Questions tagged [brownian]
Brownian motion is the random motion of particles (eg atoms) that make up a gas. The math used to model Brownian motion is sometimes used in statistics to describe stochastic processes over time.
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Denoising brownian noise type signal (piecewise continuous noise) at known time samples [closed]
Posting here because I didn't have much success in dsp. Hopefully some of your skillsets might be more valuable in this situation. Original question here: ORIGINAL QUESTION
I have a signal which at ...
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12 views
Why does the Hurst package apply a finite-differencing step before doing rescaled range calculations?
When I look at the code for the compute_Hc function in the Hurst package for Python, there is an initial finite differencing step. Everything else after that agrees ...
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28 views
Conditional Expectation Brownian Motion
So this is an exam question I had recently and I honestly had no idea on how to solve it.
Let W(t) be a Brownian Motion stochastic process at time t with drift p and variance v^2
Let s exist such ...
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97 views
Modelling startups' funding journey with Brownian Motion
I am trying to implement a "light" version of a paper (Hunter, Saini & Zaman 2017), in which the authors build a model capable of predicting the probability that a startup will exit (either by ...
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52 views
Generating fractional Brownian motion in R [closed]
I was trying to generate fractional Brownian motion in R using fbm of the package somebm. However, in this package, I can not ...
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0answers
14 views
Brownian Motion proof: difference converging to 0 almost surely
I am reading a proof where it is assumed that $$ \lim_{n \to \infty} \sup_{0<s\leq s_0}\left| \frac{t_n(s)}{s}-1 \right|=0 , \hspace{30mm} (1)$$ where $t_n(.)$ is some sequence of functions. ...
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1answer
133 views
What is the distribution of the peak time of the first hitting time process
I need to find the distribution of the random variable $T_{peak}$ where $T_{peak}$ represents the peak time of the first hitting time process.
Detailed Explanation of the System:
There are $N^{Tx}$ ...
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1answer
27 views
Distribution of Conditional Brownian Motion
Let $\ X(t),t \ge 0$ be a Brownian motion process.
That is, $\ X(t)$ is a process with independent increments such that:
$$\ X(t) - X(s) \sim N(0,t-s), 0\le s \lt t $$
and $\ X(0)= 0$.
...
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1answer
67 views
Is standard Brownian motion (AKA a Wiener process) weakly or strictly stationary?
Question
Let $B(t)$ be a standard Brownian motion (AKA a Wiener process).
Is $B(t)$ weakly or strictly stationary, particularly as defined here?
My Thoughts
We know, by definition, that its ...
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149 views
How to solve / fit a geometric brownian motion process in Python?
For example, the below code simulates Geometric Brownian Motion (GBM) process, which satisfies the following stochastic differential equation:
The code is a condensed version of the code in this ...
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0answers
33 views
Chung type LIL, integral of Brownian motion
Suppose I have two Wiener processes, which are independent - call them $B(t)$ and $W(t)$.
I think it should be true that
$$\liminf_{T \rightarrow \infty} \frac{\ln\ln T}{T^2}\left|\sup_{0 \leq x \leq ...
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161 views
Why does the variance of a Brownian motion increase linearly with time?
Brownian motion is said to follow a path where each value is normally distributed with mean $\mu t$ and variance $\sigma^2 t$.
What is the basis for the relation that variance varies directly ...
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29 views
a simpler version of my original variance puzzle question
Hi: I think that I can simplify my original question a great deal so here's my attempt.
Suppose I have a function $f(t) = t-10$. $t$ denotes time and starts at $t = 0$ and the units of time pass ...
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2answers
111 views
Which formula for GBM is correct?
I am trying to write a simple GBM simulator. Unfortunately, the task has turned rather difficult.
The first approach I looked into was the most obvious. I could use the analytic solution for the GBM ...
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0answers
47 views
What is the name of this stochastic process?
Suppose that $\{Z_t : t \in [0,1]\}$ is a standard Brownian Motion process. It's well known that $X_t = Z_t - tZ_1$ is a Brownian Bridge, because it's a continuous Gaussian process, with mean function ...
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1answer
217 views
Correlation between Ornstein-Uhlenbeck processes
Consider the Ornstein-Uhlenbeck process, $U(t)$, whose evolution follows:
$$
\mathrm{d}U(t) = -\theta U(t) \mathrm{d}t + \sigma \mathrm{d}W(t),
$$
where $\theta \in (0,2)$ is the mean-reversion rate, $...
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0answers
65 views
Covariance of Gaussian process?
Problem:
Consider the random process defined by the Ito integral
$$ X_t = \int_0^t f(\tau)\, dB_\tau $$
where $f(\tau)$ is a deterministic real-valued function and $B_\tau$ denotes the canonical real-...
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33 views
Incorporating explanatory variables in a Ornstein-Uhlenbeck model
In my research im dealing with a longitudinal data set, which consists of a single response variable and a set of several predictor variables, which comprises a mixture of individual specific ...
