We have defined the stochastic integral for a finite variation, continuous adapted process A, and H a previsible process. We want to extend this to integrals with respect to continuous local martingales. Analogous to defining the Lebesgue integral by extending linearly from indicator functions, we define integrals of simple processes with respect to martingales. A simple process is a disjointly (time-)supported linear combination of the canonical previsible process . It will be convenient to demand that the variables of integration are in . Then the space is preserved under this integral operation, that is , and in particular

By Doob’s inequality, , so it makes sense to define as the set of cadlag adapted processes s.t. . Of particular interest is that is complete, by finding limits for subsequences and lifting to the whole sequence by Fatou.

We aim to construct integrals over by taking limits of integrals over . For this space, we have that is not just but in fact a UI true martingale. Then, as a natural extension of the orthogonality trick (remembering that ), we obtain

We then define for the norm by with the space of H s.t. that this is finite. Then for , we have the Ito isometry:

with

Now, we also have S dense in . Why? We know linear combinations of are dense, so it STP . Use a typical Dynkin’s lemma argument on , which contains -system generating . So extend to generally. We recover the original motivating result that . Take a sequence of stopping times reducing both H and M to force boundedness of integrand, and . Stopping the integral is equivalent to stopping the integrand, and checking limits in stopping times allows us to lift the Ito Isometry result to this one about quadratic variations.