The stochastic-calculus tag has no wiki summary.

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### Joint law of the time integral of Brownian motion and its maximum

Suppose $W_t$ is a standard one dimensional Brownian motion. Let $M_t$ and $I_t$ be its running maximum and time integral, respectively:
$$M_t=\max_{0\leq s\leq t}\,W_s$$
...

**0**

votes

**1**answer

503 views

### Measure changes for gamma process

GENERAL THEORY
In his book Ken-Iti Sato ("Lévy Processes and Infinitely Divisible Distributions") provides the theory for measure change for Lévy processes in Theorems 33.1 and 33.2.
It can be ...

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**2**answers

1k views

### Generalized Ito's formula

Consider classical statement of Ito's formula: Let $X$ be a continuous
semimartingale and $F \in C^2(\mathbb{R}^d, \mathbb{R})$; then $F(X)$
is a continuous semimartingale and
$$F(X_t) = F(X_0) + ...

**5**

votes

**2**answers

449 views

### Stochastic Green-Gauss Theorem

Is there a stochastic analog for the Green-Gauss theorem? I'm looking for an expression that relates the flux (or statistical moments of the flux) through a random surface to the divergence of the ...

**2**

votes

**1**answer

496 views

### Stochastic integrals as honest martingales — exponential damping

We have a given positive martingale ρt, with the dynamics:
$$\textrm{d}\rho_t = \lambda_t \rho_t \textrm{d}W_t$$
where $W_t$ is a standard Brownian motion. Now we have an "exponentially dampened" ...

**3**

votes

**1**answer

377 views

### Stochastic integrals as honest martingales — comparison criterion

We have a given positive martingale $\rho_t$, with the dynamics:
$$\textrm{d} \rho_t = \lambda_t \rho_t \textrm{d} W_t$$
where $W_t$ is a standard Brownian motion. Now we have a "dumped" process p_t:
...

**1**

vote

**1**answer

358 views

### Positive martingale representation with jumps

I am looking for a martingale representation theorem for positive semimartingales. Using the answer to this question:
Martingale representation theorem for Levy processes
My best guess is (subject to ...

**5**

votes

**0**answers

985 views

### Levy jump measure vs. Levy measure vs. sum of jumps

This question might be a bit basic, but I am struggling to understand the connection between various versions of the Ito's lemma for Levy processes (and semimartingales in general). Could someone ...

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votes

**1**answer

616 views

### Reachability for Markov process, continuous time

Let $X$ be a strong Markov process in the continuous time with a state space $\mathbb R^n$. Consider a reachability problem for this process, i.e.
$$
v(x):=\mathsf P_x(X_t\in A\text{ for some }0\leq ...

**5**

votes

**1**answer

1k views

### Martingale representation theorem for Levy processes

Is there an equivalent of martingale representation theorem for Levy processes in some form? I believe there is no such theorem in generality, but maybe there are some specific cases?

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**1**answer

523 views

### Fractional Brownian motion and Laplacian

Having read this link on math stackexchange, I would like to submit to your wisdom the following questions.
Is it possible, mutatis mutandis, to repeat the same reasoning for a fractional Brownian ...

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vote

**1**answer

2k views

### Time-dependent Markov process: infinitesimal generator

If one talks about homogeneous Markov diffusion
$$
\mathrm dX_t = \mu(X_t)\mathrm dt+\sigma(X_t)\mathrm dw_t
$$
with $\mu,\sigma$ sufficiently differentiable and of appropriate dimensions, there is ...

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votes

**3**answers

462 views

### Stochastic Integrals and Cauchy Variables

I hope there is a straighforward literature-pointer here.
If I were interested in $\sum_{t=1}^{n} f(t) X_{t}$, where $X_{t}$ consists of independent normal random variables, I could approximate the ...

**4**

votes

**2**answers

479 views

### law of iterated logrithm

Let $(\Omega, \mathcal{F}, P)$ be a probability space, on which
$\mathcal{F}_t$ is filtration satisfying general conditions. $W_t$ is
a standard Brownian motion. By law of iterated logarithm, one has
...

**3**

votes

**1**answer

1k views

### What does progressively measurable actually entail?

There is a definition that has always left nagging questions in my mind. To set it up, let $(\Omega, \cal{A}, (\cal{F}_t)_{t\geq 0}, P)$ be a filtered probability space. From Comets & Meyre's ...

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**1**answer

797 views

### Karhunen–Loève approximation of Brownian motion and diffusions

The Karhunen–Loève theorem says that Brownian motion on the interval [0,1] can be represented as follows:
$W_t = \sum_{n=1}^\infty Z_n \frac{\sin((n-1/2)\pi t)}{(n-1/2)\pi},$
where $Z_n \sim ...

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votes

**2**answers

898 views

### Weierstrass' function and Brownian motion

Is there a known connection between Weierstrass' function
$W_\alpha (x) = \sum_{n=0}^\infty b^{- n \alpha} \cos(b^n x)$
and Brownian motion? Specifically, when $\alpha = 1/2$, the Weierstrass ...