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0answers
49 views
Sample auto-covariance of a Wiener process
Say we have $n$ observation $\{X_i, i=1,...,n\}$ from a realisation of a Wiener process. We don't know when the process began. We want to estimate the autocovariance of this process. If we form two ...
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0answers
43 views
Is an ITO diffusion time slice always Normally distributed?
As the title says, if we take a time slice on any Ito diffusion - are we guaranteed that the data is always Normally distributed?
This seems like a useful property for computer generalization and ...
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60 views
How does one approximate $\mu$ and $\sigma$ in an arithmetic Brownian motion using a Kalman filter?
My concern arises from the fact that in the following system:
$x_k = (\mu, \sigma)^T = x_{k-1}$
$Y_k = Y_{k-1} + \mu + \sigma Z_k \quad Z_k \sim N(0,1)$
that I cannot separate the states I want to ...
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1answer
113 views
Showing that two Brownian Motions are equal in distribution
I must show that $\{B(ct), t\geq 0\}$ is equal in distribution to $\{c^{1/2}B(t), t\geq 0\}$ where $B(t)$ is a Brownian Motion and $c$ is some constant.
So, I'll be honest. I'm at a loss. I've tried ...
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1answer
81 views
Solution Geometric Brownian Brownian motion with no drift
This question has been asked before in here Geometric Brownian motion without drift
but I can't find what I want in the answers so ask again differently:
for $\mu=0$
$$
dX_t =\mu X_t dt + \sigma X_t ...
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1answer
27 views
Why does the theoretical value of the difference between these 2 stochastic integrals differ from the observed value in r?
Consider the stochastic integral
$$
2 \int_0^1 W_t \hspace{2mm} dW_t
$$
Using r, this may be evaluated using one of the following summations
$$
S_1 = 2 \sum_{j=0}^{n-1} \left[ W_\frac{j}{n} \left( W_\...
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0answers
168 views
Conditional Expectation for Geometric Brownian Motion
Given a geometric Brownian motion:
$\frac{dZ}{Z} = \mu dt + \sigma dW$
Is there a closed-form solution to $\mathbb{E}[z_s | (z_s > a)\cap(z_t > b)]$ for $t \geq s$?
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1answer
56 views
Z ~N(0,1), distribution of √t Z?
If I have a variable Z that is normally distributed, Z~N(0,1), what would be the distribution of √t Z, t>=0?
Can I say the process Xt = √t Z is a Brownian Motion?
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0answers
50 views
Brownian bridge to unknown via extremum
Suppose, I know what's the minimum $\min$ of a random walk $w_t$ in period $[0,\Delta t]$. I also know $w_0$ and $\sigma$. How to construct the Brownian bridge for the latter period?
I guess it's not ...
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1answer
55 views
Reference Request for Fractional Brownian motion
This question has been asked several times on this website. But the problem is that all the references suggested are mathematics oriented and difficult to understand. I am looking for a reference, ...
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0answers
59 views
What is the joint density of a drifted Brownian motion reflected below at a positive number and its running maximum?
Suppose $W^{\mu}_t$ is a Brownian motion with drift $\mu$ and $Y_t$ represents the reflecting process of $x+W^{\mu}_t$ ($0<x<b$) which is reflected at $b$.
...
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1answer
79 views
Deriving Inverse Gaussian as First Passage Time of Wiener Process
Chhikara and Folks (1988) show that the inverse gaussian distribution arises as the first passage time for a wiener process. However, there are several steps I don't quite understand. In particular, ...
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1answer
188 views
Power Spectral Density of Random Walk
The Brownian motion has a power spectral density (PSD) dependency on frequency like $\frac{1}{f^2}$. As far as I understand, power spectral density is defined only for wide sense stationary processes ...
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0answers
54 views
Fokker Planck equation for a general distribution
The Fokker Planck Equation(FPE) is related to the Stochastic Differential Equation
$dX_t = m(X_t,t)dt + \sigma(X_t,t)dW_t$ where $dW_t$ is normally distributed. What is the corresponding FPE like ...
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1answer
87 views
Compute $P\left(\int_0^1W(t)dt>\frac{2}{\sqrt3}\right)$ where $W(t)$ is a Wiener process
I'm working through problems I found on the net for which there are no answers given. Therefore I'm looking for someone to check my work.
Q: $P\left(\int_0^1W(t)dt>\frac{2}{\sqrt3}\right)$ where ...
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0answers
181 views
How to simulate anomalous diffusion of a 1D point like particle?
I want to simulate 3 types of diffusion processes:
normal diffusion $[\langle x^2(t)\rangle \propto t ]$.
subdiffusion $[\langle x^2(t)\rangle \propto t^\alpha ; \alpha<1 ]$
superdiffusion $[\...
