 449–462.

    Article  Google Scholar 

  • Brennan, M. J., & Schwartz, E. S. (1985). Evaluating natural resource investments. Journal of Business, 58(2), 135–157.

    Article  Google Scholar 

  • Broadie, M., & Glasserman, P. (1997). Pricing American-style securities using simulation. Journal of Economic Dynamics and Control, 21(8), 1323–1352.

    Article  Google Scholar 

  • Brockwell, P. J., & Davis, R. A. (1991). Time Series: Theory and Methods. Springer.

    Book  Google Scholar 

  • Ciarlet, P. G. (1979). The finite elements method for elliptic problems. North-Holland.

    Google Scholar 

  • Cortazar, G., & Casassus, J. (1998). Optimal timing of a mine expansion: Implementing a real options model. The Quarterly Review of Economics and Finance, 38(3), 755–769.

    Article  Google Scholar 

  • Cortazar, G., Schwartz, E. S., & Casassus, J. (2001). Optimal exploration investments under price and geological-technical uncertainty: A real options model. R &D Management, 31(2), 181–189.

    Google Scholar 

  • Dimitrakopoulos, R. G., & Sabour, S. A. A. (2007). Evaluating mine plans under uncertainty: Can the real options make a difference? Resources Policy, 32(3), 116–125.

    Article  Google Scholar 

  • Dixit, A. K., & Pindyck, R. S. (1994). Investment Under Uncertainty. Princeton University Press.

    Book  Google Scholar 

  • Dolejší, V. (2013). \(hp\)-dgfem for nonlinear convection-diffusion problems. Mathematics and Computers in Simulation, 87, 87–118.

    Article  Google Scholar 

  • Dolejší, V., & Feistauer, M. (2015). Discontinuous Galerkin method. Analysis and Applications to Compressible Flow. Springer.

    Book  Google Scholar 

  • Duffy, D. J. (2006). Finite difference methods in financial engineering: A partial differential equation approach. John Wiley & Sons.

    Book  Google Scholar 

  • Eymard, R., Gallouët, T., & Herbin, R. (2000). Finite volume methods. Handbook of numerical analysis. Solution of equation in \(R^n\)(Part 3), techniques of scientific computing (Part 3) (Vol. 7, pp. 713–1018). Amsterdam: Elsevier.

  • Hale, J. K. (1969) Ordinary differential equations. Pure & Applied Mathematics 21. Wiley-Interscience, New York

  • Haque, M. A., Topal, E., & Lilford, E. (2014). A numerical study for a mining project using real options valuation under commodity price uncertainty. Resources Policy, 39, 115–123.

    Article  Google Scholar 

  • Haque, M. A., Topal, E., & Lilford, E. (2016). Estimation of mining project values through real option valuation using a combination of hedging strategy and a mean reversion commodity price. Natural Resources Research, 25, 459–471.

    Article  Google Scholar 

  • Harris, M. (1987). Dynamic Economic Analysis. Oxford University Press.

    Google Scholar 

  • Haug, E. G. (2006). The complete guide to option pricing formulas. McGraw-Hill.

    Google Scholar 

  • Hecht, F. (2012). New development in freefem++. Journal of Numerical Mathematics, 20, 251–265.

    Article  Google Scholar 

  • Hozman, J., & Tichý, T. (2016). On the impact of various formulations of the boundary condition within numerical option valuation by DG method. Filomat, 30(15), 4253–4263.

    Article  Google Scholar 

  • Hozman, J., & Tichý, T. (2017). DG method for numerical pricing of multi-asset asian options – the case of options with floating strike. Applications of Mathematics, 62(2), 171–195.

    Article  Google Scholar 

  • Hozman, J., & Tichý, T. (2018). DG framework for pricing European options under one-factor stochastic volatility models. Journal of Computational and Applied Mathematics, 344, 585–600.

    Article  Google Scholar 

  • Hozman, J., & Tichý, T. (2020). The discontinuous Galerkin method for discretely observed Asian options. Mathematical Methods in the Applied Sciences, 43(13), 7726–7746.

    Article  Google Scholar 

  • Hozman, J., & Tichý, T. (2021). Option valuation under the VG process by a DG method. Applications of Mathematics, 66(6), 857–886.

