What is the Ito-Doeblin Formula?

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The Ito-Doeblin formula states that the differential of Brownian motion, dW(t), satisfies the equation dW(t)dW(t) = dt. This result arises from the behavior of higher-order terms in stochastic calculus, which vanish when summed over partitions as dt approaches zero. The relationship W_t = √t B, where B is a standard normal variable, helps illustrate this concept. Specifically, the expected values of higher powers of the increments of Brownian motion, such as E[|δW_t|^3], indicate that these terms are of smaller order than dt. Consequently, in the limit, only the first-order term remains significant, validating the formula.
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Reading through a proof on why the higher order terms vanish and it makes this statement

dW(t)dW(t) = dt

where W(t) is a Brownian motion

It is not obvious to me why this is the case, but the text seems to infer that it is because no further explanation is offered
 
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It may have to do with W_t=\sqrt{t} B where B is N(0,1).
 
\delta W_t \sim N(0,t). It follows that E[(\delta W_t)^2]=\delta t and E[|\delta W_t|^3]={\rm const}\times \delta t^{3/2}. So third and higher powers of dW are smaller order than dt on average , and therefore vanish if you sum them over a partition and let dt->0.
 
I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...
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