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Pricing and Hedging of Long-Dated Commodity Derivatives

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  • Benjamin Tin Chun Cheng

Abstract

Commodity markets have grown substantially over the last decade and significantly contribute to all major financial sectors such as hedge funds, investment funds and insurance. Crude oil derivatives, in particular, are the most actively traded commodity derivative in which the market for long-dated contracts have tripled over the last 10 years. Given the rapid development and increasing importance of long-dated commodity derivatives contracts, models that can accurately evaluate and hedge this type of contracts become of critical importance. Early commodity pricing models proposed in the literature are spot price models with convenience yields either modelled as a function of the spot price or as a correlated stochastic process. These models may have desired features of commodity prices such as mean-reversion and seasonality. However, futures prices from this type of models are endogenously derived. Consequently, futures prices of different maturities are highly correlated. Multi-factor spot price models may remedy this issue. Aiming to model the entire term structure of commodity futures price curve, several authors have proposed commodity pricing models within the Heath, Jarrow & Morton (1992) (hereafter HJM) framework, with different levels of generality. These models, albeit having captured empirically observed features of commodity derivatives, such as unspanned stochastic volatility and hump volatility structures, may not be suitable to price and/or hedge long-dated commodity derivatives as they assume deterministic interest rates. Models featuring stochastic volatility and stochastic interest rates have been studied for equity and FX markets, known as hybrid models, and yet the research in commodity derivatives markets is limited. The main contributions of this thesis include: Pricing of long-dated commodity derivatives with stochastic volatility and stochastic interest rates – Chapter 2. This chapter develops a class of forward price models within the HJM framework for commodity derivatives that incorporates stochastic volatility and stochastic interest rates and allows a correlation structure between the underlying processes. The functional form of the futures price volatility is specified, so that the model admits finite dimensional realisations and retains affine representations; henceforth, quasi-analytical European futures option pricing formulae can be obtained. A sensitivity analysis of the model parameters on pricing long-dated contracts is conducted, and the results are discussed. Empirical pricing performance on long-dated crude oil derivatives – Chapter 3. This chapter conducts an empirical study on the pricing performance of stochastic volatility/stochastic interest-rate models on long-dated crude oil derivatives. Forward price stochastic volatility models for commodity derivatives with deterministic and stochastic interest-rate specifications are considered that allow for a full correlation structure. By using historical crude oil futures and option prices, the proposed models are estimated, and the associated computational issues and results are discussed. Hedging of futures options with stochastic interest rates – Chapter 4. This chapter studies hedging of long-dated futures options with spot price models incorporating stochastic interest rates, a modified version of the Rabinovitch (1989) model. Several hedging schemes are considered including delta hedging and interest-rate hedging. The impact of the model parameters, such as the volatility of the interest rates, the long-term level of the interest rates, and the correlation on the hedging performance is investigated. Hedging long-dated futures options with shorter maturity derivatives is also considered. Empirical hedging performance on long-dated crude oil derivatives – Chapter 5. This chapter conducts an empirical study on hedging long-dated crude oil derivatives with the stochastic volatility/stochastic interest-rate models developed in Chapter 2. Delta hedging, gamma hedging, vega hedging and interest-rate hedging are considered, and the corresponding hedge ratios are computed by using factor hedging. The hedging performance of long-dated crude oil options is assessed with a variety of hedging instruments, such as futures and options with shorter maturities.

Suggested Citation

  • Benjamin Tin Chun Cheng, 2017. "Pricing and Hedging of Long-Dated Commodity Derivatives," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2017.
  • Handle: RePEc:uts:finphd:2-2017
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    References listed on IDEAS

