A stochastic, or random, process describes the correlation or evolution of random events. It is used to model stock market fluctuations and electronic/audio-visual/biological signals. Among the most well-known stochastic processes are random walks and Brownian motion.

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Conditional Expected Value of Occurrence Time in Stochastic Process

I have a stochastic process defined by the intensity function $\lambda(t:F_t)$ where $t$ is time and $F_t$ is the filtration process. The stochastic process is self-exciting and models the occurrence ...
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2answers
99 views

Proving integrability of a random variable involving stopping times

Let $X_1, X_2,...$ be i.i.d integrable random variables in $\mathbb{R}$ with $\mathbb{E}[X_i] =0$ and $\mathbb{P} (X_i >0) >0$. Let $x>0$, $S_0 = x$, and $S_n= x + \sum_{i=1}^{n} X_i $. For ...
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16 views

Sum over stochastic processes on the same set of categories

I have a stochastic process consisting of multiple (stochastic) steps, for which I want to know if I can substitute (or at least approximate) it by summing over the deterministic and stochastic parts ...
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36 views

Minimum of a random variable sequence

$S_{n}$ model the price of a financial asset. The recurrence relation is given by: $$ S_{n+1} = (1 + r\Delta t_{n} + \Delta W_{n})S_{n}, n = 0, \dots, N $$ where $\Delta W$ has a normal ...
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1answer
34 views

Simple question about the definition of Brownian motion

I have a question concerning the definiton of Brownian motion. Usually (e.g. on Wikipdia) one demands a brownian motion $\lbrace B_t\rbrace_{t\in[0,\infty)}$ to satisfy the following condition: ...
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18 views

Scheduling Algorithm for a multi-server queue problem

I have 4 servers, n customers and m reports. At any time, a customer may request one of m reports. There are only 4 servers which are capable of generating reports. Each server can only process one ...
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1answer
26 views

Adapted and backward adapted?

I understand the following: Consider a probability space $(\Omega, \mathcal{A},P)$ and a Brownian motion $B=\{B_t, t\in [0,1]\}$ on this space and denote $\mathcal{F}:=(\mathcal{F}_t)_{t\in [0,1]}$ ...
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1answer
60 views

Is a deterministic process adapted?

Let $B$ be a standard Brownian motion on a probability Space $(\Omega, \mathcal{F}, P)$ and let $\mathbb F:=(\mathcal{F}_t)_{t\in [0,T]}$ denote the natural filtration, i.e. $\mathcal{F}_t = ...
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1answer
29 views

Intuition underlying stopped martingales

Let $X$ be a martingale and $T$ a stopping time. Define the stopped martingale $X_{\min\{T,n\}}$. What is the intuition underlying this process? It is quite confusing here. $X$ is random and $T$ is ...
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1answer
44 views

Derivation of Differential Chapman-Kolmogorov equation, Kramers-Moyal expansion

I'm stuck with the derivation of the differential Chapman-Kolmogorov equation provided in Gardiner 1985, section 3.4. This is supposed to be some middle ground between the master equation and the ...
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1answer
27 views

independent increments property implies Markov property

Let $\{X_t\}_{t\in\mathbb R^+}$ be a stochastic process with values in $\mathbb R$. Suppose that $\{X_t\}$ has independent increments, namely for every $t_1<t_2<\ldots<t_k$ the random ...
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37 views

Ito formula for jump proccess

I have just learned Ito fomula for jump processes but I have still not understood it well. Assume that I have $dS_r=S_{t^-}\mu+S_{t^-}\sigma dB_t +S_{t^-}\int_{\mathbb{R}^+}(y-1)N(dt,dy), \;\; 0\leq ...
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1answer
51 views

An inequality in martingale

Suppose $X_n$ is a supermartingale,for $\lambda>0$ ,we have the following inequality: $$\lambda\mathbb{P}(\inf_{n\leq k}X_n\leq-\lambda)\leq\int_{[\inf_{n\leq k }X_n\leq -\lambda]}(-X_k) ...
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1answer
85 views

Expectation of Square of Stopping Time

Let $B_t$ be standard Brownian motion and $a < 0 < b$. Define stopping time $T$ as follows. $$T = \min \{t \geq 0: B_t \in \{a, b\} \}.$$ The expectation of $T$ is $\mathbb ET = |a|b$ and can be ...
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1answer
71 views

Solve $dX_t = (\sqrt{1+X_t^2} + \frac{1}{2}X_t) \, dt + \sqrt{1+X_t^2} \, dW_t$ explicitly

Solve explicitly the 1-dimensional equation: $dX_t = (\sqrt{1+X_t^2} + \frac{1}{2}X_t)dt + \sqrt{1+X_t^2}dW_t$ I have hopelessly been guessing solutions to this. Does anyone know how to solve this ...
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1answer
36 views

Markov processes on function spaces

Is there any reference on Continuous time Markov process whose state space is infinite dimensional function spaces, such as the space of continuous functions $C(R^d)$? It seems Dirichlet Form is a ...
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23 views

Control of the expected false discovery rate

I've been looking at why exactly the Benjamini and Hochberg procedure controls the expected false discovery proportion. More specifically, assuming $N$ hypotheses with corresponding $p$-values; for a ...
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1answer
55 views

Markov Chains : Can anything be said about what happens in between two transition?

