Multiplicative Langevin Process for Volatilities Produces Observed Q-Variance Regularities

Fuente: arXiv
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Auteurs principaux: Press, William H., Dannenberg, Alex
Format: Preprint
Publié: 2026
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author Press, William H.
Dannenberg, Alex
author_facet Press, William H.
Dannenberg, Alex
contents Q-variance (so-called) posits a statistical relationship $\mathbf{E}(σ^2 | z) = σ_0^2 + \tfrac{1}{2}z^2$ between an asset's volatility $σ^2$, as observed in a time interval $T$, and its (suitably scaled) return $z$ in the same interval. We here show that this relationship is {\em exactly equivalent} to to positing an Inverse Gamma probability distribution for $σ^2$ itself. We then show that such a distribution is exactly generated by a multiplicative Langevin process with an arbitrary, settable coherence time $τ_c$, so that very nearly the same Q-variance relationship will hold for all $T \ll τ_c$.
format Preprint
id arxiv_https___arxiv_org_abs_2606_00800
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Multiplicative Langevin Process for Volatilities Produces Observed Q-Variance Regularities
Press, William H.
Dannenberg, Alex
Pricing of Securities
Statistical Finance
Q-variance (so-called) posits a statistical relationship $\mathbf{E}(σ^2 | z) = σ_0^2 + \tfrac{1}{2}z^2$ between an asset's volatility $σ^2$, as observed in a time interval $T$, and its (suitably scaled) return $z$ in the same interval. We here show that this relationship is {\em exactly equivalent} to to positing an Inverse Gamma probability distribution for $σ^2$ itself. We then show that such a distribution is exactly generated by a multiplicative Langevin process with an arbitrary, settable coherence time $τ_c$, so that very nearly the same Q-variance relationship will hold for all $T \ll τ_c$.
title Multiplicative Langevin Process for Volatilities Produces Observed Q-Variance Regularities
topic Pricing of Securities
Statistical Finance
url https://arxiv.org/abs/2606.00800