In this work, we develop a multi-factor approximation for Stochastic Volterra Equations with Lipschitz coefficients and kernels of completely monotone type that may be singular. Our approach consists in truncating and then discretizing the integral defining the kernel, which corresponds to a classical Stochastic Differential Equation. We prove strong convergence results for this approximation. For the particular rough kernel case with Hurst parameter lying in $(0,1/2)$, we propose various discretization procedures and give their precise rates of convergence. We illustrate the efficiency of our approximation schemes with numerical tests for the rough Bergomi model.

翻译：在这项工作中,我们为具有完全单型单体单体型的利普西茨系数和内核的斯托切斯特伏特拉赤道开发了一个多要素近似值。我们的方法是截断和分解整体定义内核,这个内核与古典的斯托克差异等值相对应。我们证明这一近似值具有很强的趋同结果。对于赫斯特参数为(0.1/2)美元(0.1/2)美元)的特大粗内核,我们建议了各种离散程序,并给出精确的趋同率。我们用粗贝戈米模型的数字测试来说明我们近似计划的效率。