Theoretical and computational investigations of superposed interacting affine and more complex processes

Abstract: Non-Markovian long memory processes arise from numerous science and engineering problems. The Markovian lift is an effective mathematical technique that transforms a non-Markov process into an infinite-dimensional Markov process to which a broad range of theoretical and computational results can be potentially applied. One challenge in Markovian lifts is that the resulting Markovian system has multiple time scales ranging from infinitely small to infinitely large; therefore, a numerical method that consistently deals with them is required. However, such an approach has not been well studied for the superposition of affine or more complex jump-diffusion processes driven by L\'evy bases. We address this issue based on recently developed exact discretization methods for affine diffusion and jump processes. A nominal superposition process consisting of an infinite number of interacting affine processes was considered, along with its finite-dimensional version and associated generalized Riccati equations. We examine the computational performance of the proposed numerical scheme based on exact discretization methods through comparisons with the analytical results. We also numerically investigate a more complex model arising in the environmental sciences and some extended cases in which superposed processes belong to a class of nonlinear processes that generalize affine processes.