    Article  Google Scholar 

  • Hozman, J., & Tichý, T. (2021). Numerical valuation of the investment project with expansion options based on the PDE approach. In R. Hlavatý (Ed.), MME 2021 (pp. 185–190). Czech University of Life Sciences Prague.

    Google Scholar 

  • Hozman, J., & Tichý, T. (2022). Numerical valuation of the investment project flexibility based on the PDE approach: An option to contract. In H. Vojáčková (Ed.), MME 2022 (pp. 122–128). College of Polytechnics Jihlava: Jihlava, Czech Republic.

    Google Scholar 

  • Ikonen, S., & Toivanen, J. (2004). Operator splitting methods for American option pricing. Applied Mathematics Letters, 17, 809–814.

    Article  Google Scholar 

  • Kufner, A. (1980) Weighted Sobolev Spaces. Teubner-Texte zur Mathematik 31. BSB B. G. Teubner Verlagsgesellschaft, Leipzig

  • Li, N., & Wang, S. (2019). Pricing options on investment project expansions under commodity price uncertainty. Journal of Industrial & Management Optimization, 15(1), 261–273.

    Article  Google Scholar 

  • Li, N., Wang, S., & Zhang, S. (2020). Pricing options on investment project contraction and ownership transfer using a finite volume scheme and an interior penalty method. Journal of Industrial & Management Optimization, 16(3), 1349–1368.

    Article  Google Scholar 

  • Li, N., Wang, S., & Zhang, K. (2022). Price options on investment project expansion under commodity price and volatility uncertainties using a novel finite difference method. Applied Mathematics and Computation, 421, 126937.

    Article  Google Scholar 

  • Martzoukos, S. H. (2000). Real options with random controls and the value of learning. Annals of Operations Research, 99, 305–323.

    Article  Google Scholar 

  • Myers, S. C. (1977). Determinants of corporate borrowing. Journal of Financial Economy, 5(2), 147–175.

    Article  Google Scholar 

  • Myers, S. C., & Turnbull, S. M. (1977). Capital budgeting and the capital asset pricing model: Good news and bad new. Journal of Finance, 32(2), 321–333.

    Article  Google Scholar 

  • Nelson, C. R., & Siegel, A. F. (1987). Parsimonious modeling of yield curves. Journal of Business, 60(4), 473–489.

    Article  Google Scholar 

  • Pascucci, A. (2011). PDE and martingale methods in option pricing. Milan: Springer.

    Book  Google Scholar 

  • Savolainen, J. (2016). Real options in metal mining project valuation: Review of literature. Resources Policy, 50, 49–65.

    Article  Google Scholar 

  • Slade, M. E. (2001). Valuing managerial flexibility: An application of real-option theory to mining investments. Journal of Environmental Economics and Management, 41(2), 193–233.

    Article  Google Scholar 

  • Svensson, L. E. O. (1994) Estimating and interpreting forward interest rates: Sweden 1992-1994. IMF Working Paper No. 94/114

  • Topal, E. (2008). Evaluation of a mining project using discounted cash flow analysis, decision tree analysis, monte carlo simulation and real options using an example. International Journal of Mining and Mineral Engineering, 1(1), 62–76.

    Article  Google Scholar 

  • Topper, J. (2005). Financial engineering with finite elements. John Wiley & Sons.

    Google Scholar 

  • Trigeorgis, L. (2005). Making use of real options simple: An overview and applications in flexible/modular decision making. Journal of Computational and Applied Mathematics, 50(1), 25–53.

    Google Scholar 

  • Wong, H. Y., & Zhao, J. (2008). An artificial boundary method for American option pricing under the CEV model. Journal of Computational and Applied Mathematics, 46(4), 2183–2209.

    Google Scholar 

  • Zvan, R., Forsyth, P. A., & Vetzal, K. R. (1998). Penalty methods for American options with stochastic volatility. Journal of Computational and Applied Mathematics, 91(2), 199–218.

    Article  Google Scholar 

Download references

Acknowledgements

All authors were supported through the Czech Science Foundation (GAČR), Czech Republic under project 22-17028 S. The support is greatly acknowledged.

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Jiří Hozman, Tomáš Tichý and HanaDvořáčková, contributed equally to this work

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Hozman, J., Tichý, T. & Dvořáčková, H. Valuation of mining projects under dynamic model framework. Ann Oper Res (2023). https://doi.org/10.1007/s10479-023-05569-y

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