Questions tagged [martingale]
In probability theory, a martingale is a model of a fair game where knowledge of past events never helps predict the mean of the future winnings and only the current event matters.
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How to compute expectation of square of Riemann integral of a random variable?
How does one compute $E[(\int_0^T W_s ds)^2]$ where $(W_t)_{t \in [0,T]}$ is standard Brownian motion in $(\Omega, \mathscr F, \mathbb P)$?
Apparently proving
$$\int_0^T W_s ds = \int_0^T (T-s) dW_s ...
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Does a martingale difference sequence (mds) imply strong mixing?
I read this from an econometrics paper (Dufour and Pelletier, 2014)
"
The typical hypothesis which is imposed in the time series literature is that the $u_t$'s are either independent and identically ...
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Help to understand martingale example from Billingsley
I am studying Billingsley's section 35 about martingales and I have some difficulties understanding one of the examples.
This is the example 35.4.
Suppose we have a measurable space $(\Omega,\mathcal ...
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How to check these sequences generated by i.i.d random variables are martingales?
Let $\{Y_n\}_{n\geq 1}$ be a sequence of independent, identically distributed random variables.
$P(Y_i=1)=P(Y_i=-1)=\frac12$
Set $S_0=0$ and $S_n=Y_1+...+Y_n$ if $n\geq 1$
I want to check if the ...
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Is this weird pattern in my Martingale Residuals plot normal?
I'm running a cox model:
coxtest<-coxph(Surv(time=Age_Sample,time2=Age_event,event=LungCancer)~Cigarettes_Lifetime,data=mydata)
Then I do
...
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What is the Interpretation of the Alternative Hypothesis of the Conditional Predictive Ability Test [Giacomini and White (2006)]?
I am reading "Tests of Conditional Predictive Ability" by Giacomini and White (2006).
The Null Hypothesis of equal Conditional Predictive Ability is formulated as
$H_0: E[\Delta L_{m,t+\tau}|G_t]=0 \...
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Martingale Difference Sequence CLT
Could you provide me with the proof of the following:
$$n^{-1/2} \cdot\sum_t a_{t-j}e_t$$ converges to normal distribution as $n$ goes infinity by martingale difference sequence CLT where $a_t = \...
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1answer
42 views
Martingale Difference Sequence
I saw that in the link on page 3 it is said $Y_t = e_t\cdot e_{t-1}$ is martingale difference sequence and dependent where $e_t$ is i.i.d with $N(0,\sigma^2)$ Could you provide me with the proof of it?...
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Estimating conditional expectation using SVR
I have an estimation problem: $X_t=f(S_t)=E(X_T\mid S_t)$ given the observations $(X^i_{T},S^i_{t})$ for all $i$'s. I used support vector regression (SVR) to run a regression of $X_T$ on $S_t$. Here $...
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The magic money tree problem
I thought of this problem in the shower, it was inspired by investment strategies.
Let's say there was a magic money tree. Every day, you can offer an amount of money to the money tree and it will ...
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1answer
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log transform fixed PH in Cox model - how?
I have survival data to which I am fitting a Cox model with a continuous predictor. The cumulative martingale residual method (supremum test) of Lin, Wei and Ying
suggested that both proportional ...
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2answers
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Cox PH model: managing continuous variables and linearity assumption
In an epidemiological study, I'm using martingale plot to assess the linearity of continuous variables.
Here are the Martingale Residuals (from Null Model) using R's ...
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Is a random walk necessarily a martingale?
I read in the following notes (http://www2.econ.iastate.edu/classes/econ672/Falk/_notes/lecture_4_martingales.pdf, p.2) that "a random walk is a martingale."
Although it seems logical with the used ...
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1answer
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When is the posterior distribution equal to the prior?
So I have heard that if the prior distribution is in the subexponential class, applying Bayes rule does not change the belief. I have been trying to find an example of this but I am unable to do so. I ...
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1answer
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Cox PH linearity assumption: reading martingal residual plots
According to a lot of ressources about Cox PH model, continuous numeric variables should be tested for linearity assymption by plotting the Martingale residuals.
In R, you can use ...
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Is it a valid algorithm to win at the casino roulette?
