[Math] Smallest $\sigma$-algebra and $\sigma$-algebra generated by a function

measure-theoryprobability theory

I'm reading through the following theorem:

Let $X=\{X_t,t\in T\}$ be a stochastic process. Then $\sigma (X)=\sigma ( \cup_{t\in T} \sigma (X_t))$

From my basic knowledge of measure theory, I know $\sigma (S)$ as the smallest $\sigma$-algebra containing the system of subsets $S$. In probability theory we're defining $\sigma (X) $ as the $\sigma$-algebra generated by the random variable $X$
(Definition: Let $X:(\Omega , $ $\mathcal{A}$ $ )\rightarrow (S,$ $\mathscr{S} $ $ )$ then we define $\sigma(X)=\{[X\in B], B\in $ $\mathscr{S} $ $\}$ )

That's where the confusion comes in:

a) What is the connection between those two (if there is any) ?

b) In the theorem, is the equality then "The $\sigma$-algebra generated by $X$ equals to the smallest $\sigma$-algebra containing the union of $\sigma$-algebras generated by the $X_t$ ?

Thank you.

Best Answer

  1. By definition, $\sigma(X)$ denotes the smallest $\sigma$-algebra such that $X$ is measurable, i.e. $$\sigma(X) = \{X^{-1}(B); B \in \mathscr{S}\}. \tag{1}$$ Define $$S = \{C; \exists B \in \mathscr{S}: C = f^{-1}(B)\}.$$ Note that $S$ is a $\sigma$-algebra as a pre-image $\sigma$-algebra; therefore, $$\sigma(X) \stackrel{(1)}{=} S = \sigma(S).$$
  2. Yes, this is a correct. Another one: "The $\sigma$-algebra generated by $X$ equals the smallest $\sigma$-algebra such that $X_t$ is measurable for any $t \in T$."