Questions on the calculus of stochastic processes, or processes that have a random component.

learn more… | top users | synonyms

0
votes
1answer
39 views

Stopping time problem - Show that T is bounded

Let $a< 0 < b$ and $W_t$ is Brownian motion $T_a$=inf{$t\ge$0|$W_t\le a$} $T_b$=inf{$t\ge$0|$W_t\ge b$} T=min{$T_a$,$T_b$} $1)$ Show that $T$ $<$ $\infty$ My attempt : ...
1
vote
1answer
36 views

How to calculate the value of $E[X^4], E[X^6],E[X^8] $…?

I learned that when X is a normal random variable , $X$~ $N(0,1)$ , $E[X^2]=1$ $E[X^4]=1.3=3$ $E[X^6]=1.3.5=15$ $E[X^8]=1.3.5.7=105$ For the general case , when variance is s , how do you do ...
0
votes
1answer
84 views

Simple integral with stochastic Brownian motion integrand

Consider $$\int_0^t \sin(B_s) ds$$ where $B_s$ is standard Brownian motion, I was wondering can I write $$\int_0^t \sin(B_s) ds = - ( \cos(B_t) - \cos(B_0)) = - \cos(B_t) ? $$ by using the ...
0
votes
0answers
43 views

The relationship of $\sigma(f(X))$ and $X$

If X is a random variable and f is a measurable function, 1) Is f(X) measurable with $\sigma(X)$ ? 2) Is X measurable with $\sigma(f(X))$ ? Please give proof & example or counter example. Ok ...
1
vote
1answer
32 views

Can I make the substitution of dP when using the CDF?

Random variable $X \geq 0$ with parameter $\lambda>0$ and $X$ has the c.d.f. $$ F (a) = P{(X ≤ a)} = 1 − \exp(−λa)$$ for $a \geq 0$. Consider $Z = (λ'/λ)\exp(-(λ'-λ)X)$ Show that $E[Z]=1$ thus ...
0
votes
1answer
44 views

Stochastic Integration and Ito Calculus

Before reading this I must not I think I am a little behind on some of the prereq for this topic but I really want to be able to understand it in a relatively meaningful way. I am having trouble ...
1
vote
1answer
18 views

Non-interacting particles

Suppose $X(t)$ is a Markov chain taking values in $\{0,1\}^2$. Suppose $q$ is the q matrix whose positive valued entries are $q((0,0),(1,0)) = \beta_{0}$ $q((1,0),(0,0)) = \delta_{0}$ ...
0
votes
1answer
17 views

Please explain $E[S_{min(n,T)} ]= E [S_{0}]=0$

If $S_{n}$ is a simple random walk i.e $X_{k}= +/- 1$ with prob = 0.5 T = inf {n > = 0 |$S_{n}$ = 1} is a stopping time. T is finite almost surely. .Explain $E[S_{min(n,T)} ]= E [S_{0}]=0$ I know ...
0
votes
0answers
25 views

Maximal principle for elliptic or linear integro-differential operator

Consider $L$ the operator forming as $$ Lg= -g^{'}(x)+(g(x+1)-g(x)) $$. $h$ on $[0,\infty)$ satisfies the following integro-differential equation $$ Lh \geq 0 $$ with boundary condition: $$ ...
1
vote
1answer
30 views

Integrating the difference of brownian motion

I'm reading the solutions to an exercise where it is stated that $$\int_t^T\Big(W(u) - W(t)\Big)du = \int_t^T (T-u)dW(u).$$ But can someone enlighten me to what theorem/rule can be used to show this? ...
0
votes
0answers
20 views

Show that $ \text{ess-sup}_\Omega g (x+ B_T) = \sup_{y \in \mathbb R ^d }g(y)$

Show that $$ \text{ess-sup}_\Omega g (x+ B_T) = \sup_{y \in \mathbb R ^d }g(y)$$ where $B$ is a d-dimentional brownian motion , $x \in \mathbb R ^d $ and g a Lipschitz bounded function of $\mathbb R ...
4
votes
1answer
87 views

Approximation of stochastic processes in Protter

I'm reading Stochast integration and stochastic differential equation by Protter. In particular I have a question about Theorem 10 in chapter 2.4. Here Protter defines a simple predictable processes ...
0
votes
1answer
51 views

Markov processes and semimartingales

Semimartingales and Markov processes are two fundamental families in probability theory. There are many specific processes that belongs to the intersection of those two families, e.g. Levy processes. ...
1
vote
0answers
42 views

Stochastic Differential Equation- When martingale?

