On Time-subordinated Brownian Motion Processes for Financial Markets

Fuente: arXiv
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Main Authors: Shenoy, Rohan, Kempthorne, Peter
Format: Preprint
Published: 2025
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author Shenoy, Rohan
Kempthorne, Peter
author_facet Shenoy, Rohan
Kempthorne, Peter
contents In the context of time-subordinated Brownian motion models, Fourier theory and methodology are proposed to modelling the stochastic distribution of time increments. Gaussian Variance-Mean mixtures and time-subordinated models are reviewed with a key example being the Variance-Gamma process. A non-parametric characteristic function decomposition of subordinated Brownian motion is presented. The theory requires an extension of the real domain of certain characteristic functions to the complex plane, the validity of which is proven here. This allows one to characterise and study the stochastic time-change directly from the full process. An empirical decomposition of S\&P log-returns is provided to illustrate the methodology.
format Preprint
id arxiv_https___arxiv_org_abs_2510_14108
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On Time-subordinated Brownian Motion Processes for Financial Markets
Shenoy, Rohan
Kempthorne, Peter
Mathematical Finance
Statistics Theory
In the context of time-subordinated Brownian motion models, Fourier theory and methodology are proposed to modelling the stochastic distribution of time increments. Gaussian Variance-Mean mixtures and time-subordinated models are reviewed with a key example being the Variance-Gamma process. A non-parametric characteristic function decomposition of subordinated Brownian motion is presented. The theory requires an extension of the real domain of certain characteristic functions to the complex plane, the validity of which is proven here. This allows one to characterise and study the stochastic time-change directly from the full process. An empirical decomposition of S\&P log-returns is provided to illustrate the methodology.
title On Time-subordinated Brownian Motion Processes for Financial Markets
topic Mathematical Finance
Statistics Theory
url https://arxiv.org/abs/2510.14108