Stopped Process is Adapted Stochastic Process
Theorem
Let $\struct {\Omega, \Sigma, \sequence {\FF_n}_{n \ge 0}, \Pr}$ be a filtered probability space.
Let $\sequence {X_n}_{n \ge 0}$ be an $\sequence {\FF_n}_{n \ge 0}$-adapted stochastic process.
Let $T$ be a stopping time with respect to $\sequence {\FF_n}_{n \ge 0}$.
Let $\sequence {X_n}_{n \ge 0}$ be a $\sequence {\FF_n}_{n \ge 0}$-adapted process.
Let $\sequence {X_n^T}_{n \ge 0}$ be the stopped process.
Then $\sequence {X_n^T}_{n \ge 0}$ is a $\sequence {\FF_n}_{n \ge 0}$-adapted process.
Proof
Let $n \in \Z_{\ge 0}$.
From Constant Function is Stopping Time, $n$ is a stopping time.
From Pointwise Minimum of Stopping Times is Stopping Time, $n \wedge T$ is a stopping time, where $\wedge$ is the pointwise minimum.
From Adapted Stochastic Process at Stopping Time is Measurable with respect to Stopped Sigma-Algebra, we have:
- $X_{n \wedge T}$ is $\FF_{n \wedge T}$-measurable
where $\FF_{n \wedge T}$ is the stopped $\sigma$-algebra associated with $n \wedge T$.
We have by the definition of pointwise minimum:
- $n \wedge T \le n$
From Stopped Sigma-Algebra preserves Inequality between Stopping Times and Stopped Sigma-Algebra of Constant Stopping Time coincides with Filtration, we have:
- $\FF_{n \wedge T} \subseteq \FF_n$
So:
- $X_{n \wedge T}$ is $\FF_n$-measurable.
So:
- $\sequence {X_n^T}_{n \ge 0}$ is a $\sequence {\FF_n}_{n \ge 0}$-adapted process.
$\blacksquare$