Technical Note—On Matrix Exponential Differentiation with Application to Weighted Sum Distributions

On Modeling the Probability Distribution of Stochastic Sums In “Technical Note—On Matrix Exponential Differentiation with Application to Weighted Sum Distributions,” Das, Tsai, Kyriakou, and Fusai propose an efficient methodology for approximating unknown probability distribution a weighted stochastic sum or time integral. Resulting from earlier contributions based on continuous-time Markov chain approximations one-dimensional processes is Laplace transform available in exponential matrix form. this paper, authors develop bona fide Pearson curve-fitting approach moments, which they recover derivatives transform. Motivated by computational hurdles toward this, derive computationally closed-form expressions exponential. They then apply pricing average-based options.