We study discrete-time simulation schemes for stochastic Volterra equations, namely the Euler and Milstein schemes, corresponding Multilevel Monte-Carlo method. By using adapting some results from Zhang (2008), together with Garsia–Rodemich–Rumsey lemma, we obtain convergence rates of scheme under supremum norm. then apply these to approximate expectation functionals such equations by (Multilev...

We outline and test a new methodology for genuine simulation of stochastic processes with any dependence structure marginal distribution. reproduce time generalized, symmetric or asymmetric, moving-average scheme. This implements linear filtering non-Gaussian white noise, the weights filter determined by analytical equations, in terms autocovariance process. approximate distribution process, ir...