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Efficient numerical schemes for the approximation of expectations of functionals of the solution of a S.D.E., and applications
2 references·5 citing·30 second hop
Efficient numerical schemes for the approximation of expectations of functionals of the solution of a S.D.E., and applications (2005)Efficient numerical schemes for the appro…Discretization and simulation of stochastic differential equations (1985)Discretization and simulation…Simulation and the Monte Carlo Method (1981)Simulation and the Monte Carl…Arbitrage-free discretization of lognormal forward Libor and swap rate models (2000)Arbitrage-free discretization…Rate of Convergence of the Euler Approximation for Diffusion Processes (1991)Rate of Convergence of the Eu…Time Discrete Taylor Approximations for Itǒ Processes with Jump Component (1988)Time Discrete Taylor Approxim…Discrétisation d'une équation différentielle stochastique et calcul approché d'espérances de fonctionnelles de la solution (1986)Discrétisation d'une équation…An asymptotically efficient difference formula for solving stochastic differential equations (1986)An asymptotically efficient d…Stochastic Calculus and Stochastic Models (1974)On the Gap Between Deterministic and Stochastic Ordinary Differential Equations (1978)Stochastic Differential Equations and Diffusion Processes (1983)Wong-Zakai Corrections, Random Evolutions, and Simulation Schemes for SDE's (1991)Option Pricing Under Incompleteness and Stochastic Volatility (1992)Fast strong approximation Monte Carlo schemes for stochastic volatility models (2006)MULTI-DIMENSIONAL DIFFUSION PROCESSES (1980)Weak approximation of solutions of systems of stochastic differential equations (1995)Weak rate of convergence of the Euler–Maruyama scheme for stochastic differential equations with non-regular drift (2017)On the regularisation of the noise for the Euler-Maruyama scheme with irregular drift (2020)Calcul Stochastique et Problèmes de Martingales (1979)Controlled Diffusion Processes (1980)Stochastic Differential Equations and Diffusion Processes (1981)Weak Approximations and Extrapolations of Stochastic Differential Equations with Jumps (2000)Convergence of a discretization scheme for jump-diffusion processes with state–dependent intensities (2004)Stochastic Differential Equations and Applications (1976)Monte carlo evaluation of functionals of solutions of stochastic differential equations. variance reduction and numerical examples (1988)Exact convergence rate of the Euler-Maruyama scheme, with application to sampling design (1996)Optimal pointwise approximation of stochastic differential equations driven by fractional Brownian motion (2008)Bond Pricing and the Term Structure of Interest Rates: A New Methodology for Contingent Claims Valuation (1992)A Libor Market Model with Default Risk (2001)Pricing Models for Bermudan-style Interest Rate Derivatives (2001)Numerical solution of jump-diffusion LIBOR market models (2003)“Options, Futures, and Other Derivatives” (2016)Numerical solution of stochastic differential equations (2016)Error estimates for the binomial approximation of American put options (1998)Numerical Approximation for Functionals of Reflecting Diffusion Processes (1998)A New Study on Reliability-Based Design Optimization (1999)Estimation of small failure probabilities in high dimensions by subset simulation (2001)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)
this work references cited by second hop

References

  • 1981Simulation and the Monte Carlo Method2,402 cited
  • 1985Discretization and simulation of stochastic differential equations197 cited

Cited by

  • 2000Arbitrage-free discretization of lognormal forward Libor and swap rate models76 cited
  • 1986Discrétisation d'une équation différentielle stochastique et calcul approché d'espérances de fonctionnelles de la solution76 cited
  • 1988Time Discrete Taylor Approximations for Itǒ Processes with Jump Component66 cited
  • 1991Rate of Convergence of the Euler Approximation for Diffusion Processes54 cited
  • 1986An asymptotically efficient difference formula for solving stochastic differential equations43 cited

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