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Definition
StochasticDiffsStochasticProcesses

A random time on (Ω,F,P)(\Omega,\mathcal{F},P) with values in N\mathbb{N} is a measurable mapping T:ΩN{+}ωT(ω)\begin{align*} T:&\Omega\to \mathbb{N}\cup \{ +\infty \}\\ &\omega \mapsto T(\omega) \end{align*}

Let (Xn)nN(X_{n})_{n\in\mathbb{N}} be (Fn)nN(\mathcal{F}_{n})_{n\in\mathbb{N}}-adapted and let TT be a (Fn)nN(\mathcal{F}_{n})_{n\in\mathbb{N}}-stopping time. Then XT is a Random VariableX_{T}\text{ is a Random Variable}and XT is FT-measurableX_{T}\text{ is }\mathcal{F}_{T}\text{-measurable}

Let (Xt)t0(X_{t})_{t\ge 0} be (Ft)t0(\mathcal{F}_{t})_{t\ge 0}-adapted and let TT be a (Ft)t0(\mathcal{F}_{t})_{t\ge 0}-stopping time. Assume (Xt)t0(X_{t})_{t\ge 0} is right continuous (respectively left) then XT1{T<} is FT-measurableX_{T}\mathbb{1}_{\{ T<\infty \}}\text{ is }\mathcal{F}_{T}\text{-measurable}where XT1{T<}={0T(ω)=+XT(ω)(ω)T(ω)<X_{T}\mathbb{1}_{\{ T<\infty \}}=\begin{cases} 0 & T(\omega)=+\infty \\ X_{T(\omega)}(\omega) & T(\omega)<\infty \end{cases}or if TT is bounded then XT is FT-measurableX_{T}\text{ is }\mathcal{F}_{T}\text{-measurable}

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