Quadratic Variation in the Second-Order Term of Itô’s Lemma
Summary
The document clarifies how the second-order term in a derivation of Itô’s lemma is handled over a time interval beginning at an arbitrary time. For Brownian motion, the sum of squared increments over partitions converges in the mean-square sense to the length of the interval, regardless of the interval’s starting point. Thus the offset in the time indices does not alter the quadratic variation.
The answer gives a more standard argument for the weighted sum, where the second derivative of the function is evaluated along the process. It rewrites squared increments using changes in the square of the process and a first-order increment term, then takes the limit using the identity relating the differential of the square to the process and time. This yields an integral of the second derivative over the interval. The discussion assumes the relevant stochastic calculus conditions and does not spell out a full formal proof.
Key ideas
- Brownian motion’s quadratic variation over an interval is the interval’s length, even when that interval starts after time zero.
- The second-order Taylor contribution is a weighted sum of squared process increments.
- Rewriting squared increments through changes in the process squared supports the limiting integral argument.
- The identity for the differential of a squared process converts the limiting expression into the time integral used in Itô’s lemma.
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# Clarification on Paul Wilmott's derivation of Ito's Lemma
# Clarification on Paul Wilmott's derivation of Ito's Lemma
I'm currently self-studying to be quant and have been thoroughly enjoying PW's book. I have some questions regarding his derivation of Ito's lemma. Specifically, I can see that the first line in his expansion comes from
$$ \begin{split} (F(X(t + h)) - F(X(t))) + (F(X(t + 2h)) - F(X(t + h))) + . . . + (F(X(t + nh)) -F(X(t + (n - 1)h)))\\ = F(X(t + nh)) -F(X(t + (n - 1)h)) + F(X(t + (n - 1)h)) - ... - F(X(t + 2h)) + F(X(t + 2h))\\ - F(X(t + h)) + F(X(t + h)) - F(X(t))\\ = F(X(t + nh)) - F(X(t))\\ = F(X(t + \delta t)) - F(X(t)) \end{split} $$ By using the definition $$ \begin{split} W(t) &= \int^t_0 f(\tau)dX(\tau)\\ &= \lim_{n\to\infty}\sum_{j=1}^{n} f(t_{j-1})(X(t_j) - X(t_{j-1}))\\ &= \lim_{n\to\infty}\sum_{j=1}^{n} f((j-1)t/n)(X(jt/n) - X((j-1)t/n))\\ \end{split} $$ which I can see that the second line becomes $$ \begin{split} \sum^n_{j=1}(X(t+jh)-X(t+(j-1)h))\frac{dF(X(t+(j-1)h))}{dX} \\ = \sum^n_{j=1}(X(t+j\delta t/n)-X(t+(j-1)\delta t/n))\frac{dF(X(t+(j-1)\delta t/n)))}{dX}\\ = \int^{t+\delta t}_{t} \frac{dF}{dX}dX \end{split} $$ Finally, what I don't quite see if how the final term goes from $$ \frac{1}{2}\frac{d^2F(X(t))}{dX^2}\sum^n_{j=1}(X(t+jh)-X(t+(j-1)h))^2 $$ to $$ \frac{1}{2}\frac{d^2F}{dX^2}(X(t))\delta t $$ to then become $$ \frac{1}{2}\int^{t+\delta t}_{t}\frac{d^2F(X(\tau))}{dX^2}d\tau $$ If in the mean square limit of $n\rightarrow\infty$ for $t_j = jt/n$, $$ \sum^n_{j=1} (X(t_j)-X(t_{j-1}))^2 = \sum^n_{j=1} (X(jt/n)-X((j-1)t/n))^2 = t $$ then I don't quite see how $$ \sum^n_{j=1} (X(t+jh)-X(t+(j-1)h))^2 = \sum^n_{j=1} (X(t+j\delta t/n)-X(t+(j-1)\delta t/n))^2 = \delta t ? $$ don't they differ by a $t + $ term? Perhaps I don't see this due to my maths being rusty. And also finally, I don't see how $\frac{1}{2}\frac{d^2F(X(t))}{dX^2}\delta t$ becomes $\frac{1}{2}\int^{t+\delta t}_{t}\frac{d^2F(X(\tau))}{dX^2}d\tau$ when the integrand is also dependent on $\tau$.
## Answer by Kurt G. (score 5)
https://quant.stackexchange.com/a/68116
Given my earlier comment, the only open question is how $\frac{1}{2}\frac{d^2F(X(t))}{dX^2}\delta t$ becomes $\frac{1}{2}\int^{t+\delta t}_{t}\frac{d^2F(X(\tau))}{dX^2}d\tau\,.$ A more standard proof is this: Writing $$ t_j=t+jh $$ we have
\begin{align} &\sum_{j=1}^n\frac{d^2F}{dX^2}\Big(X(t_{j-1})\Big)\Big(X(t_j)-X(t_{j-1})\Big)^2\\ &=\sum_{j=1}^n\frac{d^2F}{dX^2}\Big(X(t_{j-1})\Big)\Big(X^2(t_j)-X^2(t_{j-1})+2X(t_{j-1})(X(t_{j-1})-X(t_j))\Big)\\ &\to\int_t^{t+\delta t}\frac{d^2F}{dX^2}\Big(X(\tau)\Big)\,dX^2(\tau)-2\int_t^{t+\delta t}\frac{d^2F}{dX^2}\Big(X(\tau)\Big)\,X(\tau)\,dX(\tau)\\ &=\int_t^{t+\delta t}\frac{d^2F}{dX^2}(X(\tau))\,d\tau\,. \end{align} The last line follows from $dX^2=2X\,dX+dt\,.$ Wilmott's approximation $$ \frac{d^2F}{dX^2}(X(t_{j-1}))=\frac{d^2F}{dX^2}(X(t)) $$ is not needed.Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.