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Natural and usual augmented Brownian filtrations
Definition
Assume the Axiom of Choice. Let be a standard Brownian motion on a probability space Brownian motion. First replace the ambient space by its completion, retaining the notation for this extension. This is supplied by Assuming countable choice, every measure space has a unique complete extension to its completion; AC supplies its countable-choice hypothesis by AC supplies countable selections and prescribed serial paths. The coordinate functions, their laws, and their raw sigma-algebras are unchanged. Four families are distinguished.
- Raw natural filtration. for , and . Both sigma-algebras exist by Nonempty intersections of sigma-algebras are sigma-algebras, so the generated sigma-algebra exists and is minimal, and is a continuous-time filtration in the sense of Continuous-time filtrations and all-pairs martingales, the smallest one to which is adapted. It contains no completion and no right-continuous augmentation.
- Raw right limit. for . At this is the germ sigma-algebra used later on this page; the uncountable intersection is the decreasing intersection over the rational , since is increasing. No null sets are adjoined in this operation.
- Ambient null ideal and completed raw filtration. Let be the family of all subsets of ambient -null events. These sets are ambient-measurable because the ambient probability space was completed. This is a sigma-ideal: for a countable family choose null envelopes using AC, then take their union; subsets require the same envelope. Nullness follows from Null sets are closed under countable unions and, in a complete space, under arbitrary subsets. Put Each is a sub-sigma-algebra of , contains every member of , and for , so is a filtration.
- Usual augmentation. for .
The following facts are part of the definition and are the form in which it is used later.
(a) for every , and every contains . (b) is increasing and right-continuous: for every , Indeed, if , fix and take . Then . Since was arbitrary, . Conversely gives , because is increasing and the intersection defining ranges over the larger parameter set , so . (c) Every completed set differs from a raw set by a null set. Let Then is a sigma-algebra containing : complementation preserves symmetric difference, and, after selecting countably many witnesses by AC, Thus . Conversely, if , then , so . This proves equality, and also ambient measurability of every . In particular, for one has for such an , and for every integrable real or complex , by Two integrable functions are equal almost everywhere exactly when all of their indefinite integrals agree applied to and . Apply it to indicators for the measure equality. If , its raw representative is null, so is contained in an ambient null envelope. Every subset of therefore belongs to . This proves completeness of each . It also proves completeness of : a null member belongs to and hence all its subsets belong to . Thus every ambient null event and every one of its subsets belongs already to ; together with right-continuity, this is the usual-conditions convention used below. (d) The four families , , and are kept distinct in every statement below. The strong Markov theorem is stated for and the deterministic Markov theorems are stated for both and ; the companion examples page carries a counterexample showing that in the canonical realization.
The raw filtration remains raw even though the ambient measure has been completed; no null set is removed from . Choice is used for the completion theorem and the countable witnesses above, and is also inherited from the ambient Brownian construction.
Source notes
Sousi, Definition 6.10 (printed p. 54), defines the natural filtration and its raw right limit; it does not supply the completion construction. Completion is supplied by the declared measure-space theorem, with the ambient-null-ideal convention and the symmetric-difference description proved above. These distinctions are needed when moving between completed events and raw representatives in the later Markov and zero-one arguments.
Depends on
- Brownian motion
- Continuous-time filtrations and all-pairs martingales
- Nonempty intersections of sigma-algebras are sigma-algebras, so the generated sigma-algebra exists and is minimal
- The Axiom of Choice
- Assuming countable choice, every measure space has a unique complete extension to its completion
- Null sets are closed under countable unions and, in a complete space, under arbitrary subsets
- Two integrable functions are equal almost everywhere exactly when all of their indefinite integrals agree
- AC supplies countable selections and prescribed serial paths
Used by
- Cadlag Brownian-filtration local martingales have continuous versions Corollary
- Heat-semigroup martingales Corollary
- One-dimensional Brownian motion is recurrent Corollary
- Square-integrable Brownian terminal variables have Ito representations Corollary
- A nonadapted step integrand breaks the Ito isometry Counterexample
- An unbounded stopped exponential martingale needs uniform integrability Counterexample
- Strong Markov fails at a nonstopping random time Counterexample
- The raw natural Brownian filtration need not be right-continuous Counterexample
- Elementary predictable Brownian integrands Definition
- The Brownian germ sigma-algebra at zero Definition
- Expected exit time from an interval Example
- Harmonic functions of planar Brownian motion Example
- Hitting probabilities from an exponential martingale Example
- Logarithm of geometric Brownian motion Example
- Successive Brownian exit segments are independent copies Example
- Brownian closed-set hitting times are stopping times Lemma
- Raw versus usual filtrations in the strong Markov theorem Remark
- Blumenthal's zero-one law Theorem
- Brownian reflection principle Theorem
- Brownian-filtration martingale representation Theorem
- Future-path Markov property Theorem
- Markov property of Brownian motion Theorem
- Quadratic covariation of Brownian Ito processes Theorem
- Strong Markov property of Brownian motion Theorem
- The Brownian zero set has no isolated points Theorem
- Two-sided Brownian exit probability Theorem
Dependency tree · two levels
29 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Perla Sousi, Advanced Probability, Definition 6.10 (standard reference, not scraped)
- Rick Durrett, Probability: Theory and Examples, fifth edition, Section 7.2 (standard reference, not scraped)