**1**

vote

**2**answers

268 views

### Martingale part of the discontinuous put payoff

I need the martingale part of the put payoff (not $C^2$..). Where $S_t=exp(\sigma W_t -\frac{\sigma^2t}{2})$
$d[(S_t -K)^+ ]$ ??
I guess I need to use local times but how?

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vote

**0**answers

260 views

### Inverse Skorokhod Embedding Problem

The Skorokhod Embedding Problem is well known and has many documented solutions in the literature.
Now if we are given a Brownian stochastic basis (satisfying usual hypothesis), a diffusion $X_t$ ...

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vote

**1**answer

377 views

### infimum of a set of stopping times

Let $(Y^a: a\in \Lambda)$ be a set of random processes given by
$$Y^a(s) = \int_0^s \sigma^a(r) dW(r)$$
where $W$ is Brownian motion w.r.t. filtered probability space
$(\Omega, \mathcal{F}, P, ...

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votes

**1**answer

289 views

### Local continuous martingale

Hi,
This is a relatively simple result with a simple proof. However, there are 2 things I don't understand:
Why is M a brownian motion?
How is I calculated ("Thus, we get...")?
Any insight would ...

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vote

**2**answers

982 views

### The only continuous martingales with stationary increments are Brownian motions

Hi,
I know that the above statement is true, but I can't demonstrate it.
It's a pretty powerful theorem, here is its mathematical formulation:
Theorem: The only continuous martingales with ...

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**1**answer

1k views

### Martingales in both discrete and continuous setting

I am wondering, polynomials like
$S_n^4-6n S_n^2+3n^2+2n$ for $$S_n=\sum_{i=1}^n{X_i}$$ where $$\mathbb{P}(X_i=1)=\mathbb{P}(X_i=-1)=\frac{1}{2}$$ is a martingale (under the conventional filtration). ...

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**2**answers

375 views

### General question about Stochastic analysis [closed]

Dear all,
I'm wondering which university is a good choice for grad school in the field of stochastic analysis, more specifically, stochastic evolution equations.
Well, I know this is not a strict ...

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votes

**1**answer

488 views

### Exact simulation of SDE

Consider a one dimensional SDE of the form $dX_t = \mu(X_t) dt + \sigma dW_t$, where $\sigma>0$ is a constant. Under mild regularity assumptions on $\mu(\cdot)$, one can exactly simulate ...

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**1**answer

351 views

### Time-integral of a smooth, vector-valued function of a planar Brownian bridge

I'm looking for information on how to compute the distribution of the random vector
$$Z = \int_0^t f(B_s) ds$$
where $t>0$ is fixed, $B_s$ is a 2D Brownian bridge with $B_0 = 0$, $B_t=b \in ...

**0**

votes

**1**answer

457 views

### square root processes with correlated deriving Brownian motion

$$dX = \kappa_x (\theta_x - X)dt + \sigma_x \sqrt{X} \,dW_x$$
$$dY = \kappa_y (\theta_y - Y)dt + \sigma_y \sqrt{Y} \,dW_y$$
$$dW_x dW_y = \rho\, dt$$
we know that $X$ and $Y$ are marginally ...

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**1**answer

336 views

### Homogeneous linear stochastic DE with noncommuting coefficients

The system I am studying can be reduced to a Stratonovich vector
stochastic differential equation
$dX = A X \; dt + \sum B_k X \circ dW_k$
with $W_k$, $k=1..m$ the Brownian motion in $m$ dimensions, ...

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vote

**2**answers

960 views

### Change of measure Markov process

We begin with example. For the Poisson process with an intensity $\lambda_1$ there is an equivalent change of measure which makes it intensity to $\lambda_2$.
I would like to find the conditions ...

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**3**answers

345 views

### comparing diffusions

Consider a probability distribution $\pi$ on the real axis that has a density (w.r.t Lebesgue) proportional to $e^{-V(x)}$, where $V(\cdot)$ is a potential function. For any reasonable volatility ...

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**2**answers

203 views

### Has anyone found a way to determine the invariant measure of a one-dimensional jump-diffusion?

I am working with a jump-diffusion on the unit interval, with absorbing endpoints, and I was hoping someone has found a way to determine the invariant measure, similar to that of an Ito process.

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**1**answer

529 views

### Change of space-time in Walsh's stochastic integral

One can read about Walsh's construction of martingale integral in the paper (pp.16-23)
www.math.utah.edu/~davar/ps-pdf-files/SPDEBookDK.pdf
For $U,V\in \mathcal{B}(\mathbb{R}\times \mathbb{R}^+), ...

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**0**answers

197 views

### Stochastic Optimal Control - Maximizing convex terminal costs

The theory of stochastic optimal control deals with the following problem:
Find $\quad\sup\limits_{u} \; \mathrm E[g(X^{(u,x)}_T)]$
where $X^{(u,x)}_t$ solves the following controlled SDE:
...