Suppose I'd like to check the martingale property for some SDE. What do I have to require for it to be martingale? I know that no drift is one requirement, but what are the others?
0
votes
1answer
23 views

Strictly increasing maps

For $p\ge n$, how many strictly increasing maps from $N^*_n$ to $N^*_p$ do exist, where $N^*_n = \{1, 2, \dots, n\}$ is the set of the first $n$ integers greater than 0 ? My answer: uncountable many. ...
0
votes
0answers
46 views

If two stochastic integrands are equal on some measurable set, will the stochastic integrals be equal on that set?

Given a $X$ semi-martingale on a filtered probability space $(\Omega,\{\mathcal F_t\}_{t\le\infty},P)$ I am trying to prove: For any $B\in\mathcal F_\infty$ and processes $a_1,a_2$ such that ...
1
vote
3answers
54 views

The uniqueness of solution for stochastic differential equation involved with sign function.

When I read a paper about Levy distribution thoerem (http://www.maphysto.dk/publications/MPS-RR/1998/22.pdf). In the first page, the author mentioned the following: There is a unique strong solution ...
0
votes
1answer
47 views

Independence random variables

I found two theorems in my notes and they seem to be somewhat complementary which made me doubt that both of them are true: a) Let $X,Y: \Omega \rightarrow \mathbb{R}$ be a measurable function and ...
2
votes
1answer
65 views

Diffusion processes

I am trying to work out a problem to which I have not found similar solutions on the website. Perhaps you can help me out. Let $X = (X_t)_{t\geq0}$ be a non-negative diffusion process which solves ...
1
vote
0answers
12 views

Reference or Intuition on a Stochastic Equation (Klyatski-Tatarski formula)

I am working through an already not so easy to find paper from the 70s, which in turn uses an even older result that i can not find at all. Im refering to ...
0
votes
0answers
44 views

Martingale and Stochastic equation

Using the Ito formula, I can show that the martingale $$ Z_{t}=\frac{1}{\sqrt{1-t}}\exp -\frac{B_t^2}{2(1-t)}\qquad 0\leq t<1 $$ admits the following differential $$ dZ_t=-\frac{B_t}{1-t}Z_tdB_t. ...
2
votes
1answer
67 views

Distribution of Stopped Brownian motion at hitting time of another Brownian motion.

Suppose $B_t$ and $W_t$ are two independent Brownian motions and $\tau$ is the first hitting time of $B_t$ to some $a >0$. Compute the distribution of $W_{\tau}$. We can try the characteristic ...
0
votes
1answer
42 views

A few questions about Stochastic Processes and Numerical Methods

I am having a few problems understanding the Ornstein Uhlenbeck solutions, on wikipedia under solution (http://en.wikipedia.org/wiki/Ornstein%E2%80%93Uhlenbeck_process) it described using variation of ...
0
votes
1answer
69 views

Distribution of ceiling function and absolute value of random variable

Given a distribution function $f_X$, where $X$ is some random variable. I want to get the distribution functions of $|X|$ and $\lceil X \rceil$( the last one may only have an easy form if $X$ is ...
1
vote
1answer
33 views

Unbiased estimate $\lambda^2$

Given a Poisson distribution I want to figure out whether $d:(x_1,...,x_n) \mapsto x_1^2$ and $d':(x_1,...,x_n) \mapsto x_1x_2$ are unbiased estimations for $\lambda^2$ ? I mean it would sound ...
0
votes
1answer
84 views

Proof that a median minimizes 1-norm. [duplicate]

I was wondering whether there is an easy way to show the following: We have a data set $x_1,...,x_n$ and $m$ is a median if for at least half of the n data points we have that $x_i \le m$ and for ...
4
votes
0answers
91 views

Determine if this is a Martingale

I am trying to check if the process $S_t$ is a martingale, where $\mathrm dS_t = \frac{I_{S_t > 0}}{S_t} \mathrm dW_t$, $S_0 = 1$. We know that $S_t$ is a local martingale because if we stop it ...
3
votes
1answer
116 views

Sum of two Markov processes another Markov process?