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    1. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Empirical Hedging Performance on Long-Dated Crude Oil Derivatives," Research Paper Series 376, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. K. R. Miltersen, 2003. "Commodity price modelling that matches current observables: a new approach," Quantitative Finance, Taylor & Francis Journals, vol. 3(1), pages 51-58.
    3. Stein, Elias M & Stein, Jeremy C, 1991. "Stock Price Distributions with Stochastic Volatility: An Analytic Approach," Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 727-752.
    4. Yulia V. Veld‐Merkoulova & Frans A. de Roon, 2003. "Hedging long‐term commodity risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(2), pages 109-133, February.
    5. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    6. van Haastrecht, Alexander & Lord, Roger & Pelsser, Antoon & Schrager, David, 2009. "Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 436-448, December.
    7. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Empirical Pricing Performance in Long-Dated Crude Oil Derivatives: Do Models with Stochastic Interest Rates Matter?," Research Paper Series 367, Quantitative Finance Research Centre, University of Technology, Sydney.
    8. John Crosby, 2008. "A multi-factor jump-diffusion model for commodities," Quantitative Finance, Taylor & Francis Journals, vol. 8(2), pages 181-200.
    9. Anders B. Trolle & Eduardo S. Schwartz, 2009. "A General Stochastic Volatility Model for the Pricing of Interest Rate Derivatives," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 2007-2057, May.
    10. Eckhard Platen, 2006. "A Benchmark Approach To Finance," Mathematical Finance, Wiley Blackwell, vol. 16(1), pages 131-151, January.
    11. James D. Hamilton, 2009. "Understanding Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 179-206.
    12. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    13. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
    14. Schrager, David F. & Pelsser, Antoon A.J., 2004. "Pricing Rate of Return Guarantees in Regular Premium Unit Linked Insurance," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 369-398, October.
    15. Lech A. Grzelak & Cornelis W. Oosterlee, 2012. "On Cross-Currency Models with Stochastic Volatility and Correlated Interest Rates," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(1), pages 1-35, February.
    16. Chiarella, Carl & Kang, Boda & Nikitopoulos, Christina Sklibosios & Tô, Thuy-Duong, 2013. "Humps in the volatility structure of the crude oil futures market: New evidence," Energy Economics, Elsevier, vol. 40(C), pages 989-1000.
    17. repec:dau:papers:123456789/607 is not listed on IDEAS
    18. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2015. "Pricing of Long-dated Commodity Derivatives with Stochastic Volatility and Stochastic Interest Rates," Research Paper Series 366, Quantitative Finance Research Centre, University of Technology, Sydney.
    19. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1997. "Estimation of stochastic volatility models with diagnostics," Journal of Econometrics, Elsevier, vol. 81(1), pages 159-192, November.
    20. Jaime Casassus & Pierre Collin‐Dufresne, 2005. "Stochastic Convenience Yield Implied from Commodity Futures and Interest Rates," Journal of Finance, American Finance Association, vol. 60(5), pages 2283-2331, October.
    21. Patrik Karlsson & Kay F Pilz & Erik Schlogl, 2016. "Calibrating Market Model to Commodity and Interest Rate Risk," Research Paper Series 372, Quantitative Finance Research Centre, University of Technology, Sydney.
    22. Rabinovitch, Ramon, 1989. "Pricing Stock and Bond Options when the Default-Free Rate is Stochastic," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(4), pages 447-457, December.
    23. Arora, Vipin & Tanner, Matthew, 2013. "Do oil prices respond to real interest rates?," Energy Economics, Elsevier, vol. 36(C), pages 546-555.
    24. Kevin Fergusson & Eckhard Platen, 2015. "Less Expensive Pricing and Hedging of Long-Dated Equity Index Options When Interest Rates are Stochastic," Research Paper Series 357, Quantitative Finance Research Centre, University of Technology, Sydney.
    25. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    26. Gonzalo Cortazar & Simon Gutierrez & Hector Ortega, 2016. "Empirical Performance of Commodity Pricing Models: When is it Worthwhile to Use a Stochastic Volatility Specification?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 457-487, May.
    27. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Hedging Futures Options with Stochastic Interest Rates," Research Paper Series 375, Quantitative Finance Research Centre, University of Technology, Sydney.
    28. Carl Chiarella & Oh Kang Kwon, 2001. "Forward rate dependent Markovian transformations of the Heath-Jarrow-Morton term structure model," Finance and Stochastics, Springer, vol. 5(2), pages 237-257.
    29. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    30. Turnbull, Stuart M & Milne, Frank, 1991. "A Simple Approach to Interest-Rate Option Pricing," Review of Financial Studies, Society for Financial Studies, vol. 4(1), pages 87-120.
    31. Alexander Van Haastrecht & Antoon Pelsser, 2011. "Accounting for stochastic interest rates, stochastic volatility and a general correlation structure in the valuation of forward starting options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 103-125, February.
    32. Louis O. Scott, 1997. "Pricing Stock Options in a Jump‐Diffusion Model with Stochastic Volatility and Interest Rates: Applications of Fourier Inversion Methods," Mathematical Finance, Wiley Blackwell, vol. 7(4), pages 413-426, October.
    33. Grzelak, Lech & Oosterlee, Kees, 2009. "On The Heston Model with Stochastic Interest Rates," MPRA Paper 20620, University Library of Munich, Germany, revised 18 Jan 2010.
    34. Gibson, Rajna & Schwartz, Eduardo S, 1990. "Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-976, July.
    35. Fusai, Gianluca & Marena, Marina & Roncoroni, Andrea, 2008. "Analytical pricing of discretely monitored Asian-style options: Theory and application to commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2033-2045, October.
    36. Miltersen, Kristian R. & Schwartz, Eduardo S., 1998. "Pricing of Options on Commodity Futures with Stochastic Term Structures of Convenience Yields and Interest Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(1), pages 33-59, March.
    37. Ballotta, Laura & Haberman, Steven, 2003. "Valuation of guaranteed annuity conversion options," Insurance: Mathematics and Economics, Elsevier, vol. 33(1), pages 87-108, August.
    38. Franklin R. Edwards & Michael S. Canter, 1995. "The Collapse Of Metallgesellschaft: Unhedgeable Risks, Poor Hedging Strategy, Or Just Bad Luck?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 8(1), pages 86-105, March.
    39. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    40. Carl Chiarella & Boda Kang & Christina Sklibosios Nikitopoulos & Thuy‐Duong Tô, 2016. "The Return–Volatility Relation in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(2), pages 127-152, February.
    41. Carl Chiarella & Oh Kwon, 2003. "Finite Dimensional Affine Realisations of HJM Models in Terms of Forward Rates and Yields," Review of Derivatives Research, Springer, vol. 6(2), pages 129-155, May.
    42. Cox, John C. & Ingersoll, Jonathan Jr. & Ross, Stephen A., 1981. "The relation between forward prices and futures prices," Journal of Financial Economics, Elsevier, vol. 9(4), pages 321-346, December.
    43. K. F. Pilz & E. Schlögl, 2013. "A hybrid commodity and interest rate market model," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 543-560, March.
    44. Gonzalo Cortazar & Lorenzo Naranjo, 2006. "An N‐factor Gaussian model of oil futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(3), pages 243-268, March.
    45. Helyette Geman, 2005. "Commodities and Commodity Derivatives. Modeling and Pricing for Agriculturals, Metals and Energy," Post-Print halshs-00144182, HAL.
    46. Hilliard, Jimmy E. & Reis, Jorge, 1998. "Valuation of Commodity Futures and Options under Stochastic Convenience Yields, Interest Rates, and Jump Diffusions in the Spot," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(1), pages 61-86, March.
    47. Lech A. Grzelak & Cornelis W. Oosterlee & Sacha Van Weeren, 2012. "Extension of stochastic volatility equity models with the Hull--White interest rate process," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 89-105, July.
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