Substituting Itô Differential Expressions Inside Stochastic Integrals
Summary
The document asks why an Itô differential equation can be multiplied by a process inside a stochastic integral. It considers a process whose increments are represented by a Brownian term and a drift term, then asks whether the same decomposition holds after weighting those increments by another process.
The answer motivates the substitution through discretized increments: multiply each step by the integrand, sum across steps, and take the limits that define the integrals. This connects the symbolic differential notation to the definition of integration with respect to an Itô process. The explanation points to the relevant definition in Shreve’s text but does not give a full proof or spell out technical conditions, such as integrability requirements on the weighting process.
Key ideas
- An Itô differential equation represents a relationship among process increments and their integral limits.
- Multiplying discretized increments by an integrand motivates the corresponding weighted integral identity.
- The resulting integral with respect to an Itô process can be defined using its Brownian and time components.
- A rigorous justification depends on the integration framework and conditions on the integrand.
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# Justification for substituting "Itô differentials"
# Justification for substituting "Itô differentials"
I'm reading Shreve's Stochastic Calculus for Finance, Volume II. In it, he uses the stochastic differential notation. For example, he may write
$$\mathrm{d}X(t) = \sigma(t)\mathrm{d}W(t)+\alpha(t)\mathrm{d}t\tag{ 1}$$
to mean (formally)
$$\int_{t=s_0}^{t=s_1}\mathrm{d}X(t) = \int_{t=s_0}^{t=s_1}\sigma(t)\mathrm{d}W(t)+\int_{t=s_0}^{t=s_1}\alpha(t)\mathrm{d}t\text{.}\tag{2}$$
This is fine and makes sense. The problem is that he will often substitute the LHS of $(1)$ for the RHS of $(1)$ in other stochastic differential equations. For example, given the function $S(t)$, he may use $(1)$ to justify the equality
$$S(t) \mathrm{d}X(t) = S(t)\sigma(t)\mathrm{d}W(t)+S(t)\alpha(t)\mathrm{d}t\text{,}\tag{3}$$
which is equivalent to
$$\int_{t=s_0}^{t=s_1} S(t) \mathrm{d}X(t) = \int_{t=s_0}^{t=s_1} S(t)\sigma(t)\mathrm{d}W(t)+\int_{t=s_0}^{t=s_1} S(t)\alpha(t)\mathrm{d}t\text{.}\tag{4}$$
This trick appears to be purely symbolic. Intuitively, it makes sense. However, I am having trouble proving that you can make this substitution. Is there a proof that you can make these kinds of substitutions (in this example or in general)?
## Answer by ir7 (score 1, accepted)
https://quant.stackexchange.com/a/63658
I don't see where in the book Shreve justifies (3) directly from (1). But he would have almost surely referred to the discretized versions of the "differentials". That is:
$$ X(t_{i+1})-X(t_{i}) \approx \sigma(t_i)(W(t_{i+1})-W(t_{i}))+\alpha(t_{i})(t_{i+1}-t_{i}) $$
implies $$ S(t_{i})(X(t_{i+1})-X(t_{i})) \approx S(t_{i})\sigma(t_i)(W(t_{i+1})-W(t_{i}))+S(t_{i})\alpha(t_i)(t_{i+1}-t_{i}). $$
We would then take summations and limits (needed in an integration mechanism) on both sides and justify why a stochastic integral wrt to an Ito process integrator can be defined as in (4), which is Definition 4.4.5 in the book, given after Shreve had already defined stochastic integrals wrt to $W(t)$ and $t$ integrators.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.