Why Brownian Motion Requires Itô Integration
Summary
The document explains why ordinary Riemann–Stieltjes integration generally cannot integrate a continuous process against Brownian motion. It compares left-endpoint and right-endpoint sums for the integral of Brownian motion against itself. Their difference is the sum of squared increments, which has expectation equal to elapsed time rather than tending to zero as the partition is refined. Since the sums do not agree, the classical integral is not defined in this example.
The explanation connects this failure to Brownian paths having infinite total variation. For continuous integrands, finite variation of the integrator controls the relevant Riemann–Stieltjes sums; continuous local martingales with finite variation are constant, so nontrivial ones fall outside that framework. The document then gives the Itô integral identity for this example, which includes a time correction. This is an introductory illustration, not a full treatment of stochastic integration or the conditions for more general integrands.
Key ideas
- Brownian paths have infinite variation, so the usual finite-variation condition for Riemann–Stieltjes integration fails.
- Left- and right-endpoint sums for the Brownian self-integral differ by squared increments.
- The expected difference remains equal to elapsed time as partitions are refined.
- The Itô integral is a distinct integration notion and gives a time-corrected result in this example.
- A continuous local martingale with finite variation must be constant.
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# Brownian motion and Stochastic Integration
# Brownian motion and Stochastic Integration
I have two questions relating stochastic integration which perhaps could be answered together.
First question:
First of all, I don't really understand why we can't use Riemann-Stieltjes integration when a Brownian motion is the integrator (has something to do with its infinite variation but I don't see how that affects the integral).
Second Question:
For the second question (I think the more general case), we first need to define the following spaces
$$ \begin{align} M_{0, loc}^{c} &:= \text{Space of all continuous local martingales } (M_{t})_{t \in [0, T]} \text{ with } M_{0} = 0 \\ FV_{0}^{c} &:= \text{Space of all adapted stochastic processes } (A_{t})_{t \in [0, T]} \text{ with } A_{0} = 0 \\& \hspace{0.6cm} \text{ and continuous sample paths of finite variation} \end{align} $$
Now, I have the following lemma:
Every continuous local martingale $(M_{t})_{t \in [0, T]}$ with sample paths of finite variation is constant. In particular, one has $M_{0, loc}^{c} \cap FV_{0}^{c} = \{0 \}.$
This lemma allegedly is responsible, that we cannot construct the integrals with respect to martingales based on classical Riemann-Stieltjes integration. I don't really see why this is the case either.
I hope you understand my questions and are able to answer them.
Best regards,
Peter
## Answer by Kevin (score 4, accepted)
https://quant.stackexchange.com/a/53909
Let's take a standard Brownian motion $(B_t)$ and let's try to compute $\int_0^t B_s\mathrm{d}B_s$ in the Riemann-Stieltjes sense.
Let $0=t_0<t_1<...<t_n=t$ be a partition and let $y_i=t_{i-1}$ or $y=t_i$ for $i=1,...,n$ be two intermediate partitions. Thus, \begin{align*} S^1_n(t) &= \sum_{i=1}^n B_{t_{i-1}}(B_{t_i}-B_{t_{i-1}}), \\ S^2_n(t) &= \sum_{i=1}^n B_{t_{i}}(B_{t_i}-B_{t_{i-1}}), \end{align*} are Riemann-Stieltjes sums.
If the Riemann-Stieltjes integral exists, $S_n^1(t)-S_n^2(t)\to0$ as $\max\limits_{i=1,...,n}\{t_i-t_{i-1}\}\to0$. However, \begin{align*} S^2_n(t)- S^1_n(t)&= \sum_{i=1}^n (B_{t_i}-B_{t_{i-1}})^2 >0 \end{align*} and \begin{align*} \mathbb{E}[S^2_n(t)- S^1_n(t)]&= \sum_{i=1}^n (t_i-t_{i-1})=t \neq 0. \end{align*} Thus, the Riemann-Stieltjes integral does not exist for a Brownian motion as integrator.
In general, the Riemann-Stieltjes integral $\int_0^t f(s)\mathrm{d}g(s)$ exists if $f$ is piecewise continuous and $g$ has finite variation.* However, as you said, the sample paths of Brownian motion have infinite variation (yet finite quadratic variation). Your lemma states that every non-trivial continuous local martingale has infinite variation, as well. Thus, we have to use a new integral notion, Itô's integral. In fact, $\int_0^t B_s\mathrm{d}B_s=\frac{1}{2}(B_t^2-t)$ in the Itô sense.
*To prove this, we take a partition $0=t_0<t_1<...<t_n=t$ and choose $y_i^-$ such that $$f(y^-_i) = \begin{cases} \inf\limits_{t_{i-1}\leq y\leq t_i} f(y) &\mathrm{if}\; g(t_i)-g(t_{i-1})\geq0, \\ \sup\limits_{t_{i-1}\leq y\leq t_i} f(y) &\mathrm{if}\; g(t_i)-g(t_{i-1})<0, \end{cases} $$ and choose $y_i^+$ such that $$f(y^+_i) = \begin{cases} \sup\limits_{t_{i-1}\leq y\leq t_i} f(y) &\mathrm{if}\; g(t_i)-g(t_{i-1})\geq0, \\ \inf\limits_{t_{i-1}\leq y\leq t_i} f(y) &\mathrm{if}\; g(t_i)-g(t_{i-1})<0, \end{cases}.$$ Let \begin{align*} S^+_n(t) &= \sum_{i=1}^n f(y_i^+)(g(t_i)-g(t_{i-1})), \\ S^-_n(t) &= \sum_{i=1}^n f(y_i^-)(g(t_i)-g(t_{i-1})). \end{align*} Then, the Riemann-Stieltjes integral exists if $S^+_n(t)-S^-_n(t)\to0$ as $n\to\infty$.
However, if $\max\limits_{i=1,...,n} \{t_i-t_{i-1}\}\leq \delta$ for some $\delta>0$, then \begin{align*} S^+_n(t)-S^-_n(t) &\leq \sum_{i=1}^n |f(y_i^+)-f(y_i^-)||g(t_i)-g(t_{i-1})| \\ &\leq \sup\{|f(y)-f(y')| : y\geq0; y'\leq t,\;|y-y'|<\delta\} \sum_{i=1}^n |g(t_i)-g(t_{i-1})| \\ &\to 0, \end{align*} if $f$ is continuous (first term goes to zero) and $g$ has finite variation (the sum doesn't blow up). This, of course, also works if $f$ is piecewise continuous, we merely need to split up the integral domain.
This is the reason why we need finite variation for $g$! Otherwise, the Riemann-Stieltjes integral is simply not well-defined.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.