Adapted and progressively measurable processes #
This file defines some standard definition from the theory of stochastic processes including filtrations and stopping times. These definitions are used to model the amount of information at a specific time and are the first step in formalizing stochastic processes.
Main definitions #
- MeasureTheory.Adapted: a sequence of functions- uis said to be adapted to a filtration- fif at each point in time- i,- u iis- f i-strongly measurable
- MeasureTheory.ProgMeasurable: a sequence of functions- uis said to be progressively measurable with respect to a filtration- fif at each point in time- i,- urestricted to- Set.Iic i × Ωis strongly measurable with respect to the product- MeasurableSpacestructure where the σ-algebra used for- Ωis- f i.
Main results #
- Adapted.progMeasurable_of_continuous: a continuous adapted process is progressively measurable.
Tags #
adapted, progressively measurable
A sequence of functions u is adapted to a filtration f if for all i,
u i is f i-measurable.
Equations
- MeasureTheory.Adapted f u = ∀ (i : ι), MeasureTheory.StronglyMeasurable (u i)
Instances For
Progressively measurable process. A sequence of functions u is said to be progressively
measurable with respect to a filtration f if at each point in time i, u restricted to
Set.Iic i × Ω is measurable with respect to the product MeasurableSpace structure where the
σ-algebra used for Ω is f i.
The usual definition uses the interval [0,i], which we replace by Set.Iic i. We recover the
usual definition for index types ℝ≥0 or ℕ.
Equations
- MeasureTheory.ProgMeasurable f u = ∀ (i : ι), MeasureTheory.StronglyMeasurable fun (p : ↑(Set.Iic i) × Ω) => u (↑p.1) p.2
Instances For
A continuous and adapted process is progressively measurable.
For filtrations indexed by a discrete order, Adapted and ProgMeasurable are equivalent.
This lemma provides Adapted f u → ProgMeasurable f u.
See ProgMeasurable.adapted for the reverse direction, which is true more generally.