When does $\int_0^t dX_s = X_t-X_0$ hold for a stochastic process?

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So I am learning stochastic calculus and I have seen this relationship be used many times: $$ \int_0^t dX_s = X_t-X_0 $$ where $X_t$ is some stochastic process.

It looks like some sort of application of the fundamental theorem of calculus, but is it? And does this hold for any stochastic process?

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The definition of an Itō stochastic integral $ \int_0^t H_s \; dX_s$ (with respect to a semimartingale $X_t$) is the limit of $\sum_{j=1}^n H_{t_{j-1}} (X_{t_j} - X_{t_{j-1}})$ for partitions $0 = t_0 \le t_1 \le \ldots \le t_n= t$ of $[0,t]$ with mesh size going to $0$. For $H = 1$ the sum telescopes to $X_t - X_0$. So in this case the identity follows directly from the definition.

Similarly for the Stratonovich integral, and essentially any reasonable kind of stochastic integral that is defined using a limit of "Riemann sums".