proof of measurability of stopped processes
Let (ℱt)t∈𝕋 be a filtration (http://planetmath.org/FiltrationOfSigmaAlgebras) on the measurable space
(Ω,ℱ), τ be a stopping time, and X be a stochastic process
. We prove the following measurability properties of the stopped process Xτ.
If X is jointly measurable then so is Xτ.
Suppose first that X is a process of the form Xt=1A1{t≥s} for some A∈ℱ and t∈𝕋. Then, Xτt=1A∩{τ≥s}1{t≥s} is ℬ(𝕋)⊗ℱ-measurable. By the functional monotone class theorem, it follows that Xτ is a bounded ℬ(𝕋)⊗ℱ-measurable process whenever X is. By taking limits of bounded processes, this generalizes to all jointly measurable processes.
If X is progressively measurable then so is Xτ.
For any given t∈𝕋, let Y be the ℬ(𝕋)⊗ℱt-measurable process Ys=Xts=Xs∧t. As τ∧t is ℱt-measurable, the result proven above says that (Xτ)t=Yτ∧t will also be ℬ(𝕋)⊗ℱt-measurable, so Xτ is progressive.
If X is optional then so is Xτ.
As the optional processes are generated by the right-continuous and adapted processes then it is enough to prove this result when X is right-continuous and adapted. Clearly, Xτ will be right-continuous. Also, X will be progressive (see measurability of stochastic processes) and, by the result proven above, it follows that Xτ is progressive and, in particular, is adapted.
If X is predictable then so is Xτ.
By the definition of predictable processes, it is enough to prove the result in the cases where Xt=1A1{t>s} for some s∈𝕋 and A∈ℱs, and Xt=1A1{t=t0} where t0 is the minimal element of 𝕋 and A∈ℱt0.
In the first case, Xτt=1A∩{τ>s}1{t>s} is predictable and, in the second case, Xτt=1A1{t=t0}+1A∩{τ=t0}1{t>t0} is predictable.
Title | proof of measurability of stopped processes |
---|---|
Canonical name | ProofOfMeasurabilityOfStoppedProcesses |
Date of creation | 2013-03-22 18:39:03 |
Last modified on | 2013-03-22 18:39:03 |
Owner | gel (22282) |
Last modified by | gel (22282) |
Numerical id | 4 |
Author | gel (22282) |
Entry type | Proof |
Classification | msc 60G05 |