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Stephan Sturm's user avatar
Stephan Sturm's user avatar
Stephan Sturm's user avatar
Stephan Sturm
  • Member for 13 years
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Can an a.s. non constant continuous martingale be differentiable with nonzero probability?
@jlewk: While the argument is formally correct, I do not think it is useful here. A Lipschitz martingale is of bounded total variation, hence of zero quadratic variation. So the only martingales satisfying this conditions are constants anyway.
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Explicit solution for a simple SDE?
A maybe useful reformulation of the SDE can be found in Lemma 3.1 of the following paper: Sven Rady. Option Pricing in the Presence of Natural Boundaries and a Quadratic Diffusion Term. Finance & Stochastics 1, 331-344 (1997)
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Is a stopped Ito-integral integrable if the Ito integrand is only square-integrable on an open interval?
You might also try to look up “suicide strategy” in the financial math literature. It is intimately tied to this problem as well as the classic (D. Bernoulli in the 18th century) St. Petersburg paradox.
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Is a stopped Ito-integral integrable if the Ito integrand is only square-integrable on an open interval?
Consider a time change $u = Log(T-t)$. Then this is equivalent to that Brownian motion hits 1 in finite time.
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Question about the exit time of a time-homogeneous Itô diffusion
I tried to address your question by expanding my answer.
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Question about the exit time of a time-homogeneous Itô diffusion
Added material addressing the question in the comment
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Is there solution to a backward stochastic differential equation with $yz$ in the generator?
And I suspect that there might be problems. At least the natural bound $2yz \leq y^2 + z^2$ will not work as the heat equation with quadratic nonliearity blows up (see, e.g., Evan's PDE book, section 9.4). Thus if there is an existence for the solution, the argument might be quite subtle.
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Is there solution to a backward stochastic differential equation with $yz$ in the generator?
If $a(u)$, $b(u)$ would be random processes, the according Feynman-Kac formula would be in a three dimensional state space $(x,a,b)$. But I think one has first to understand what is happening in easy (but not trivial) model cases. If the solution doesn't exist there, we cannot expect much in general.
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Is there solution to a backward stochastic differential equation with $yz$ in the generator?
Just a quick note: Looking at the "simple" case where $\xi = W_T$ this can be seen as FBSDE which (assuming Feynman-Kac) should correspond to the semilinear PDE $-u_t + \frac{1}{2}u_{xx} = uu_x$. A quick search in Polyanin-Zaitsev didn't produce any results.
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Does the linear combination of the quantile $\alpha F^{-1}(\tau)+\beta G^{-1}(\tau)$ still a quantile
Indeed, doesn't any right-continuous nondecreasing function $g$ with domain $[0,1]$ define a quantile function? (Just check that $g(U)$, for $U$ a standard uniform random variable defines a random variable with cdf $g^{-1}$, the (right-) generalized inverse function of $g$)?
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Meaning of $. \wedge t$ (. \wedge t) in stochastic analysis
The first one that you take the whole path (which is then taken only up to t thanks to the minimum and stays from there on constant). The norm is a norm on the path space. The second one that this is the end of the sentence (period).
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