Duality and transform analysis for non-decreasing functionals of stochastic processes and their applications

Abstract We establish a novel duality relationship between continuous/discrete non-negative non-decreasing functionals of stochastic (not necessarily Markovian) processes and their right inverses, and further discuss its applications. For general Markov processes, we develop a theoretical and computational framework for the transform analysis via an operator-based approach, i.e. through the infinitesimal generators. More precisely, we characterize the joint double transforms of additive functionals of Markov processes and the terminal values in continuous/discrete time. Under the continuous-time Markov chain (CTMC) setting, we obtain single Laplace transforms for continuous/discrete additive functionals and their inverses. We apply the proposed transform methodology to computing option prices related to the occupation time of the underlying asset price process.