Simplified stochastic calculus with applications in Economics and Finance

TL;DR

This paper presents a simplified stochastic calculus that operates without explicit probability measures, facilitating easier calculations of drifts, expectations, and applications in Economics and Finance.

Contribution

It introduces a measure-free stochastic calculus that simplifies manipulation of processes and enhances computational effectiveness in financial modeling.

Findings

New calculus captures jumps without explicit probability measures.

Effective computation of drifts and expectations involving measure changes.

Application to a novel Margrabe option exchange result.

Abstract

The paper introduces a simple way of recording and manipulating general stochastic processes without explicit reference to a probability measure. In the new calculus, operations traditionally presented in a measure-specific way are instead captured by tracing the behaviour of jumps (also when no jumps are physically present). The calculus is fail-safe in that, under minimal assumptions, all informal calculations yield mathematically well-defined stochastic processes. The calculus is also intuitive as it allows the user to pretend all jumps are of compound Poisson type. The new calculus is very effective when it comes to computing drifts and expected values that possibly involve a change of measure. Such drift calculations yield, for example, partial integro-differential equations, Hamilton-Jacobi-Bellman equations, Feynman-Kac formulae, or exponential moments needed in numerous applications. We provide several illustrations of the new technique, among them a novel result on the Margrabe option to exchange one defaultable asset for another.