Expectation of a stochastic process

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Ok, I'm new to stochastic calculus and I'm having some troubles with a simple exercise that I don't seem to get. Here it is:

Recalling that $\mathbb{E}[e^{W_t}]=e^{\frac{t}{2}}$ compute $\mathbb{E}[e^{W_t}|\mathcal{F}_s]$, with $s\leq t$.

Now the expectation that I'm supposed to remember is simply an expectation of a lognormal distribution with mean zero and variance $t$. I don't get the second point: how can the introduction of filtration affect the expected value? I would appreciate an explanation as general as possible, in order to avoid having problems with similar exercises even in the future... thanks!

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$\mathbb{E}[e^{W_t}|\mathcal{F}_s]$

$=\mathbb{E}[e^{W_s}e^{W_t - W_s}|\mathcal{F}_s]$

$=e^{W_s} \mathbb{E}[e^{W_t - W_s}|\mathcal{F}_s]$ (why?)

$=e^{W_s} \mathbb{E}[e^{W_t - W_s}]$ (why?)

Now note that $W_t - W_s$ is a random variable distributed $N(0, t-s)$.

Do you remember moment generating functions?


As to how filtration can affect expectation, in general:

$E[X|Y] \neq E[X]$

where Y can be an event, random variable, $\sigma$-algebra or filtration.

Do you remember conditional expectation?