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A Unifying Approach for the Pricing of Debt Securities (2403.06303v3)

Published 10 Mar 2024 in q-fin.PR, q-fin.CP, and q-fin.MF

Abstract: We propose a unifying framework for the pricing of debt securities under general time-inhomogeneous short-rate diffusion processes. The pricing of bonds, bond options, callable/putable bonds, and convertible bonds (CBs) is covered. Using continuous-time Markov chain (CTMC) approximations, we obtain closed-form matrix expressions to approximate the price of bonds and bond options under general one-dimensional short-rate processes. A simple and efficient algorithm is also developed to price callable/putable debt. The availability of a closed-form expression for the price of zero-coupon bonds allows for the perfect fit of the approximated model to the current market term structure of interest rates, regardless of the complexity of the underlying diffusion process selected. We further consider the pricing of CBs under general bi-dimensional time-inhomogeneous diffusion processes to model equity and short-rate dynamics. Credit risk is also incorporated into the model using the approach of Tsiveriotis and Fernandes (1998). Based on a two-layer CTMC method, an efficient algorithm is developed to approximate the price of convertible bonds. When conversion is only allowed at maturity, a closed-form matrix expression is obtained. Numerical experiments show the accuracy and efficiency of the method across a wide range of model parameters and short-rate models.

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References (68)
  1. M. Abudy and Y. Izhakian. Pricing stock options with stochastic interest rate. International Journal of Portfolio Analysis and Management, 1(3):250–277, 2013.
  2. Simulation-based pricing of convertible bonds. Journal of Empirical Finance, 15(2):310–331, 2008.
  3. Valuation of Convertible Bonds with Credit Risk. The Journal of Derivatives, 11(1):9–29, 2003.
  4. Two-factor convertible bonds valuation using the method of characteristics/finite elements. Journal of Economic Dynamics and Control, 27(10):1801–1831, 2003.
  5. A. Battauz and F. Rotondi. American options and stochastic interest rates. Computational Management Science, 19:567–604, 2022.
  6. Convertible bond pricing models. Journal of Economic Surveys, 28(5):775–803, 2014.
  7. Pricing convertible bonds. Journal of Banking & Finance, 92:216–236, 2018.
  8. A dynamic programming approach for pricing options embedded in bonds. Journal of Economic Dynamics and Control, 31(7):2212–2233, 2007.
  9. P. Billingsley. Convergence of Probability Measures. John Wiley & Sons, Inc., 2nd edition, 1999.
  10. T. Björk. Arbitrage Theory in Continuous Time. Oxford University Press, 3rd edition, 2009.
  11. F. Black and P. Karasinski. Bond and Option Pricing when Short Rates are Lognormal. Financial Analysts Journal, 47(4):52–59, 1991.
  12. A One-Factor Model of Interest Rates and Its Application to Treasury Bond Options. Financial Analysts Journal, 46(1):33–39, 1990.
  13. Convertible Bonds: Valuation and Optimal Strategies for Call and Conversion. The Journal of Finance, 32(5):1699–1715, 1977.
  14. D. Brigo and F. Mercurio. Interest Rate Models – Theory and Practice: With Smile, Inflation and Credit. Springer, 2nd edition, 2006.
  15. J. Buffington and R. J. Elliott. American options with regime switching. International Journal of Theoretical and Applied Finance, 5(05):497–514, 2002.
  16. H.-J. Büttler and J. Waldvogel. Pricing Callable Bonds by Means of Green’s Function. Mathematical Finance, 6(1):53–88, 1996.
  17. D. R. Chambers and Q. Lu. A Tree Model for Pricing Convertible Bonds with Equity, Interest Rate, and Default Risk. The Journal of Derivatives, 14(4):25–46, 2007.
  18. K. Chourdakis. Non-Affine Option Pricing. The Journal of Derivatives, 11(3):10–25, 2004.
  19. Option Pricing: A Simplified Approach. Journal of financial Economics, 7(3):229–263, 1979.
  20. A Theory of the Term Structure of Interest Rates. Econometrica, 53(2):385–407, 1985.
  21. I. Crimaldi and L. Pratelli. Convergence results for conditional expectations. Bernoulli, 11(4):737–745, 2005.
  22. Z. Cui. Martingale Property and Pricing for Time-Homogeneous Diffusion Models in Finance. PhD thesis, University of Waterloo, 2013.
  23. A General Valuation Framework for SABR and Stochastic Local Volatility Models. SIAM Journal on Financial Mathematics, 9(2):520–563, 2018.
  24. Continuous-Time Markov Chain and Regime Switching Approximations with Applications to Options Pricing. In G. Yin and Q. Zhang, editors, Modeling, Stochastic Control, Optimization, and Applications, pages 115–146. Springer, 2019.
  25. Efficient simulation of generalized SABR and stochastic local volatility models based on Markov chain approximations. European Journal of Operational Research, 290(3):1046–1062, 2021.
  26. A numerical PDE approach for pricing callable bonds. Applied Mathematical Finance, 8(1):49–77, 2001.
  27. Pricing callable bonds based on monte carlo simulation techniques. Technology and Investment, 3:121–125, 2012.
  28. K. Ding and N. Ning. Markov chain approximation and measure change for time-inhomogeneous stochastic processes. Applied Mathematics and Computation, 392:125732, 2021.
  29. L. Dothan. On the term structure of interest rates. Journal of Financial Economics, 6(1):59–69, 1978.
  30. D. J. Duffy. Finite Difference Methods in Financial Engineering: A Partial Differential Equation Approach. John Wiley & Sons, 2006.
