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Problema de calibración de mercado y estructura implícita del modelo de bonos de Black-Cox = Market Calibration Problem and the Implied Structure of the Black-Cox Bond Model

Author

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  • Sukhomlin, Nikolay

    (Departamento de Física, Universidad Autónoma de Santo Domingo (República Dominicana), CEREGMIA, Université des Antilles et de la Guyane (France))

  • Santana Jiménez, Lisette Josefina

    (Grupo de Investigación en Econofísica, Universidad Autónoma de Santo Domingo (República Dominicana))

Abstract

El principal resultado de este artículo consiste en la resolución del problema inverso del modelo de Black-Cox (1976), usando el método propuesto por Sukhomlin (2007). Se parte del enfoque retrógrado (backward) para obtener una expresión exacta de la volatilidad implícita en función de parámetros cuantificables con datos de mercado y de variables conocidas. Se descubre la existencia de dos valores de la volatilidad para un activo subyacente en el modelo referido, lo que indica que las asunciones tradicionales no lo definen de manera unívoca. Se encuentra la causa de que el modelo de Black-Cox contenga dos valores de la volatilidad. Además, se lleva a cabo una simulación, afín de verificar, numéricamente, que la expresión obtenida para la volatilidad es la inversión de la fórmula que representa la probabilidad de que la firma no alcance un nivel de insolvencia antes del tiempo de madurez de la deuda. Finalmente, se resuelve el problema de calibración de mercado desde el punto de vista directo (forward), encontrándose una expresión que resulta de mayor utilidad para los agentes de mercado. The main result of this paper consists in the resolution of the inverse problem for the Black-Cox (1976) model, using the method proposed by Sukhomlin (2007). Based on the backward approach, we obtain an exact expression of the implied volatility expressed as a function of quantifiable market parameters and known variables. We discover the existence of two values of the volatility for an underlying asset, in the referred model, which means that the model's traditional assumptions do not define it univocally. We find the cause that the Black-Cox model contains two values of the volatility. Besides, we carry out a simulation in order to verify, numerically, that our volatility expression is in fact the inversion of the formula that represents the probability that the firm has not reached the reorganization boundary before the debt expires. Finally, we solve the market calibration problem from the forward approach, finding an expression that is more useful for market agents.

Suggested Citation

  • Sukhomlin, Nikolay & Santana Jiménez, Lisette Josefina, 2010. "Problema de calibración de mercado y estructura implícita del modelo de bonos de Black-Cox = Market Calibration Problem and the Implied Structure of the Black-Cox Bond Model," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 10(1), pages 73-98, December.
  • Handle: RePEc:pab:rmcpee:v:10:y:2010:i:1:p:73-98
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    References listed on IDEAS

    as
    1. Jean-Pierre Fouque & George Papanicolaou & Ronnie Sircar & Knut Solna, 2004. "Maturity cycles in implied volatility," Finance and Stochastics, Springer, vol. 8(4), pages 451-477, November.
    2. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-367, May.
    3. Isengildina-Massa, Olga & Curtis, Charles E., Jr. & Bridges, William & Nian, Minhuan, 2007. "Accuracy of Implied Volatility Approximations Using "Nearest-to-the-Money" Option Premiums," 2007 Annual Meeting, February 4-7, 2007, Mobile, Alabama 34927, Southern Agricultural Economics Association.
    4. Motokazu Ishizaka & Koichiro Takaoka, 2003. "On the Pricing of Defaultable Bonds Using the Framework of Barrier Options," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 10(2), pages 151-162, September.
    5. Michael A. Kelly, 2006. "Faster Implied Volatilities via the Implicit Function Theorem," The Financial Review, Eastern Finance Association, vol. 41(4), pages 589-597, November.
    6. Leland, Hayne E, 1994. "Corporate Debt Value, Bond Covenants, and Optimal Capital Structure," Journal of Finance, American Finance Association, vol. 49(4), pages 1213-1252, September.
    7. Max Bruche, 2006. "Estimating Structural Models of Corporate Bond Prices," Working Papers wp2006_0610, CEMFI.
    8. Martina Nardon, 2005. "Valuing defaultable bonds: an excursion time approach," Finance 0511015, University Library of Munich, Germany.
    9. Damiano Brigo & Marco Tarenghi, 2009. "Credit Default Swap Calibration and Equity Swap Valuation under Counterparty Risk with a Tractable Structural Model," Papers 0912.3028, arXiv.org.
    10. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    11. Chance, Don M, 1996. "A Generalized Simple Formula to Compute the Implied Volatility," The Financial Review, Eastern Finance Association, vol. 31(4), pages 859-867, November.
    12. Li, Minqiang, 2008. "Approximate inversion of the Black-Scholes formula using rational functions," European Journal of Operational Research, Elsevier, vol. 185(2), pages 743-759, March.
    13. Corrado, Charles J. & Miller, Thomas Jr., 1996. "A note on a simple, accurate formula to compute implied standard deviations," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 595-603, April.
    14. Leland, Hayne E & Toft, Klaus Bjerre, 1996. "Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Journal of Finance, American Finance Association, vol. 51(3), pages 987-1019, July.
    15. Young Ho Eom, 2004. "Structural Models of Corporate Bond Pricing: An Empirical Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 499-544.
    16. Longstaff, Francis A & Schwartz, Eduardo S, 1995. "A Simple Approach to Valuing Risky Fixed and Floating Rate Debt," Journal of Finance, American Finance Association, vol. 50(3), pages 789-819, July.
    17. Fujita, Takahiko & 藤田, 岳彦 & Ishizaka, Motokazu & 石坂, 元一, 2002. "An Application of New Barrier Options (Edokko Options) for Pricing Bonds with Credit Risk," Hitotsubashi Journal of commerce and management, Hitotsubashi University, vol. 37(1), pages 17-23, October.
    18. Geske, Robert, 1977. "The Valuation of Corporate Liabilities as Compound Options," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(4), pages 541-552, November.
    19. Nikolay Sukhomlin & Philippe Jacquinot, 2007. "Solution exacte du problème inverse de valorisation des options dans le cadre du modèle de Black et Scholes," Working Papers hal-00144781, HAL.
    20. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    21. Chambers, Donald R & Nawalkha, Sanjay K, 2001. "An Improved Approach to Computing Implied Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 89-99, August.
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    More about this item

    Keywords

    modelo de Black-Cox; volatilidad implícita; arbitraje; Black-Cox model; implied volatility; arbitrage;
    All these keywords.

    JEL classification:

    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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