Let $dX_{t} = m_1(l_1-X_{t})dt+\sigma_1 dW_{t}$ and $dY_{t} = m_2(l_2-Y_{t})dt+\sigma_2(\rho dW_{t}+\sqrt{1-\rho^2}dW_{t}^{1})$ where the $m_i$'s, $l_i$'s and $\sigma_i$'s are constants, $\rho \in ...
0
votes
1answer
42 views

Quadratic variation - Semimartingale

We know that any Semimartingale has Quadratic variation. I am interested to know if the converse is also true i.e. if a process has quadratic variation then it is semimartingale. Can some one ...
1
vote
1answer
99 views

Correlation between two stochastic processes [closed]

Let $$dX_t = k_1 X_t \, dt + \sigma_1 \, dW_t$$ and $$dY_t = k_2 Y_t \, dt + \sigma_2 \left( \rho \, dW_t + \sqrt{1-\rho^{2}} \, dW_t^1\right)$$ where $W_t$ and $W_t^1$ are independent. What is ...
0
votes
0answers
42 views

Log normal stock prices - Steps after Ito

When we specify a GBM stock price: $$dS = \mu S dt + \sigma S dW$$ And then we change it to: $$\frac{dS}{S} = \mu dt + \sigma dW$$ The we assume: let $Z_t = f(S_t) = \log S_t$, where $f(x) = \log ...
2
votes
1answer
133 views

Convergence in distribution ( Two equivalent definitions)

I read that for convergence in distribution it is equivalent to have that either the characteristic functions of the random variables convergence pointwise or we have that $F_{X_n} \rightarrow F_{X}$ ...
0
votes
0answers
33 views

Differential of the integral of a stochastic process

In the HJM model one considers the forward rates to be on the form $$\mathrm df(t,T) = \alpha(t,T)\,\mathrm dt + \sigma(t,T)\,\mathrm dW(t)$$ In the proof of showing the drift condition on $\alpha$ ...
1
vote
1answer
56 views

First hitting time in the one-dimensional case by solving a boundary value problem

If have a question about section 3.1 in the paper Kramers' law: Validity, derivations and generalisations by Nils Berglund. (See http://arxiv.org/abs/1106.5799 page 7 - 9) On page 8 it says, that ...
0
votes
1answer
44 views

Computation of a simple stochastic integral

For $t \in [0,T]$. consider two stochastic integrals with a nonnegative constant integrand $c$ $$\mathbb{E} \left[ \int_0^{t(\omega)^* \wedge T} c \cdot dW_t \right]$$ where $t^*$ is random ...
0
votes
1answer
43 views

Is any FV-Process a special Semimartingale?

Any FV-Process can be represented as the difference of two increasing (or decreasing) processes and so any FV-Process is a quasimartingale. Due to Raos Theorem any FV-Process is a special ...
1
vote
1answer
50 views

lower bounds for a stochastic integral

for all $t \in [0,T]$, consider a stochastic integral as follows: $\int_0^{min \{t^*,T \}} f(t,\omega) dt$ where $f \geq 0$ is a nonnegative stochastic process and $t^*$ is a random stopping time. I ...
1
vote
1answer
74 views

Proof that the predictable sigma algebra is also generated by continuous and adapted processes

I'm reading George Lowther's blog and have a question about the proof of lemma 2. We want to verify that the predictable sigma algebra is also generated by the continuous and adapted processes. One ...
0
votes
1answer
30 views

