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A stochastic process is a collection of random variables usually indexed by a totally ordered set.
1
vote
1
answer
231
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Under which conditions does Malliavin derivative and Lebesgue integral commute?
So the title is quite self-explanatory,
suppose we have a stochastic process $(X_t: t\in[0,T])$ where for a fixed $t$, $X_t$ is a $\mathbb R$-valued square integrable random variable, we could even as …
0
votes
0
answers
137
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Space derivative of Brownian local time
Let $\{L_x(t):(t,x)\in [0,T]\times\mathbb R\}$ be the local time of a Brownian motion $(B_t)_{t\in [0,T]}$, I know that the map $x\mapsto L_x(t)$ is $\alpha$-Hölder for $\alpha<1/2$ (uniformly in time …
10
votes
2
answers
2k
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Show that this process is not a martingale
I am cross-posting this question from MSE since I did not received any answer, furthermore I tried asking some professors in my university but still we could not find an answer.
The most surprising th …
1
vote
0
answers
295
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Gaussian measures on infinite dimensional spaces
On Zabczyk & Da Prato book about infinite dimensional SDEs they introduce the idea of Gaussian measures in infinite dimensional Banach spaces. They do so by means of Fernique theorem.
In the White No …
2
votes
0
answers
47
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Continuity of translation operator in fractional white noise analysis
Fix $H\in(\frac{1}{2},1)$, and let $\Omega:=C_0([0,T],\mathbb R^d)$ be the space of $\mathbb R^d$-valued continuous functions. There is a probability measure $P^H$ on $(\Omega,\mathcal B(\Omega))$, s …
2
votes
2
answers
233
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Reference request (Brownian local time): for fixed $t$, $a\mapsto L_a(t)$ is a.s. continuous...
So the title is quite self explanatory.
In the book "Continuous Martingales and Brownian Motion" by Rebuz and Yor, in the proof of Proposition $(2.1)$ of chapter XIII it's stated that:
For fixed $t$ …