I would like to try the following algorithm in order to win in the roulette:
Be an observer until there are 3 same parity numbers in a row ($0$ has no defined parity in this context)
Once there were ...
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How to approach Basketball “Beat the Pro” drill with Markov Chain
Suppose, similarly to Gambler's ruin problem a Basketball player is doing "Beat the Pro" drill. That is, for every shot made, he scores one point, and for those missed, two points are to be deducted. ...
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Power martingales for change detection: M goes to zero?
I'm trying to apply the power martingale framework by [Vovk et al., 2003] to change detection in unlabeled data streams, just like in [Ho and Wechsler, 2007]. The basic idea involves using a power ...
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1answer
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ABRACADABRA Problem
As a complement to this answer for those not familiar with martingales.
What is the expected number of keystrokes (or "time") it would take a
monkey to type the string $\small \text{ABRACADABRA}$...
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Azuma's inequality Use
For binary vectors, x = (x1,x2,...,xn) and y=(y1,y2,...,yn), the Hammond distance between them is defined by
d(x,y) = |x1 - y1| + |x2 - y2| + ... + |xn - yn|.
Let A be a finite set of such vectors ...
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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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856 views
Martingale Difference & Conditional Heteroskedasticity
I was reading this passage in a book and I am confused about the last line. As far as I understand, the white noise process does not allow for conditional heteroskedasticity due to its i.i.d. property....
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Prove $Z_n = X_n1_{n \le T} + Y_n1_{n+1\ge T}$ is a martingale
Given a filtered probability space $(\Omega, \mathscr F, \{\mathscr F_n\}, \mathbb P)$, let $X = (X_n)_{n \in \mathbb N}$ and $Y = (Y_n)_{n \in \mathbb N}$ be $(\{\mathscr F_n\}, \mathbb P)-$...
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Upper bound for randomly weighted sum of independent random variables
I have a sequence of independent random variables {$\epsilon_j$} with mean 0. I also have another sequence of Bernoulli random variables $\delta_1, \delta_2,\dots$ which are dependent on the previous ...
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1_event set notation
I do not understand the notation as given here:
The source for the image is page 17 in this paper after equation 18.
I understand the first subset notation but what does 1_\e_t mean?
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Why white noise process and IID process are considered martingale [closed]
Can anyone explain to me why A white noise process (εt) and An IID process (εt) are martingales?
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$M_t$ Local Martingale if and only if satisfies $\frac{\partial f}{\partial t}+\frac{1}{2}\frac{\partial^2 f}{\partial x^2}=0$ proof?
I was reading the wikipedia article on local martingales and it states the following theorem
Let $W_t$ be standard Brownian motion and let $f:[0,\infty)\times\mathbb{R}\rightarrow\mathbb{R}$ such ...
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An inequality about expectation [duplicate]
If $X_n$ is a martingales with $sup E|X_n|^p<\infty$ where $p>1$, How can show that
$$E^p|X_n|\leq E |X_n|^p$$
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Martingales: Why must expected posterior equal prior?
For a posterior distribution to be plausible in the Bayesian sense (Bayes' Plausible), it is said that:
$\mathbb{E}(\mu_{t+1} | \mu_t) = \mu_t$
where $\mu_t$ is the posterior distribution at time $...
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1answer
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Semi-martingale vs. martingale. What is the difference?
Can someone please explain (preferably in layman's terms) what is the difference between semi-martingales and martingales?
I have found the following sentence on Wikipedia: In probability theory, a ...
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The best constant in a martingale moment inequality
Suppose we have a stochastic integral of the form $M_{t}=\int_{0}^{t}{H_{u}dW_{u}}$ and we know $M$ is a (true) martingale. It is known that for all $p\geq1$,
$$
\mathbb{E}[|M_{t}|^{p}]^{1/p} \leq C(p)...
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1answer
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Martingale process
Let $\zeta(t)$ be a process with independent increments and $M(t)=E(\exp(\zeta(t))) < \infty $, show that $M(t)^{-1}\exp(\zeta(t))$ is a martingale.
So what I need to show is
$$E(M(t)^{-1}\exp(\...
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1answer
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How to Simplify the Representation of Local Martingales?
