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Markov Chain Approximation of One-Dimensional Sticky Diffusions

Christian Meier, Lingfei Li and Gongqiu Zhang

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Abstract: We develop continuous time Markov chain (CTMC) approximation of one-dimensional diffusions with a lower sticky boundary. Approximate solutions to the action of the Feynman-Kac operator associated with a sticky diffusion and first passage probabilities are obtained using matrix exponentials. We show how to compute matrix exponentials efficiently and prove that a carefully designed scheme achieves second order convergence. We also propose a scheme based on CTMC approximation for the simulation of sticky diffusions, for which the Euler scheme may completely fail. The efficiency of our method and its advantages over alternative approaches are illustrated in the context of bond pricing in a sticky short rate model for low interest environment.

Date: 2019-10
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Published in Adv. Appl. Probab. 53 (2021) 335-369

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