  31. Pricing American options: A Comparison of Monte Carlo Simulation Approaches. Journal of Computational Finance, 4(3):39–88, 2001.
  32. Changes of numéraire, changes of probability measure and option pricing. Journal of Applied probability, 32(2):443–458, 1995.
  33. P. Glasserman. Monte Carlo Methods in Financial Engineering, volume 53. Springer, 2003.
  34. E. M. Goggin. Convergence in Distribution of Conditional Expectations. The Annals of Probability, pages 1097–1114, 1994.
  35. V. Gushchin and E. Curien. The pricing of convertible bonds within the Tsiveriotis and Fernandes framework with exogenous credit spread: Empirical analysis. Journal of Derivatives & Hedge Funds, 14:50–65, 2008.
  36. Term Structure Movements and Pricing Interest Rate Contingent Claims. The Journal of Finance, 41(5):1011–1029, 1986.
  37. J. Hull and A. White. Pricing Interest-Rate-Derivative Securities. The Review of Financial Studies, 3(4):573–592, 1990.
  38. J. Hull and A. White. Numerical Procedures for Implementing Term Structure Models I: Single-Factor Models. The Journal of Derivatives, 2(1):7–16, 1994.
  39. J. Hull and A. White. Using Hull-White Interest Rate Trees. The Journal of Derivatives, 3(3):26–36, 1996.
  40. Pricing Convertible Bonds Subject to Default Risk. The journal of Derivatives, 10(2):75–87, 2002.
  41. J. E. Ingersoll Jr. A contingent-claims valuation of convertible securities. Journal of Financial Economics, 4(3):289–321, 1977.
  42. Pricing Derivatives on Financial Securities Subject to Credit Risk. The Journal of Finance, 50(1):53–85, 1995.
  43. B. Jourdain. Loss of martingality in asset price models with lognormal stochastic volatility. Preprint 267, CERMICS, 2004.
  44. J. L. Kirkby. Hybrid equity swap, cap, and floor pricing under stochastic interest by Markov chain approximation. European Journal of Operational Research, 305(2):961–978, 2023.
  45. A general continuous time Markov chain approximation for multi-asset option pricing with systems of correlated diffusions. Applied Mathematics and Computation, 386:125472, 2020.
  46. M. A. Kouritzin and Y. Zeng. Weak convergence for a type of conditional expectation: application to the inference for a class of asset price models. Nonlinear Analysis: Theory, Methods & Applications, 60(2):231–239, 2005.
  47. D. Lamberton. American Options. In D. J. Hand and S. D. Jacka, editors, Statistic in Finance. Arnold, 1998.
  48. S. Lin and S.-P. Zhu. Numerically pricing convertible bonds under stochastic volatility or stochastic interest rate with an adi-based predictor–corrector scheme. Computers & Mathematics with Applications, 79(5):1393–1419, 2020.
  49. S. Lin and S.-P. Zhu. Pricing callable–puttable convertible bonds with an integral equation approach. Journal of Futures Markets, 42(10):1856–1911, 2022.
  50. C. C. Lo and K. Skindilias. An improved Markov chain approximation methodology: Derivatives pricing and model calibration. International Journal of Theoretical and Applied Finance, 17(7):1450047, 2014.
  51. Valuing American Options by Simulation: A Simple Least-Squares Approach. The Review of Financial Studies, 14(1):113–147, 2001.
  52. L. Lu and W. Xu. A Simple and Efficient Two-Factor Willow Tree Method for Convertible Bond Pricing with Stochastic Interest Rate and Default Risk. The Journal of Derivatives, 25(1):37–54, 2017.
  53. Valuation model for Chinese convertible bonds with soft call/put provision under the hybrid willow tree. Quantitative Finance, 20(12):2037–2053, 2020.
  54. A. Mackay and M.-C. Vachon. On an optimal stopping problem with a discontinuous reward. arXiv preprint arXiv:2311.03538, 2023.
  55. Analysis of VIX-linked fee incentives in variable annuities via continuous-time Markov chain approximation. Quantitative Finance, 23(7-8):1055–1078, 2023.
  56. LYON taming. The Journal of Finance, 41(3):561–576, 1986.
  57. F. Mentink-Vigier. Fast exponential matrix for Matlab (full/sparse), fastExpm. Available at Github https://github.com/fmentink/fastExpm. Accessed: April 27, 2023.
  58. F. Mercurio and J. M. Moraleda. A family of humped volatility models. The European Journal of Finance, 7(2):93–116, 2001.
  59. A. Mijatović and M. Pistorius. Continuously monitored barrier options under Markov processes (unabridged version with Matlab code). Available at SSRN 1462822, 2009.
  60. A. Mijatović and M. Pistorius. Continuously monitored barrier options under Markov processes. Mathematical Finance, 23(1):1–38, 2013.
  61. A Binomial-Tree Model for Convertible Bond Pricing. The Journal of Fixed Income, 22(3):79–94, 2013.
  62. V. Ostrovski. Efficient and Exact Simulation of the Hull-White Model. Available at SSRN 2304848, 2013.
  63. Exact Methods for the Transient Analysis of Nonhomogeneous Continuous Time Markov Chains. In W. J. Stewart, editor, Computations with Markov Chains, pages 121–133. Springer, 1995.
  64. C. A. Sin. Complications with stochastic volatility models. Advances in Applied Probability, 30(1):256–268, 1998.
  65. Weak Convergence Methods for Approximation of the Evaluation of Path-Dependent Functionals. SIAM Journal on Control and Optimization, 51(5):4189–4210, 2013.
  66. D. Tavella and C. Randall. Pricing Financial Instruments: The Finite Difference Method. John Willey & Sons, 2000.
  67. K. Tsiveriotis and C. Fernandes. Valuing Convertible Bonds with Credit Risk. The Journal of Fixed Income, 8(2):95, 1998.
  68. O. Vasicek. An equilibrium characterization of the term structure. Journal of Financial Economics, 5(2):177–188, 1977.

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