This is a follow-up to my previous question on MathOverflow.
Is there a way to combine the Dambis-Dubins-Schwarz theorem and the Martingale Representation Theorem to get the following result?
Let $...
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1answer
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Difference between random walk and martingale
I am trying to understand the diffrence between random walk and martingale. According to my understanding, a random walk without drift is
$$ y_{t} = y_{t-1} + u_{t} $$
where $u_{t}$ is $i.i.d.(0, \...
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2answers
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Finding $b$ such that $e^{5B_t - bt}$ is a martingale
I have $X_t = e^{5B_t}$ and
Where $B_t$ is brownian motion at time $t$.
$M_t = X_t \cdot e^{-bt}$
I need to find a value for $b$ such that $M_t$ is a martingale.
I am encountering difficulty, ...
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1answer
72 views
martingales, stochastic processes
Suppose Xn, $n\geqslant0$ is a Markov chain on $\varphi =\left \{ 0,1,2,...,d \right \}$ and $P(x,y)=\frac{\binom{2x}{y}\binom{2d-2x}{d-y}}{\binom{2d}{d}} $. States 0 and d are absorbing states for ...
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Does the LHS of $E[X_n | \mathscr F_{n-1}]$ make sense even if $X_n$ is not integrable or adapted?
Let $(\Omega, \mathscr F, \{\mathscr F_n\}_{n \in \mathbb N}, \mathbb P)$ be a filtered probability space. Then $X_n$ is a $(\{\mathscr F_n\}_{n \in \mathbb N}, \mathbb P)-$martingale if:
$X_n$'s are ...
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1answer
244 views
Proving Y is a martingale using indicator functions
Prove the stochastic process $Y = (Y_n)_{n \geq 0}$ is a martingale w/rt the filtration $\mathscr{F} = (\mathscr{F_n})_{n \geq 0}$, where $\mathscr{F_n} = \mathscr{F_n}^{Y} \doteq \sigma(Y_0, Y_1, ...,...
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1answer
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Prove Doob's using a certain Lemma
I am to prove Doob's (d) in the red box below:
What I tried:
Since $T < \infty$ a.s., we have
$$E[X_T] = E[\lim X_{T \wedge n}].$$
By Fatou's Lemma, we have
$$E\left[\lim X_{T \wedge n}\right] ...
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2answers
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Probability of being $\$5$ up after $25$ plays of a game of Heads and Tails (fair coin) [duplicate]
In a game of heads and tails with a fair coin - you win $\$1$ if heads; lose $\$1$ if ...
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3answers
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How to show $M_n = X_n^2-n$ is a martingale?
Let $X_n, n = 0, 1, 2, . . .$ denote an unbiased Normal Random Walk.
$X_0 = 10$, and $X_{n+1} = X_n + Y_{n+1}$, with $\{Y_n\}$ are i.i.d. $N(0, 1)$.
Then how can I show that:
A) $M_n = X_n^2-n$ is a ...
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1answer
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How to assess the functional form of covariates in the Cox model with martingale residuals in R?
I want to find if the functional forms of covariates in my Cox model are linear. I understand the way to do this is to plot the Martingale residuals against the covariate of interest.
I have found ...
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1answer
470 views
Martingale and deterministic functions
Suppose:
$u_t \sim N(0,1) \ iid.$, $X_t = g(X_{t-1}) \cdot u_t$ whereas $g(X)$ can be any deterministic function.
Is this sufficient to define a martingale?
So does it hold: $E(X_t|X_{t-1}, \ldots , ...
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1answer
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Basic question about the filtration in the martingale formed by sum of iid random variables
It is known that if $X_i$ are iid, $E(|X_i|) < \infty$ and $E(X_i) = 0$ then $S_n = \sum_1^n X_i$ is a martingale. Suppose all $X_i$ are defined wrt sample space $\Omega$.
I don't understand why $...
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1answer
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Limiting behavior of a martingale
This is a homework question:
Suppose that $X_0=1$ and that for $n\geq 1$ $$X_n\sim \left\{
\begin{array}{l l}
U(0,X_{n-1}) & \quad \text{with probability $1-X_{n-1}/2$}\\
U(X_{n-1},1) ...