**3**

votes

**1**answer

455 views

### Results for Hitting Times of (Not Stationary) Ito Processes

Let $W_t$ denote the Wiener process and let
$$
dX_t = a(t, X_t) dt + b(t, X_t) dW_t
$$
be an one dimensional Ito SDE (stochastic differential equation, see Ito stochastic calculus).
A hitting time ...

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votes

**3**answers

576 views

### A simple decomposition for fractional Brownian motion with parameter $H<1/2$

Background
Let $X = \{X(t):t \geq 0\}$ be a (standard, real-valued) fractional Brownian motion (fBm) with parameter $H \in (0,1)$, i.e., a continuous centered Gaussian process with covariance ...

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votes

**1**answer

256 views

### When is it possible to construct a joint law from its two-dimensional marginals?

My question is much more specific than the title:
Given a symmetric
distribution $\Xi$ on $\mathbb R^2$, when is it possible to construct a sequence $\xi_1,\xi_2,\dots$ of random variables such ...

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votes

**3**answers

1k views

### Do convex and decreasing functions preserve the semimartingale property?

Some time ago I spent a lot of effort trying to show that the semimartingale property is preserved by certain functions. Specifically, that a convex function of a semimartingale and decreasing ...

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**3**answers

6k views

### Expectation of time integral of Wiener process

I am trying to calculate $E(\int_0^T {W_s ds})$, where $W_s$ is a standard Brownian motion.
Now two approaches I can think of:
1) Take a partition of $[0,T]$. Calculate $E(\sum {W_{t_i}(t_{i+1} - ...

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**2**answers

902 views

### Brownian Motion Winding Number

Take a simple random walk $\gamma$ in the complex plane conditioned to start at point $a$ and end at point $b$. For this random walk, we can define the winding number $W_\gamma(a,b)$ around $b$ in the ...

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**1**answer

687 views

### Need help understanding Mandelbrot and Van Ness Fractional Brownian Motion

I need help understanding the Mandelbot and Van Ness' definition of Fractional Brownian motion
$
B_H( t , \omega ) - B_H( 0 , \omega ) = \frac{1}{\Gamma(H + \frac{1}{2})} \left\( \int_{-\infty}^0 ...

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**1**answer

324 views

### Stieltjes integrals of predictable processes

I am looking for a direct proof of the fact that, roughly speaking, if $S=S_0+A+M$ is an $L^2$ semimartingale, and $M$ (the martingale part) has the martingale representation property, then for any ...

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**4**answers

1k views

### Wiener process related counterexample

The Wiener process is defined by the three properties:
1. $W(0) = 0$,
2. $W(t)$ is almost surely continuous, and
3. $W(t)$ has independent increments with $W(t) - W(s) \sim N(0, t-s)$ (for $0 ≤ s ...

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**0**answers

145 views

### Characterizing polyhedron from Brownian particle collisions with a boundary

Please imagine that we have an ordinary 2-sphere, of radius $r_{sphere}$, and some three-dimensional polygon that has all of its points fixed at positions strictly internal to the sphere's surface. ...

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244 views

### Relation between regularities of the trajectory of a mean zero gaussian process and its covariance operator

Let $\xi_t$ be a zero-mean gaussian process on $[0,1]$ with covariance operator $C$.
I would like to better understand the relation between the covariance operator and the regularity of the ...

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**1**answer

613 views

### Taylor expansion to show that for Stratonovich stochastic calculus the chain rule takes the form of the classical one

As nobody seems to be able to give any kind of answer to that problem over there at math.stackexchange I post this question here:
How can I show with a heuristic argument based on a Taylor expansion ...

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**0**answers

293 views

### Change of Time in Stochastic Integral

Hi everyone,
Let's be given $I(0,t)$ a Stochastic Integral with respect to a local martingale $ M_t$ of the form :
$I(0,t)=\int_0^t h(s_-)dM_s$ with $h\in L(M)$ (for example $h$ is an adapted ...

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226 views

### Density of Dolean exponentials in L2 and Wiener Measure

Assume that W is the classical Wiener space C([0,1],R) note $\mu$ the Wiener measure, and denote by $\mu_s$ the image of $\mu$ under the maping $T: W ->W$ such that$ T(w)= \sqrt(s) w$ . Denote by ...

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**3**answers

403 views

### Continuity in intial state of Brownian Motion

$ B = (B_t, \mathcal{F}_t; t\ge 0 ) $ is a 1-d Brownian family on a
measurable space $(\Omega, \mathcal{F})$ with a family of probability
measures $\{\mathbb{P}^x\}$, i.e. $\mathbb{P}^x(B_0
= x) = 1$, ...

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votes

**1**answer

794 views

### Distribution of running maximum of a local martingale

Let $(\Omega, \mathcal{F}, \mathbb{P}, \mathcal{F}_t)$ be a given
probability space with usual conditions, on which $W$ is a standard
Brownian motion. For $x \ge 0$, consider
$$X(t) = x + \int_0^t ...

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**1**answer

378 views

### Approximation of the law of a stochastic process

Hello Dear fellows,
I thank you in advance for your help and ideas.
I have just read an article and want you to help me understand the rational behind a part of it.
We have two processes $v_t$ and ...