隨機微積分

Baxter & Rennie HJM:微分 Ito 積分

  • March 1, 2019

來自 Baxter 和 Rennie,第 138 頁:

$$ f(t,T)=\sigma W_t+f(0,T)+\int_0^t\alpha(s,T)ds $$ $$ Z_t=\exp-\bigg(\sigma(T-t)W_t+\sigma\int_0^tW_sds+\int_0^Tf(0,u)du+\int_0^t\int_s^T\alpha(s,u)ds\bigg) $$ $$ dZ_t=Z_t\bigg(-\sigma(T-t)dW_t-\bigg(\int_t^T\alpha(t,u)du\bigg)dt+\frac{1}{2}\sigma^2 (T-t)^2dt\bigg) $$ 伊藤引理將如何應用在這裡?

我努力了:

$$ Z_t=\exp-\bigg(\sigma(T-t)W_t+\sigma\int_0^tW_sds+\int_0^Tf(0,u)du+\int_0^t\int_s^T\alpha(s,u)ds\bigg)=e^{-X_t} $$ $$ X_t=\sigma(T-t)W_t+\sigma\int_0^tW_sds+\int_0^Tf(0,u)du+\int_0^t\int_s^T\alpha(s,u)ds $$ $$ \begin{align} dX_t &=\sigma(T-t)W_t-\sigma W_tdt+\sigma(W_tdt-W_0d0)+f(0,T)dT-f(0,0)d0+\bigg(\int_t^T\alpha(t,u)du\bigg)dt-\bigg(\int_t^T\alpha(0,u)du\bigg)d0\ &=\sigma(T-t)W_t+f(0,T)dT+\bigg(\int_t^T\alpha(t,u)du\bigg)dt \end{align} $$ $$ \begin{align} dZ_t&=-Z_tdX_t+\frac{1}{2}Z_t(dX_t)^2\ &=Z_t\bigg(-\sigma(T-t)W_t-f(0,T)dT-\bigg(\int_t^T\alpha(t,u)du\bigg)dt+\frac{1}{2}\sigma^2(T-t)^2dt\bigg) \end{align} $$ 有幾個問題是我寫的 $ d0 $ 我有 $ f(0,T)dT $ 其餘的。我確實認為我已經正確應用了 Ito 的引理,問題在於 $ dX_t $ .

任何幫助表示讚賞。

$$ Z_t = \exp(-X_t) $$ 和 $$ X_t = \sigma(T-t)W_t+\sigma\int_0^tW_sds+\int_0^Tf(0,u)du+\int_0^t\int_s^T\alpha(s,u)du ds $$ 和 $ W_t $ 一個標準的布朗運動,以及通常的假設。 我們可以寫 $ X_t=f(t,W_t) $ 並應用伊藤引理得到:

$$ dX_t = \frac{\partial f}{\partial t}(t,W_t) dt + \frac{\partial f}{\partial W_t} (t,W_t) dW_t + \frac{1}{2}\frac{\partial^2 f}{\partial W_t^2}(t,W_t) d \langle W, W \rangle_t $$ $$ \begin{align} \frac{\partial f}{\partial t}(t,W_t) &= -\sigma W_t + \sigma W_t + \int_t^T \alpha(t,u) du\ \frac{\partial f}{\partial W_t}(t,W_t) &= \sigma(T-t)\ \frac{\partial^2 f}{\partial W_t^2}(t,W_t) &= 0\ \end{align} $$ 我們使用萊布尼茨積分規則(見這裡)來表示積分項的時間導數,特別是以下: $$ \begin{align} \partial_t \int_0^t \underbrace{\int_s^T \alpha(s,u) du}{\tilde{\alpha}(s,T)} ds &= \partial_t \int_0^t \tilde{\alpha}(s,T) ds \ &= \int_0^t \underbrace{\partial_t \tilde{\alpha}(s,T)}{=0} ds + \underbrace{\partial_t(t)}{=1} \tilde{\alpha}(t,T) - \underbrace{\partial_t(0)}{0} \tilde{\alpha}(0,T) \ &= \tilde{\alpha}(t,T) \ &= \int_t^T \alpha(s,u) du \end{align} $$ 總結起來,為該過程產生以下差異 $ X_t $ $$ dX_t = \left(\int_t^T \alpha(t,u) du\right) dt + \sigma(T-t) dW_t $$ 從中可以推斷 $$ d\langle X, X\rangle_t = \sigma^2(T-t)^2 dt $$ 最後,將伊藤引理應用於連續半鞅 $ Z_t = \tilde{f}(t,X_t) = \exp(-X_t) $ $$ \begin{align} dZ_t &= - Z_t dX_t + \frac{1}{2} Z_t d\langle X, X \rangle_t \ &= Z_t \left( \left(\frac{1}{2} \sigma^2(T-t)^2 - \int_t^T \alpha(t,u) du \right)dt - \sigma(T-t) dW_t \right) \end{align} $$

引用自:https://quant.stackexchange.com/questions/30631