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9
votes
1answer
702 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 ...
4
votes
2answers
859 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
2answers
264 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?
1
vote
0answers
258 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 $X_t$ ...
1
vote
1answer
367 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, ...
0
votes
1answer
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 ...
1
vote
2answers
938 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 ...
9
votes
1answer
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). ...
2
votes
2answers
364 views

General question about Stochastic analysis

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 ...
5
votes
1answer
479 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 ...
4
votes
1answer
349 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
1answer
454 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 ...
4
votes
1answer
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, ...
1
vote
2answers
923 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 ...
5
votes
3answers
343 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 ...
2
votes
2answers
202 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.
6
votes
1answer
522 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}^+), ...
0
votes
0answers
194 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
1answer
435 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 ...
6
votes
3answers
561 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 ...
7
votes
1answer
254 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 ...
17
votes
3answers
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 ...
1
vote
3answers
5k 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} - ...
6
votes
2answers
860 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 ...
1
vote
1answer
671 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 ...
5
votes
1answer
322 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 ...
13
votes
4answers
996 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 ...
3
votes
0answers
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. ...
4
votes
2answers
242 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 ...
2
votes
1answer
601 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 ...
1
vote
0answers
284 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 ...
0
votes
0answers
223 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 ...
4
votes
3answers
399 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. $\mathbb{P}^x(B_0 = x) = 1$, ...
4
votes
1answer
762 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 ...
3
votes
1answer
373 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 ...
15
votes
4answers
4k views

Intuition and/or visualisation of Ito integral/Ito's lemma

Riemann-sums can e.g. be very intuitively visualized by rectangles that approximate the area under the curve. See e.g. Wikipedia:Riemann sum The Ito integral has due to the unbounded total variation ...
3
votes
2answers
737 views

Is the truncated Brownian motion of the class DL?

Let $W$ be a standard Brownian motion under given probability space. For a given constant $a$, $W^a$ is a truncated Brownian motion by stopping time $T^a = \inf(t>0:W(t) = a)$. That is, $W^a(t) = ...
2
votes
0answers
291 views

Finding jump probabilities from mean-occupancy values for positions on a one-dimensional random walk

Please imagine a discrete random walk on a one-dimensional lattice. The lattice consists of a set of $L$ positions, $(x_0, x_1, ..., x_L) \in L$, where $x_0$ is the initial position of the walk (as ...
2
votes
2answers
850 views

Examples of deterministic processes of quadratic variation which are of unbounded variation

In [Föllmer 81] (English translation to be found here) writes: "The class of processes of quadratic variation is clearly larger than the class of semimartingales: Just consider a deterministic process ...
1
vote
3answers
861 views

Föllmer: “Calcul d'Ito sans probabilités” in English or German?

Does anybody know a translation of Föllmer: Calcul d'Ito sans probabilités in English or German? It seems to be a very interesting text - Abstract: "It is shown that if a deterministic continuous ...
5
votes
2answers
240 views

how to sample a conditioned diffusion

there are several reasons why we could be interested in sampling conditioned diffusions: if we observed a diffusion at discrete time and want to do some kind of inference on the parameters of the ...
2
votes
1answer
876 views

Stationary Solutions of stochastic differential equations

When does the stationary density of an homogeneous Markov process exist?
3
votes
1answer
312 views

initial condition of a diffusion approximation

I am trying to prove that a certain sequence of Markov chains $x^N_k$ converges towards a diffusion process. The invariant measure of $x^N$ is $\pi^N$ and the Markov chain $x^N$ is started in ...
6
votes
1answer
2k views

Big picture concerning Ito integral, Stratonovich integral and standard results in probability theory

I am confused and don't get the big picture concerning the connection between Ito integral Stratonovich integral Standard results in probability theory concerning skewed distributions. Example: ...
4
votes
0answers
458 views

Dynamic programming principle (DPP)

In stochastic control problem, one shall use the measurable selection theorem to prove DPP. It was discussed in discrete time case in [Bertsekas and Shreve 1978]. Is there unified framework in ...
0
votes
1answer
429 views

Looking for a version of Itô's Lemma

Hi Everyone I have some difficulties deriving the Stochastic Differential Equation for the following problem, any help or reference would be appreciated. We are given a Brownian Motion $B_t$ and ...
1
vote
2answers
251 views

Problem with a Long Range Correlated Time Series

Consider a stochastic process $X_t$ , $t \in 1,2,3,..,N $. $X_t$ is a Bernoulli variable and $\Pr(X_t=1) = p$ for all $t$. The Autocovariance function $\gamma(|s-t|)= E[(X_t - p)(X_s -p)]$ is given ...
3
votes
2answers
361 views

Systematization of deterministic and stochastic integrals

With this question I try to build up a systematization of different kinds of integrals. The following table differentiates between deterministic and stochastic integrals, the summation processes ...
16
votes
5answers
2k views

Brownian motion and spheres

Consider a Brownian motion on $[0;1]$. A (finite) discrete approximation of this Brownian motion consists of $N$ iid Gaussian random variables $\Delta W_i$ of variance $\frac{1}{N}$: $$ ...
9
votes
2answers
2k views

Convergence and non-convergence of left-point and mid-point Riemann sums

In standard calculus it is a well known fact that left-point and mid-point Riemann sums do become equal in the limit. When it comes to stochastic integration this is no longer the case. Taking the ...