The properties that model a Wiener process are:
- $Z(0)=0$
- $Z(t)$ is almost everywhere contrinuous.
- $Z(t)$ occurs in independent increments.
- $Z(t)-Z(s)\sim \mathcal N(0, t-s)$ for all $0\leqslant s < t)$
So you are looking at:
$\begin{align}\Bbb E[Z(2)\,Z(4)]
\tag 1 & = \Bbb E[~\Bbb E[Z(2)\,Z(4)\mid Z(2)]~]
\\[1ex] \tag 2 & =\Bbb E[~ Z(2)\,\Bbb E[Z(4)\mid Z(2)]~]
\\[1ex] \tag 3 & = \Bbb E[~ Z(2) \times Z(2)~]
\\[1ex] \tag 4 & = \Bbb E[~Z^2(2)~]\end{align}$
Step $1$ is the Law of Total Epectation. What you have listed is the interior part of the nested expectation: $$\Bbb E[Z(2)\,Z(4)\mid Z(2)]$$
Step $2$ is that $\mathsf E(XY\mid X)=X~\mathsf E(Y\mid X)$, since when measured against $X$, a factor of $X$ itself can be distributed out of the operator. So: $$Z(2)\,\Bbb E[Z(4)\mid Z(2)]$$
Step $3$ is just evaluating the conditional expectation; $\Bbb E[Z(4)\mid Z(2)]= Z(2)$.
$$\begin{align} &\qquad \Bbb E[Z(4)\mid Z(2)] \\[1ex] &=~ \Bbb E[Z(2)\mid Z(2)]+\Bbb E[Z(4){-}Z(2)\mid Z(2)] &&\text{Linearity of Expectation} \\[1ex] &=~ Z(2)+\Bbb E[Z(4){-}Z(2)\mid Z(2)] && \text{Since }\mathsf E(X\mid X)=X \\[1ex] &=~ Z(2)+ \Bbb E[Z(4){-}Z(2)] && \text{Wiener process occurs in independent increments}\\[1ex] &= ~ Z(2)+0 &&\text{Because } Z(4){-}Z(2)\sim \mathcal N(0, 2) \end{align}$$
Step $4$ is just multiplying the factors.$$Z^2(2)$$
Then take the expectation of that to conclude that $$\Bbb E[Z(2)\;Z(4)] = \mathbb E[Z^2(2)]$$
From here recall again that $Z(2)\sim\mathcal N(0;2)$ so therefore: $\mathbb E[Z^2(2)]= 2$
https://math.stackexchange.com/q/2288421/446754
Thanks a lot!
– Nehal May 20 '17 at 00:25