PROBLEM
Let $U_t$ be a Brownian bridge on $[0,1]$ and let $Z$ be a standard normal random variable independent of $U_t$.
$(a)$ Prove that the process $W_t = U_t + tZ$ is a brownian motion.
$(b)$ Prove that the process $W_t = (1+t)U_{\frac{t}{1+t}}$ on $[0,\infty)$ is a Brownian motion.
I have no idea how to prove these statements, I know that a Brownian motion follows a normal distribution with $\mu = 0$ and $\sigma^2 = t$.
Can anybody please help me to prove this?
Best Answer
Let's recall that a Brownian bridge $(U_t)_{t \in [0,1]}$ is a Gaussian process with continuous sample paths, mean zero and covariance function
$$C(s,t) := \mathbb{E}(U_s \cdot U_t) = s \wedge t - s \cdot t \tag{1}$$
In order to show that $W_t := U_t+t \cdot Z$ is a Brownian motion we have to check the following properties:
Proof:
This finishes the proof of part (a). The proof of the second part is similarly, I leave it to you.