Conditional Expectation based on Stopping Times

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Let $S$ and $T$ be stopping times with respect to the filtration $\{\mathcal{F}_n\}_{n \in \mathbb{N}}$. I want to show that for an integrable random variable $Y$, $$E(E(Y|\mathcal{F}_S)|\mathcal{F}_T) = E(Y|\mathcal{F}_{S \wedge T})$$

Clearly $\mathcal{F}_{S \wedge T} = \mathcal{F}_{T} \cap \mathcal{F}_{S}$ so that $\forall A \in \mathcal{F}_{S \wedge T}$, we have $$ E(E(E(Y|\mathcal{F}_S)|\mathcal{F}_T)1_A) = E(E(Y|\mathcal{F}_S)1_A) = E(Y1_A)$$

where the first equality follows since $A \in \mathcal{F}_T$ and the second follows from $A \in \mathcal{F}_S$ and applying the definition of conditional expectation.

Thus it suffices to show that $Z \equiv E(E(Y|\mathcal{F}_S)|\mathcal{F}_T)$ is $\mathcal{F}_{S \wedge T}$ measurable. I know that the sets $\{S<T\}$ and $\{S \ge T\}$ are both in $\mathcal{F}_S \cap \mathcal{F}_T$, so we may write for any Borel set $B$

$$\{Z \in B\} \equiv C = (C \cap \{S \ge T\}) \cup (C \cap \{S < T\})$$

Because $C \in \mathcal{F}_T$ by definition of cond. expectation, we have $C \cap \{S \ge T\} \cap \{S \wedge T \leq n\} = C \cap \{S \ge T\} \cap \{T\leq n\} \in \mathcal{F}_n \forall n$ so that $C \cap \{S \ge T\} \in \mathcal{F}_{S \wedge T}$.

Finally I just need to show $C \cap \{S < T\} \in \mathcal{F}_{S \wedge T}$ which is something I have been incapable of doing thus far. Any ideas?

(For reference, this is from Jacod and Protter exercise 24.11)

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One approach to this issue is to consider the uniformly integrable martingale defined by $M_n:=E(Y\mid \mathcal F_n)$. The stopped process $K_n:=M_{n\wedge S}$ is also a UI martingale, with terminal value $K_\infty=\lim_{n\to\infty}K_n=M_S=E(Y\mid\mathcal F_S)$. And $E(K_\infty\mid\mathcal F_T)=K_T$, to finish.