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Weak convergence of a numerical scheme for stochastic differential equations

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Języki publikacji
EN
Abstrakty
EN
In this paper a numerical scheme approximating the solution to a stochastic differential equation is presented. On bounded subsets of time, this scheme has a finite state space, which allows us to decrease the round-off error when the algorithm is implemented. At the same time, the scheme introduced turns out locally consistent for any step size of time. Weak convergence of the scheme to the solution of the stochastic differentia equation is shown.
Rocznik
Strony
201--215
Opis fizyczny
Bibliogr. 22 poz.
Twórcy
autor
  • Facultad de Ciencias de la Ingeniería, Universidad Austral de Chile, Valdivia, Chile
autor
  • Instituto de Matemáticas, Universidad de Valparaíso, Villa Alemana, Chile
Bibliografia
  • [1] P. Billingsley, Convergence of Probability Measures, Wiley, New York 1968.
  • [2] A. A. Bykov, Numerical solution of stiff Cauchy problems for systems of linear ordinary differential equations, Vyčisl. Metody i Programmirovanie 38 (1983), pp. 173-181.
  • [3] M. Daumas, D. Lester, É. Martin-Dorel, and A. Truffert, Improved bound for stochastic formal correctness of numerical algorithms, Innovations in Systems and Software Engineering 6 (3) (2010), pp. 173-179.
  • [4] K. Debrabant and A. Rössler, Classification of stochastic Runge-Kutta methods for the weak approximation of stochastic differential equations, Math. Comput. Simulation 77 (2008), pp. 408-420.
  • [5] K. Debrabant and A. Rössler, Families of efficient second order Runge-Kutta methods for the weak approximation of Itô stochastic differential equations, Appl. Numer. Math. 59 (2009), pp. 582-594.
  • [6] S. Delanttre and J. Jacod, A central limit theorem for normalized functions of the increments of a diffusion process, in the presence of round-off errors, Bernoulli 3 (3) (1997), pp. 1-28.
  • [7] O. S. Fard, A numerical scheme to solve nonlinear stochastic differential equation, Int. J. Appl. Math. Comput. Sci. 2 (2007), pp. 101-113.
  • [8] R. Fierro and S. Torres, A stochastic scheme of approximation for ordinary differential equations, Electron. Commun. Probab. 13 (2008), pp. 1-9.
  • [9] G. Fleury, Convergence of schemes for stochastic differential equations, Probab. Eng. Mech. 21 (2006), pp. 35-43.
  • [10] P. Henrici, Discrete Variable Methods in Ordinary Differential Equations, Wiley, New York 1962.
  • [11] J. Jacob and A. N. Shiryaev, Limit Theorems for Stochastic Processes, Springer, Berlin 2003.
  • [12] A. Jakubowski, J. Mémin, and G. Pages, Convergence en loi des suites d’intégrales stochastiques sur l’espace D1 de Skorohod, Probab. Theory Related Fields 81 (1989), pp. 111-137.
  • [13] S. Janković and D. Ilić, An analytic approximation of solutions of stochastic differential equations, Comput. Math. Appl. 47 (2004), pp. 903-912.
  • [14] P. E. Kloeden and E. Platen, Numerical Solution of Stochastic Differential Equations, Springer, New York 1995.
  • [15] T. G. Kurtz and P. Protter, Weak limit theorems for stochastic integrals and stochastic differential equations, Ann. Probab. 19 (3) (1991), pp. 1035-1070.
  • [16] H. J. Kushner and P. G. Dupuis, Numerical Methods for Stochastic Control Problems in Continuous Time, Springer, New York 1992.
  • [17] J. Mémin and L. Słomiński, Condition UT et stabilité en loi des solutions d’équations différentielles stochastiques, in: Séminaire des Probabilités XXV, Lecture Notes in Math., Vol. 1485, Springer, Berlin 1992, pp. 162-177.
  • [18] R. Rebolledo, Central limit theorems for local martingales, Probab. Theory Related Fields 51 (1980), pp. 269-286.
  • [19] M. Rosenbaum, Integrated volatility and round-off error, Bernoulli 2 (3) (2009), pp. 687-720.
  • [20] L. Słomiński, Stability of strong solutions of stochastic differential equations, Stochastic Process. Appl. 31 (1989), pp. 173-202.
  • [21] P. D. N. Srinivasu and M. Venkatesulu, Quadratically convergent numerical schemes for non-standard value problems, Appl. Math. Comput. 47 (1992), pp. 145-154.
  • [22] S. Wollman, Convergence of a numerical approximation to the one-dimensional Vlasov-Poisson system, Transport Theory Statist. Phys. 19 (3) (1990), pp. 545-562.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dc3ba82e-339a-427e-934c-055e3ef1079a
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