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In this paper, a two-parameter Milstein method for stochastic Volterra integral equations is introduced. First, the method is proved to be strongly convergent with order one in L p norm (p ≥ 1). Then, we investigate the mean square stability of the exact and numerical solutions of a stochastic convolution test equation. Stability conditions are derived. Based on these conditions, analytical and numerical stability regions are plotted and compared with each other. The results show that additional implicitness offers benefits for numerical stability. Finally, some numerical experiments are carried out to confirm the theoretical results. [ABSTRACT FROM AUTHOR]

This paper aims to provide a rigorous analysis of exponential convergence of the Chebyshev collocation method for third kind linear Volterra integral equations. Different from Volterra integral equations of the second kind, the integral operator in third kind equations is noncompact under certain conditions, which brings special challenges to numerical analysis. The key idea of the proposed method is to adopt a smoothing transformation for the Chebyshev collocation method to circumvent the curse of singularity at the beginning of time. Therefore, the solution of the resulting equation will possess better regularity and then the numerical method can achieve the spectral accuracy. Moreover, in order to show the applicability and efficiency of the method, several examples with non-smooth solutions are illustrated. [ABSTRACT FROM AUTHOR]