ไน ้ขไธ¶
1.¶
(1): \(B(h(t))\sim \mathcal{N}(0,h(t))\implies E B(h(t))=0, Var B(h(t))=h(t)\).
(2): \(\forall t\). \(X(t)\) ไธบๆญฃๆ่ฟ็จ, ไธ \(E{X}(t)=0\). \(Var X(t)=h(t)\). ๆ \(B(h(t)) \overset{d}{=} X(t)\).
(3): ๅ ่ฎก็ฎ 2-็ปดๆ ่ดใ $$ \text{Cov}(X(s),X(t))=E\left(\frac{st}{h(s)h(t)}\right)^{-1/2}B(s)B(t)=\sqrt{\frac{h(s)h(t)}{st}}s $$
\(\forall k .0<t_1<\cdots<t_k\).
ไป่ๅฝไธไป ๅฝ \(h(t)=ct\) ๆถๅๅๅธใ
2.¶
(1): \(EX(t)=a e^{-\alpha t},Var X(t)=\sigma^4 t\).
(2): \(\forall t_1<t_2<\cdots<t_k\).
ๆ ไธบๆญฃๆ่ฟ็จใ
(3): \(X(t)-X(s)=a e^{-\alpha t}-a e^{-\alpha s}+\sigma^2 B(t-s)\).
็ฌ็ซไธๅนณ็จณ
3¶
ๅทฒ็ป็ฅ้ \(M(t)\overset{d}{=} |B(t)|\).
4¶
\(Y(t)=\int_0^t(x+\mu s+\sigma B(s)) d s=x t+\frac{1}{2} \mu t^2+\sigma \int_0^t B(s) d s\)
\(\implies EY(t)=xt+\frac12 \mu t^2\)
\(Var Y(t)=\sigma^2 \int_0^t\int_0^tEB(u)B(v)dudv=\frac13 \sigma^2t^3\)
5¶
\(Y(t)=\int_0^t B(s)ds\sim \mathcal{N}(0,\frac{t^3}{3})\)
\(\implies EX(t)=Ee^{Y(t)}=\int_R e^y \frac{1}{\sqrt{2 \pi \frac{1}{3} t^3}} e^{-\frac{y^2}{\frac{2}{3} t^3}} d y=e^{t^3 / 6}\)
6¶
\(\tau_a=\inf \{t:X(t)=a \} \overset{d}{=} \inf\{ t:B(t)=\ln\frac{a}{x} \}\)
\(\implies P(\tau_a=t)=f_{\tau_a}(t)=\frac{|\ln\frac{a}{x}|}{\sqrt{2\pi t^3}} e ^{ -\frac{(\ln\frac{a}{x})^2}{2t}}\)
\(\implies E\tau_a=\infty\)
7¶
ไปค \(F(u)\) ไธบๅ ถๅๅธๅฝๆฐ