stochastic processes - Why does the short rate in the Hull White model follow a normal distribution?

Consider Hull White model $dr(t)=[\theta(t)-\alpha(t)r(t)]dt+\sigma(t)dW(t)$ when we solve the SDE above we have $r(t)=e^{-\alpha t}r(0)+\frac{\theta}{\alpha}(1-e^{-\alpha t})+\sigma e^{-\alpha t}\int_{0}^{t}e^{\alpha u}dW(u)$ and when we take expectation and variance we have $r(t) \sim N(e^{-\alpha t}r(0)+\frac{\theta}{\alpha}(1-e^{-\alpha t}),\frac{\sigma^2}{2\alpha}(1-e^{-\alpha t}))$.

I know the calculate how find SDE and find expectation or variance but I don't understand why $r(t)$ has normal distribution.

thanks.

Answer

For simplicity, we assume that $\alpha$ is a positive constant. You need to show that, for any $t>0$,

$$\begin{align*} M_t = \int_0^t e^{\alpha u} dW_u \end{align*}$$ is normally distributed, where $\{W_t, \, t \ge 0\}$ is a standard Brownian motion with respect to the filtration $\{\mathscr{F}_t,\, t \ge 0\}$. Here, we employ the time-changed Brownian motion technique. For $t\ge 0$, let $\mathscr{G}_t = \mathscr{F}_{\frac{1}{2}\ln(1+2t)}$. Consider the process $X=\{X_t, t \geq 0\}$, where $$\begin{align*} X_t = \int_0^{\frac{1}{2}\ln(1+2t)} e^{\alpha u} dW_u. \end{align*}$$ Then $X$ is a continuous martingale with respect to the filtration $\{\mathscr{G}_t,\, t \ge 0\}$. Moreover, $$\begin{align*} \langle X, X\rangle_t &= \langle M, M\rangle_{\frac{1}{2}\ln(1+2t)}\\ &=\int_0^{\frac{1}{2}\ln(1+2t)} e^{2u} du =t. \end{align*}$$ By Levy's martingale characterization of Brownian motion, $\{X_t, t \ge 0\}$ is a Brownian motion. That is, for $t >0$, $X_t$ is normally distributed. Consequently, for any $t >0$, $$\begin{align*} M_t &= \int_0^t e^{\alpha u} dW_u\\ &=X_{\frac{1}{2}(e^{2t}-1 )} \end{align*}$$ is normally distributed, and $r_t$ is also normally distributed.