We present new high order approximations schemes for the Cox-Ingersoll-Ross (CIR) process that are obtained by using a recent technique developed by Alfonsi and Bally (2021) for the approximation of semigroups. The idea consists in using a suitable combination of discretization schemes calculated on different random grids to increase the order of convergence. This technique coupled with the second order scheme proposed by Alfonsi (2010) for the CIR leads to weak approximations of order $2k$, for all $k\in\mathbb{N}^*$. Despite the singularity of the square-root volatility coefficient, we show rigorously this order of convergence under some restrictions on the volatility parameters. We illustrate numerically the convergence of these approximations for the CIR process and for the Heston stochastic volatility model and show the computational time gain they give.
翻译:我们为Cox-Ingersoll-Ross(CIR)进程提出了新的高定序近似方案,这是通过使用Alfonsi和Bally(2021年)最近开发的近似半组技术获得的,其理念是使用在不同随机网格上计算的不同离散方案的适当组合来提高趋同的顺序。这一技术与Alfonsi(2010年)为CIR提议的第二定序方案相结合,导致所有美元均达2k美元近似值疲软。尽管平方根波动系数的奇特性,但我们在对波动参数的某些限制下严格显示了这种趋同顺序。我们从数字上说明了这些近似值对CIR进程和赫斯顿预测波动模型的趋同性,并展示了它们带来的计算时间收益。