Distribution of integral wrt. to a Levy process

Assume that a stochastic process is given by $X_{t} = \int_0^t e^{-k(t-s)}dY_{s}$ where $Y_{s}$ is a Levy process. Is there any way I can use the knowledge about the Levy measure of $Y_{t}$ in ...
2
votes
0answers
107 views

Clarification in stochastic integration

In the book "Stochastic Processes" by Bass R.F. when he constructs the Stochastic Integral, at some point he defines for $Y$ predictable $$||Y||_2= \left(\mathbb E \int_0^{\infty}Y_t^2\text{d} \langle ...
0
votes
1answer
194 views

Expected value of Stock Price, Poisson Process

I would appreciate a hint regarding the following question (taken from Durret, Essentials of Stochastic Processes, questions 2.38 "Let $S_t$ be the price of stock at time t and suppose that at times ...
1
vote
1answer
50 views

Why $\int _0 ^t \phi_s ^2 ds < \infty \ \mathbb P \text{-a.e.}$ do not implies $\mathbb E [\int _0 ^t \phi_s ^2 ds] < \infty$?

Why $\phi =(\phi_t)_{t \in [0,T]}$ is a progressive mesurable stochastic process do not implies $\mathbb E [\int _0 ^t \phi_s ^2 ds] < \infty$? I know that if $X$ is a positive random variable ...
4
votes
2answers
219 views

Intuition for random variable being $\sigma$-algebra measurable?

Is there some sort of intuition or a good ilustrative example for random variables being $\sigma$-algebra measurable? I understand the definition, but when looking at martingales, the meaning of ...
-1
votes
1answer
14 views

Ito's lemma for a boolean

If I have a stochastic process defined as usual by $dx=f(x,t)dt+g(t,x)dW$, how can I compute the Ito's formula for a process $n=\phi(t,x):=(x/t>a)$, i.e., $dn = (\ldots)dt + _\ldots$ ? I have ...
3
votes
1answer
94 views

Strictly stationary exponential Ornstein-Uhlenbeck process?

Can one define the initial value of the exponential Ornstein-Uhlenbeck process $r$, defined by $$r(t) = e^{y(t)}\quad\text{with}\quad dy(t) = k(θ −y(t)) \mathrm dt+\sigma \mathrm dW(t),$$ such that ...
0
votes
0answers
25 views

Evaluation of $\mathbb E[\int _{t_1} ^{t_2} f(s, X_s^{t,x} )ds \mid \mathcal F _{t_1} ]$ for a markovian SDE solution.

Given a probability space $(\Omega, \mathcal F , \mathbb P)$, a filtration $\mathbb F = (\mathcal F _t )_{t\geq 0}$ and $\mathbb F$-adapted brownian motion $W=(W_t)_{t \geq 0}$, consider $X^{t,x}= ...
0
votes
1answer
47 views

Solution of Vasicek model driven by infinite activity Levy process

Say that we have the Vasicek model $dY_{t} = \alpha(\beta-Y_{t})dt+\sigma dX_{t}$ where $X_{t}$ is an infinite activity Levy process, $\alpha$,$\beta$ and $\sigma$ are constants. I know that in the ...
1
vote
1answer
66 views

Expectation of stochastic differential equation

I have solved the nonlinear stochastic equation $dX_t=\frac{1}{2}a(a-1)X_t^{1-2/a}dt+aX_t^{1-1/a}dW_{t}$, by reducing it to a linear one (change of variables $Y_{t}=X_{t}^{1/a}$ and applying Ito ...
0
votes
1answer
22 views

Autocorrelation of Radial Stochastic Process with Planar Derivatives

I have a random field $h(\vec{r})$ that depends on $\vec{r}=(x,y)$, such that \begin{equation} \langle h(\vec{r})h(\vec{r}+\vec{r}') \rangle \sim \exp(-||\vec{r}-\vec{r}'||/a^2) \end{equation} where ...
0
votes
0answers
67 views

Finding dynamics of a dividend paying stock under arbitrary numeraire

Assuming I have a dividend paying asset $S$ with dividend process $D$. Now I would like to use the bank account process $B$ as numeraire and determine the dynamics of $S$ under the the corresponding ...