The conditional expected value of Brownian motion $B(t)$ given $B(s)$, $s\leq t$, as well as $B(1)$

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I am trying to calculate the expected value of the increment of Brownian motion $B(t+h)-B(t)$ given the enriched filtration generated by both $B(s)$,$s\leq t$, as well as $B(1)$.

Now as $B(t)$ is measurable with respect to this filtration obviously I can take that out of the expectation. What I'm having trouble figuring out is calculating the expected value of $B(t+h)$ given both its past as well as $B(1)$.

Any help appreciated. I have the formula

$\mathbb{E}[X|Y] = (\mathbb{E}[XY]/\mathbb{E}[Y^2])\cdot Y$ but I haven't been able to apply it successfully.