In time homogeneous discrete Markov chains we take a set period for a single transition. In examples we see sometimes depending on the examples the transition period being a a month a week etc. I'm ...
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1answer
51 views

Intuition in Random walk

Suppose $X_i$ are i.i.d. r.v. $S_n=X_1+\cdots+X_n$ is random walk. Why $\mathcal{F}_n =\sigma(X_1,\cdots,X_n)$ are called the information known at time n? I think We only know the measurability of ...
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1answer
23 views

Solve parameter from stochastic integral

how can I solve $\rho$ from the following: $\int_0^T dV_t = \int_0^T \kappa (\theta - V_t) dt + \int_0^T \sigma \rho \sqrt{V_t} dW_t + \int_0^T \sigma \sqrt{1-\rho^2} \sqrt{V_t} dZ_t$, where $W_t$ ...
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1answer
32 views

Verifying stopping times…

Let $m$ be a natural number, $$g_m:=\sup\left\{ {n\leq m: S_n\leq 0}\right\}$$ and $$d_m:=\inf\left\{ {n\geq m: S_n \leq 0}\right\}$$ I have to check if they are are stopping times. It's still a new ...
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2answers
58 views

Covariance of Ornstein - Uhlenbeck Process

I'm considering the Ornstein - Uhlenbeck process $ X(t)=x_{\infty}+e^{-at}(x_{0}-x_{\infty})+b \int_{0}^{t} e^{-a(t-s)} dW(s)$ where $a, b > 0 $ are given constants. I used the Itô Isometry to ...
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1answer
47 views

Random process with stationary independent increments determined by first order distribution?

It says in my random processes book that if a random process $X_t$ with stationary independent increments has value $0$ at the start ($X_0 = 0$) then it is completely determined by it's first order ...
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1answer
98 views

Problem about Random walk and Stopping time.

Here is an example in "Probability with Martingales" My questions are: (1)Does equation (a) hold for $T=\infty$? (2)The equation:$$\mathbb{E}M_T^\theta=1=\mathbb{E}[(sech \theta)^Te ...
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1answer
27 views

In an irreducible, aperiodic, null-recurrent Markov chain holds $\sum_n p_{ij}^{(n)} = \infty$

My lecture notes state the following theorem: Theorem 2. Let $(X_n)$ be an irreducible, aperiodic, null-recurrent Markov chain. Then $$\forall i,j \in S : p_{ij}^{(n)}\to 0 \text{ and } \sum_n ...
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Is a discrete random process issued from a sampled continuous ergodic WSS process also ergodic?

I have a continuous time process $\{X_t,t\in\mathbb{R}\}$ that is WSS and ergodic for the 1st and 2nd moments. I create a random discrete process $\{Y_n,n\in\mathbb{N}\}=\{X_t,t=nT\}$ by discretizing ...
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1answer
48 views

Integrating probabilities

My following problem is of general nature, here is an example to illustrate it. For example let $\left(\xi_i\right)_{i \geq 1}$ be independent and identically Exp(1) distributed random variables. We ...
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26 views

Jeffrey's Prior for Bivariate Lognormal

Exactly what the question says, I'm working on code for an MCMC simulation and need to set some uninformative or weakly informative priors. I haven't been able to find the prior for the sigma ...
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1answer
25 views

Poisson Process Suitable Scenarios

I have a couple of doubts about if these scenarios are suitable to be modeled as a Poisson process. I will like to have your views and arguments why. Packets are lost due to packet overflow in the ...
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1answer
99 views

A Markov Chain Problem.(Change the color of ball)

There are $n$ different color balls in a box. Take two balls in turns, and change color of the second ball to the first. (This is one operation). Let $k$ be the (random) number of operations needed to ...
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132 views

Changing a queueing processes

Situation Consider a general queueing system $\mathscr{S}$, whose customer arrival times are independent, and whose service times are independent; both of these are allowed to have general ...
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1answer
44 views

Poisson process has independent and stationary increments

Being $N_t$ a Poisson process, defined as $$N_t:=\sum_{n\geq 1} n \mathbb{1}_{[T_n,T_{n+1}[}(t)$$ where $T_n$ are sums of independent exponential random variables, how can I prove it has stationary ...
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27 views

Will the branching process go extinct with probability 1?

I am trying check whether the branching process goes extinct with probability one. Single Type Branching Process with Pk = (1/2n)(n/k), for k = 0,.....,n with n > 2. Assuming, i can be able to ...
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1answer
41 views

How to apply the strong Markov property in this case?

I'm trying to understand the following proof: Theorem: Let $(X_n)$ be an irreducible $(\alpha, \mathbf p)$-Markov chain with a finite state space $S$. Then $(X_n)$ is positive recurrent. ...
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1answer
106 views

How to get closed form solutions to stopped martingale problems?

