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A stochastic process is a collection of random variables usually indexed by a totally ordered set.
0
votes
Accepted
Is the number of uncrossing invariant under time-change?
We have $U_{a,b}^T(Y) = U_{a,b}^{h(T)}(X)$.
By construction, the function $h$ maps $[0,T]$ onto $[0,h(T)]$. More precisely, each $t' \in [0,h(T)]$ can be written $h(h^\leftarrow(t'))$,
where $h^\lefta …
0
votes
Is integral of adapted separable process adapted?
Partial answer
The question may be whether the process $f$ is progressively measurable under the assumptions. If yes, we can conclude as follows.
Fix $t \ge 0$. For each $\omega$, $f(\cdot,\omega)$ is …
1
vote
Solution to SDE conditional on high maxima of driving Brownian motion
Partial answer
First, an heuristic argument. When we condition by events with low probability, the main is given by behaviour the less improbable situation. Here we condition by $S_1 := \max_{0 \le s …
4
votes
Accepted
Enlargement of filtration
I think that I have a counterexample. Let $(X,Y)$ be a Brownian motion in $\mathbb{R}^2$. Then $M = \int_0^\cdot X_s \mathrm{d}Y_s$ is a martingale, in the natural filtration of $(X,Y)$, in its own fi …
1
vote
Accepted
Can an a.s. non constant continuous martingale be differentiable with nonzero probability?
Almost surely, we can write for every $t \ge 0$, $M_t=M_0+\beta_{\langle M,M \rangle_t}$, where $\beta$ is some Brownian motion.
By Kahane's theorem, almost surely, for every $s \ge 0$, $\limsup_{\del …
2
votes
Density of $W_t$ assuming it stayed above a line $L$
As I mentionned in my comment, there is an ambiguity in the statement of you question.
Anyway, if $B$ is a standard one dimensional Brownian motion, if $\lambda$ is a real number, then $(B_t-\lambda t …
3
votes
Another curious martingale
Partial answer. Continuous (local) martingales are time-changed Brownian motion.
A way to obtain funny local martingales which also are Markov processes is to start from a Brownian motion $B$ and its …
3
votes
Accepted
Brownian bridges as conditioning
If $X$ and $Y$ are independent random variables taking values in arbitrary spaces $E$ and $F$, if $Z = f(X,Y)$ for any measurable map $f : E \times F \to G$, then the family of distributions of the ra …
2
votes
Integrated square difference of Brownian bridges
For every Gaussian centered process $X$, if one takes an independent copy $X'$, then the process $X+X'$ has the same distribution as $\sqrt{2}X$ (to see that, compare their finite dimensional marginal …
0
votes
Accepted
Phase space Brownian bridge
I use capital letters for random variables and small letters for possible values.
Let $W$ be a brownian motion, defined on the canonical space $\mathcal{C}(\mathbb{R}_+)$ endowed with the Wiener measu …
1
vote
Accepted
Example of random walk in a random environment (RWRE) saying things on the environment
An example: Matzinger studied the revocery of the environment from the second factor of a RWRE.
https://arxiv.org/pdf/1110.6853.pdf
https://matzi.math.gatech.edu/overview.pdf