Weighted Brownian Increment Second Moment
ProvedLevyStochCalc.Brownian.Ito.integral_factor_increment_sq_readableThis states a weighted second-moment identity for a Brownian motion under a probability measure and a Brownian filtration . Let , and let be strongly measurable with respect to . Then
The result records the conditional diagonal calculation for an increment square; its stated assumptions include only strong -measurability of , besides the probability and Brownian-filtration hypotheses.
Original Lean declaration header
Within namespace LevyStochCalc.Brownian.Ito. Shown in its original module context. Proof omitted.
lemma integral_factor_increment_sq
{P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P]
(W : LevyStochCalc.Brownian.BrownianMotion P)
(ℱ : Filtration ℝ ‹MeasurableSpace Ω›) (hℱ : IsBrownianFiltration W ℱ) {a b : ℝ} (ha : 0 ≤ a)
(hab : a < b)
{g : Ω → ℝ}
(hg_meas : @MeasureTheory.StronglyMeasurable Ω ℝ _
(ℱ a) g) :
∫ ω, g ω * (W.W b ω - W.W a ω) ^ 2 ∂P = (∫ ω, g ω ∂P) * (b - a)
Module navigation
Module: LevyStochCalc/Brownian/ItoL2CompletionConvergence.
Definition modules: LevyStochCalc/Brownian/Filtered, LevyStochCalc/Brownian/Construction.
Previous: condExp_sq_increment_of_martingale.
Source excerpt, lines 540–548 · Frozen source 408915f.
import Definitions.Def_KLSModular_LevyStochCalc_Brownian_ItoL2CompletionConvergence
/-
Copyright (c) 2026 Christian Garry. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Christian Garry
-/
-- Vendored from https://github.com/cgarryZA/LevyStochCalc at commit 984dbf0b790031eac05d56fe5a84b65e15e1e932 (upstream path LevyStochCalc/Brownian/ItoL2CompletionConvergence.lean; Apache-2.0; provenance in formalization/vendor/vendor-lock.json of the KLS repository)
open MeasureTheory
universe u
variable {Ω : Type u} [MeasurableSpace Ω]
lemma LevyStochCalc.Brownian.Ito.integral_factor_increment_sq_readable
{P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P]
(W : LevyStochCalc.Brownian.BrownianMotion P)
(ℱ : Filtration ℝ ‹MeasurableSpace Ω›) (hℱ : IsBrownianFiltration W ℱ) {a b : ℝ} (ha : 0 ≤ a)
(hab : a < b)
{g : Ω → ℝ}
(hg_meas : @MeasureTheory.StronglyMeasurable Ω ℝ _
(ℱ a) g) :
∫ ω, g ω * (W.W b ω - W.W a ω) ^ 2 ∂P = (∫ ω, g ω ∂P) * (b - a) := by sorry