- Alcock, J., & Burrage, K. (2006). A note on the balanced method. BIT Numerical Mathematics, 46, 689–710.
Paper not yet in RePEc: Add citation now
Alfonsi, A. (2005). On the discretization schemes for the CIR (and Bessel squared) processes. Monte Carlo Methods and Applications, 11(4), 355–384.
- Andersen, L. (2007). Efficient simulation of the Heston stochastic volatility model. Working Paper. http://ssrn.com/abstract=946405 or http://dx.doi.org/10.2139/ssrn.946405 .
Paper not yet in RePEc: Add citation now
Andersen, L. B. G., & Piterbarg, V. V. (2007). Moment explosions in stochastic volatility models. Finance Stochastics, 11(1), 29–50.
Bates, D. S. (1996). Jumps and stochastic volatility: Exchange rate processes implicit in deutsche mark options. Review of Financial Studies, 9(1), 69–107.
Broadie, M., & Kaya, Özgür. (2006). Exact simulation of stochastic volatility and other affine jump diffusion processes. Operations Research, 54(2), 217–231.
- Dereich, S., Neuenkirch, A., & Szpruch, L. (2012). An Euler-type method for the strong approximation of the Cox–Ingersoll–Ross process. Proceedings of the Royal Society A, 468(2140), 1105–1115.
Paper not yet in RePEc: Add citation now
Haastrecht, A. V., & Pelsser, A. (2010). Efficient, almost exact simulation of the Heston stochastic volatility model. International Journal of Theoretical and Applied Finance, 31(1), 1–43.
Heston, S. L. (1993). A closed-form solution for options with stochastic volatility with applications to bonds and currency options. The Review of Financial Studies, 6(2), 327–343.
- Higham, D. J. (2001). An algorithmic introducton to numerical simulation of stochastic differential equations. SIAM Review, 43(3), 525–546.
Paper not yet in RePEc: Add citation now
- Higham, D. J., Mao, X., & Stuart, A. M. (2002). Strong convergence of Euler-type methods for nonlinear stochastic differential equations. SIAM Journal on Numerical Analysis, 40, 1041–1063.
Paper not yet in RePEc: Add citation now
- Jäckel, P. (2004). The best of Wilmott 1: Incorporating the Quantitative Finance Review, chap. Stochastic volatility models: Past, present and future. New York: John Wiley and Sons.
Paper not yet in RePEc: Add citation now
Kahl, C., & Schurz, H. (2006). Balanced milstein methods for ordinary sdes. Monte Carlo Methods and Applications, 12(2), 147–170.
- Kahl, C., Gunther, M., & Rossberg, T. (2008). Structure preserving stochastic integration schemes in interest rate derivative modeling. Applied Numerical Mathematics, 58, 284–295.
Paper not yet in RePEc: Add citation now
- Kloeden, P. E., & Platen, E. (1992). Numerical solution of stochastic differential equations. Berlin: Springer.
Paper not yet in RePEc: Add citation now
Lord, R., Koekkoek, R., & Dijk, D. V. (2010). A comparison of biased simulation schemes for stochastic volatility models. Quantitative Finance, 10(2), 177–194.
Milstein, G., Platen, E., & Schurz, H. (1998). Balanced implicit methods for stiff stochastic systems. SIAM Journal on Numerical Analysis, 35(3), 1010–1019.
- Moro, E., & Schurz, H. (2007). Boundary preserving semi-analytic numerical algorithms for stochastic differential equations. SIAM Journal on Scientific Computing, 29, 1525–1549.
Paper not yet in RePEc: Add citation now
- Zhu, J. (2011). A simple and accurate simulation approach to the Heston model. The Journal of Derivatives, 18(4), 26–36.
Paper not yet in RePEc: Add citation now