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A monotone piecewise constant control integration approach for the two-factor uncertain volatility model (2402.06840v4)

Published 9 Feb 2024 in q-fin.CP

Abstract: Option contracts on two underlying assets within uncertain volatility models have their worst-case and best-case prices determined by a two-dimensional (2D) Hamilton-Jacobi-BeLLMan (HJB) partial differential equation (PDE) with cross-derivative terms. This paper introduces a novel ``decompose and integrate, then optimize'' approach to tackle this HJB PDE. Within each timestep, our method applies piecewise constant control, yielding a set of independent linear 2D PDEs, each corresponding to a discretized control value. Leveraging closed-form Green's functions, these PDEs are efficiently solved via 2D convolution integrals using a monotone numerical integration method. The value function and optimal control are then obtained by synthesizing the solutions of the individual PDEs. For enhanced efficiency, we implement the integration via Fast Fourier Transforms, exploiting the Toeplitz matrix structure. The proposed method is $\ell_{\infty}$-stable, consistent in the viscosity sense, and converges to the viscosity solution of the HJB equation. Numerical results show excellent agreement with benchmark solutions obtained by finite differences, tree methods, and Monte Carlo simulation, highlighting its robustness and effectiveness.

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References (36)
  1. Pricing and hedging derivative securities in markets with uncertain volatilities. Applied Mathematical Finance, 2:73–88, 1995.
  2. Combinatorial implications of nonlinear uncertain volatility models: the case of barrier options. Applied Mathematical Finance, 6(1):1–18, 1999.
  3. G. Barles and P.E. Souganidis. Convergence of approximation schemes for fully nonlinear equations. Asymptotic Analysis, 4:271–283, 1991.
  4. Some convergence results for Howard’s algorithm. SIAM Journal on Numerical Analysis, 47:3001–3026, 2009.
  5. Consistency of generalized finite difference schemes for the stochastic HJB equation. SIAM Journal on Numerical Analysis, 41(3):1008–1021, 2003.
  6. K. Debrabant and E.R. Jakobsen. Semi-Lagrangian schemes for linear and fully non-linear diffusion equations. Mathematics of Computation, 82:1433–1462, 2013.
  7. The pricing of options in a financial market model with transaction costs and uncertain volatility. Journal of Multinational Financial Management, 8(2-3):353–364, 1998.
  8. Dean G. Duffy. Green’s Functions with Applications. Chapman and Hall/CRC, New York, 2nd edition, 2015.
  9. P. A. Forsyth and G. Labahn. Numerical methods for controlled Hamilton-Jacobi-Bellman PDEs in finance. Journal of Computational Finance, 11(2):1, 2007.
  10. Green functions for second order parabolic integro-differential problems. Number 275 in Pitman Research Notes in Mathematics. Longman Scientific and Technical, Harlow, Essex, UK, 1992.
  11. A note on the bivariate distribution representation of two perfectly correlated random variables by dirac’s δ𝛿\deltaitalic_δ-function. arXiv preprint arXiv:1205.0933, 2012.
  12. J. Guyon and P. Henry-Labordere. Uncertain volatility model: a Monte-Carlo approach. Journal of Computational Finance, 14:37–74, 2011.
  13. Managing smile risk. The Best of Wilmott, 1:249–296, 2002.
  14. S. Heston. A closed form solution for options with stochastic volatility with applications to bond and currency options. Review of Financial Studies, 6:327–343, 1993.
  15. Valuation of European options under an uncertain market price of volatility risk. Applied Mathematical Finance, 29(3):213–226, 2022.
  16. The 2D tree–grid method. Journal of Computational Finance, 22(12):29–57, 2019.
  17. N.V. Krylov. Approximating value functions for controlled degenerate diffusion processes by using piece-wise constant policies. Electronic Journal of Probability, 4(2):1–19, 1999.
  18. J.M. Lee. Introduction to smooth manifolds. Springer-Verlag, New York, 2 edition, 2012.
  19. T. Lyons. Uncertain volatility and the risk free synthesis of derivatives. Applied Mathematical Finance, 2:117–133, 1995.
  20. T. J. Lyons. Uncertain volatility and the risk-free synthesis of derivatives. Applied Mathematical Finance, 2(2):117–133, 1995.
  21. K. Ma and P.A. Forsyth. An unconditionally monotone numerical scheme for the two-factor uncertain volatility model. IMA Journal of Numerical Analysis, 37(2):905–944, 2017.
  22. A.M. Oberman. Convergent difference schemes for degenerate elliptic and parabolic equations: Hamilton–Jacobi Equations and free boundary problems. SIAM Journal Numerical Analysis, 44(2):879–895, 2006.
  23. H. Pham. On some recent aspects of stochastic control and their applications. Probability Surveys, 2:506–549, 2005.
  24. Two factor option pricing with uncertain volatility. In International Conference on Computational Science and Its Applications, pages 158–167. Springer, 2003.
  25. Numerical convergence properties of option pricing PDEs with uncertain volatility. IMA Journal of Numerical Analysis, 23:241–267, 2003.
  26. C. Reisinger and P.A. Forsyth. Piecewise constant policy approximations to Hamilton-Jacobi-Bellman equations. Applied Numerical Mathematics, 103:27–47, 2016.
  27. Walter Rudin. Principles of mathematical analysis. 1953.
  28. Two-dimensional Fourier cosine series expansion method for pricing financial options. SIAM Journal on Scientific Computing, 34(5):B642–B671, 2012.
  29. Adam T Smith. American options under uncertain volatility. Applied Mathematical Finance, 9(2):123–141, 2002.
  30. An atlas of functions, 1988.
  31. R. Stulz. Options on the minimum or the maximum of two risky assets: Analysis and applications. Journal of Financial Economics, 10(2):161–185, 1982.
  32. A.Dembo W. Bryc and T. Jiang. Spectral measure of large random Hankel, Markov and Toeplitz matrices. 2006.
  33. J. Wang and P.A. Forsyth. Maximal use of central differencing for Hamilton-Jacobi-Bellman PDEs in finance. SIAM Journal on Numerical Analysis, 46:1580–1601, 2008.
  34. Xavier Warin. Some non-monotone schemes for time dependent Hamilton-Jacobi-Bellman equations in stochastic control. Journal of Scientific Computing, 66(3):1122–1147, 2016.
  35. R. Willink. Bounds on the bivariate normal distribution function. Communications in Statistics-Theory and Methods, 33(10):2281–2297, 2005.
  36. H. Zhang and D.M. Dang. A monotone numerical integration method for mean-variance portfolio optimization under jump-diffusion models. Mathematics and Computers in Simulation, 219:112–140, 2024.
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