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1answer
74 views
Brownian motion proof
If $X(t)$ is a Brownian motion, how can we prove $X(a^2t)$ is also Brownian?
If $X(t)$ is brownian it is $N(0,\sigma^2*t)$ . But I am not able to see how I can use this for $X(a^2t)$
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1answer
159 views
Distribution of the $90$th percentile of a geometric brownian motion simulation
I have run a simulation of a geometric brownian motion. The simulation runs from $t=0$ to $T=1000$. I generate $10000$ paths. For every moment for $t=1,2,3,\ldots, 100$ I calculate the $90$th ...
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1answer
47 views
Determining if a proces is Brownian Motion
$W(t)_{t>0}$ is a Brownian motion. $V(t)=W(s+t)-W(s). \text{ } s,t>0$.
Is $V$ also a Brownian motion?
It is clear that $E[V]=0$. I would argue that the variance is $$\operatorname{var}[V]=\...
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1answer
395 views
When is a stochastic process not differentiable?
Assume $\frac{dX_t}{X_t} = \mu dt + \sigma d B_t$ where $\mu$ is a constant and $B_t$ is a Brownian motion, and let $Y_t = \ln X_t$. I understand that $B_t$ is nowhere differentiable and both $X_t$ ...
3
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1answer
157 views
Predictor for averaged Brownian motion
The best forecast (predictor) for a Brownian motion at time $t+h$ is the present value at time $t$ since it's a martingale. The same holds for random walks with independent steps and without drift.
...
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0answers
117 views
Question on variance and expectation of Brownian Motion related things
In a mathematical finance text by Ubbo F Wiersema, I came across the following
Say $\Delta t$ is very small. $\Delta B(t)$ denotes $\textit{brownian motion increment}$. Then $E[\Delta t\Delta B(t)]=0$...
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85 views
Write expectation of brownian motion conditional on filtration as an integral?
Let $W_t$ be a Brownian motion, so $W_t=z_t \sqrt{t}$ where $z_t \in N(0,1)$ and the pdf of $z$ is
$f(z)=\frac{e^{-\frac{z^2}{2}}}{\sqrt{2\pi}}$. So
$$E(W_t)=\int_{-\infty}^{\infty} W_t f(z) dz
=\...
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0answers
98 views
Random walk touching or exceeding thresholds
What is the formula to estimate the probability of a random walk touching or exceeding a particular threshold? The threshold starts and stops at particular times. (Without starting and stopping times ...
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0answers
85 views
Ito's integral formula for non-standard Brownian motion
Concerning Ito's integral formula,
$$\int_0^t B(s)dB(s) = \frac{1}{2}B^2(t)-\frac{1}{2}t,$$
the MIT lecture notes give a proof that "the standard Brownian motion has a.s. finite quadratic variation ...
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0answers
29 views
Simulate Geometric Brownian Motion Path with Fixed Starting AND Ending Points [duplicate]
It is straightforward to simulate GBM path from a set starting value, but what if I also want it to arrive at a certain value in the end? Any ideas on how to do it are highly appreciated.
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1answer
79 views
Proof the increment variance of the Scaled Random Walk
Start by defining the Symmetric Random Walk:
$$ M_t = \sum_{i=1}^{t}X_i, ~~ \text{with}~X_0=0 $$
where $X_i$ is equal to 1 or -1 with $p=(1-p)=0.5$.
Consider $t > s$, the variance of its ...
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0answers
32 views
Difference in likelihoods between BM and the stationary distribution of an OU model
I'm calculating the fits of Brownian motion and Ornstein-Uhlenbeck models to data, given a phylogeny.
However, when deriving the likelihood functions, it appears that the Ornstein-Uhlenbeck model is ...
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1answer
222 views
Kolmogorov distribution as the sup of a Brownian bridge
It is well known that The Kolmogorov distribution is the distribution of the random variable
$$
{\displaystyle K=\sup _{t\in [0,1]}|B(t)|} $$
where B(t) is the Brownian bridge:
$$
B(t) = (W_t|W_1=0)
$...
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1answer
395 views
Correlation function of Wiener process (brownian)
The following is stated in a text I am using: Consider the Wiener process (Brownian process) $W(t)$. The Wiener process has no derivative $\xi(t) := \frac{d W}{d t}$, reflecting the fact that it ...
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1answer
95 views
Best estimate for Stochastic difference equation
On the subject of Stochastic differential equations. If we consider the difference equation $$\Delta x(t_n) = x(t_n) \Delta t + f(t_n) \Delta t$$ where we consider $f(t_n) \Delta t$, the driving term ...
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1answer
957 views
What's the intuition of variance, quadratic variation and total variation of Brownian Motion in practice?
I'm familiar with the mathematic definitions of these three quantities, but having a hard time to really understand how to use them when actually dealing with discrete samples from a realization of a ...
