The Mellin Transform in Probabilistic Cash Flow Modeling

Abstract

This paper expands some of the useful properties of the Mellin transform in risk analysis. The Mellin transform is particularly useful in evaluating the present value of a cash flow profile that contains produces or quotients of independent random variables. Just as we can obtain moments directly from the Fourier, Laplace, and geometric transforms, so can we obtain statistical moments from the Mellin transform without taking the inversion process or derivatives. The Mellin transform is also useful in computing any order of moments for a cash flow distribution based on discrete-payment and discrete compounding. A few examples are shown in this paper to demonstrate the operational properties of the Mellin transform.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 29 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.