Way back when, I took a course in stochastic processes in college. I remember being frustrated by the plethora of abstract proofs without much in the way of how to use them to get actual results. It ...
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31 views

Explicit solution SDE?

I have the following SDE: $$dY_{t}=A\left(\frac{W_{t}^{1}}{\sqrt{t}},\frac{Y_{t}}{\sqrt{t}}\right)dW_{t}^{1}+B\left(\frac{W_{t}^{1}}{\sqrt{t}},\frac{Y_{t}}{\sqrt{t}}\right)dW_{t}^{2}$$ where ...
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1answer
42 views

For a Poisson process prove that (a) $N (t) -λt $ and (b) $e^{(\log(1-u) N (t) + uλt)}$, are martingales

For a Brownian motion ${z (t)}$ and for any $β ∈ R$, be $V (t) = \exp\{ βz (t) - (t β ^ 2) / 2\}, t≥0 $ Show that ${V (t)}$ is a martingale with respect to a Brownian filtration. Also ${N (t)}$ be a ...
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61 views

Mean and variance of a stochastic process

Let \begin{equation} \begin{array}{l} y_1(t)=e^{-\kappa_1 t}y_1(0)+\displaystyle\int_0^t\kappa_1 e^{\kappa_1(s-t)}\theta_1ds +\sigma_1\displaystyle\int_0^te^{\kappa_1(s-t)}\sqrt{y_1(s)}dZ_1(s),\\ ...
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3answers
37 views

Is $W_{2t}-W_t$ a brownian motion?

Is $W_{2t}-W_t$ a brownian motion? $(W_t)_{t\geq 0}$ is a brownian motion, I have to show that $X_t:=W_{2t}-W_t$ is a brownian motion as well. $$W_{2t}= 1/\sqrt{2} W_t$$ (by scaling property) then ...
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1answer
26 views

Centered independent increments process is a martingale

Let $(X_n)$ be an centered integrable process with independent increments (which as far as I understand means that $(X_{n+1}-X_n)_{n\in \mathbb N}$ is independent). While showing that $(X_n)$ is a ...
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45 views

$E[M_t|H_t]$ is a martingale with respect to $H=(H_t)_{t\geq 0}$, $H_t \subset \mathcal{F}_t \forall t$

Being $(M_t)_{t \geq 0}$ an $\mathcal{F}$-martingale, I have to show that $E[M_t|H_t]$ is a martingale with respect to $H$ ($H=(H_t)_{t\geq 0}$, $H_t \subset \mathcal{F}_t \forall t$). I proceded ...
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43 views

Write down the HJB equation

Suppose that we have to solve the following optimal control problem \begin{align} V(t,x) = \min_{\alpha}\mathbb{E} \left[\int_{0}^{T}L(t,x,\alpha)dt + F(e^{-\beta t}X^{\alpha}_{T})\right] ...
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1answer
34 views

Do we need $\tau \leq \nu$ to show $E(X_\tau)=E(X_\nu)$?

My lecture notes claim that if $(X_n)$ is a martingale and $\tau$ is a stopping time bounded by $N$ then $$E(X_\tau)=E(X_{\tau \wedge N})=E(X_{\tau \wedge 0})=E(X_0)$$ and then remarks that if $\tau$ ...
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2answers
21 views

Random number distribution from a different distribution

Suppose I have a random number generator that generates random numbers $x$ with a normal distribution $p(x) \propto e^{-x^2}$ (modulo normalization, but lets keep it simple). Now, out of these ...
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1answer
38 views

Proof that a random variable has exponential distribution.

Supose that $X_1$ is a continuous and positive (real) random variable with exponential distribution, namely $$P(X_1>t)=e^{-\lambda t}\quad t>0$$ Now suppose that $X_2$ is another continuous and ...
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1answer
58 views

Find one-dimensional distribution function $F(y\mid t)$ of random process $Y(t)$

$ Y(t)=tZ^2;\quad Z\sim U(-2;2); \quad t\ge0. \quad$ I need to 1) find one-dimensional distribution function $F(y|t)$ of random process $Y(t)$. 2) calculate probability that trajectory of the ...
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1answer
40 views

Stochastic processes with full memory

Markov processes are stochastic processes with no memory. How are called the stochastic processes with full memory? Can't found anything on google.
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4 views

How to calculate radius density of observation using locality sensitive hashing?

How do I calculate radius density of observation using locality sensitive hashing? I am new to the locality sensitive hashing(LSH). LSH based learning and Querying was difficult to understand.
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1answer
21 views

Max of independent and identical random variables is Markov

I'm supposed to show that given a sequence $\{Y_n\}$ of i.i.d the stochastic process $$X_n=\max(Y_0, Y_1...,Y_n)$$ is a Markov of chain. I think I could do it by induction but I would rather see how ...
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1answer
85 views

Angle bracket and sharp bracket for discontinuous processes

The question is quite simple actually. I am trying to understand the differences between the angle bracket $\left<X,Y\right>$ of two processes with jumps $X,Y$, and the sharp bracket of $[X,Y]$. ...