Stochastic Calculus via Stopping Derivatives

Fuente: arXiv
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Auteur principal: Simpson, Alex
Format: Preprint
Publié: 2025
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author Simpson, Alex
author_facet Simpson, Alex
contents We show that a substantial portion of stochastic calculus can be developed along similar lines to ordinary calculus, with derivative-based concepts driving the development. We define a notion of stopping derivative, which is a form of right derivative with respect to stopping times. Using this, we define the drift and variance rate of a process as stopping derivatives for (generalised) conditional expectation and conditional variance respectively. Applying elementary, derivative-based methods, we derive a calculus of rules describing how drift and variance rate transform under operations on processes, culminating in a version of the multi-dimensional Itô formula. Our approach connects with the standard machinery of stochastic calculus via a theorem establishing that continuous processes with zero drift coincide with random translations of continuous local martingales. This equivalence allows us to derive a fundamental theorem of calculus for stopping derivatives, which relates the quantities of drift and variance rate, defined as stopping derivatives, to parameters used in the description of a process as a stochastic integral.
format Preprint
id arxiv_https___arxiv_org_abs_2501_02862
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stochastic Calculus via Stopping Derivatives
Simpson, Alex
Probability
60H99 (Primary) 60G07, 60G48, 60H05 (Secondary)
We show that a substantial portion of stochastic calculus can be developed along similar lines to ordinary calculus, with derivative-based concepts driving the development. We define a notion of stopping derivative, which is a form of right derivative with respect to stopping times. Using this, we define the drift and variance rate of a process as stopping derivatives for (generalised) conditional expectation and conditional variance respectively. Applying elementary, derivative-based methods, we derive a calculus of rules describing how drift and variance rate transform under operations on processes, culminating in a version of the multi-dimensional Itô formula. Our approach connects with the standard machinery of stochastic calculus via a theorem establishing that continuous processes with zero drift coincide with random translations of continuous local martingales. This equivalence allows us to derive a fundamental theorem of calculus for stopping derivatives, which relates the quantities of drift and variance rate, defined as stopping derivatives, to parameters used in the description of a process as a stochastic integral.
title Stochastic Calculus via Stopping Derivatives
topic Probability
60H99 (Primary) 60G07, 60G48, 60H05 (Secondary)
url https://arxiv.org/abs/2501.02862