Check Martingale Sequences from i.i.d. Variables | Stats SE

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Discussion Overview

The discussion revolves around the identification of martingale sequences derived from a sequence of independent, identically distributed random variables. Participants explore specific sequences and seek guidance on how to determine if they meet the criteria for martingales, touching on foundational concepts in probability and statistics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related
  • Mathematical reasoning

Main Points Raised

  • One participant reproduces a question regarding whether specific sequences are martingales, including sequences defined by exponential functions and sums involving random variables.
  • Another participant encourages the original poster to show their work, suggesting that the third sequence is common and relatively straightforward to analyze.
  • It is noted that foundational issues related to conditional expectations may be hindering the original poster's understanding.
  • A suggestion is made to consult specific textbooks, including "Blitzstein and Hwang" and "Karlin and Taylor," for foundational knowledge on conditional expectations and martingales.
  • One participant expresses uncertainty about accessible introductory materials on the subject, recommending a chapter from a specific book while acknowledging the difficulty of the suggested texts.
  • There is a mention of the potential for finding educational videos online, though no specific resources are provided.

Areas of Agreement / Disagreement

Participants generally agree on the need for foundational understanding of conditional expectations to tackle the problem, but there is no consensus on specific methods or solutions for determining if the sequences are martingales.

Contextual Notes

Participants highlight the complexity of the topic and the potential challenges in finding suitable introductory materials. The discussion reflects varying levels of familiarity with the concepts involved.

Who May Find This Useful

Students and practitioners in mathematics, statistics, and quantitative finance who are interested in martingales and stochastic processes may find this discussion relevant.

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Dhamnekar Winod said:
How to answer this question $\rightarrow$https://stats.stackexchange.com/q/398321/72126
Hello, I am reproducing the question in the hyperlink given in #1 of this thread so that the viewers of this MHB will conveniently read it.

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 following sequences are Martingales.

$$M_n^{(1)}=\frac{e^{\theta S_n}}{(\cosh{\theta})^n}$$$$M_n^{(2)}=\displaystyle\sum_{k=1}^n sign(S_{k-1})Y_k, n\geq 1,M_0^{(2)}=0$$$$M_n^{(3)}=S_n^2 -n$$

I have no idea how to answer these questions. If any member knows the correct answers to these questions may reply with correct answers.
 
I'd like to see some work from you on these. The third one in particular is extremely common and easy. The first is pretty straightforward if you know how to manipulate MGFs to get a martingale. As for the second one, since $S_n$ is even iff n is even, it should be relatively straight forward to attempt as well.

If I were in your shoes, I would start by writing out definitions and applying them to the third one. My guess is that you have foundational issues related to conditional expectations that are holding you back.
 
steep said:
I'd like to see some work from you on these. The third one in particular is extremely common and easy. The first is pretty straightforward if you know how to manipulate MGFs to get a martingale. As for the second one, since $S_n$ is even iff n is even, it should be relatively straight forward to attempt as well.

If I were in your shoes, I would start by writing out definitions and applying them to the third one. My guess is that you have foundational issues related to conditional expectations that are holding you back.

Hello,
I am confident that you will reply to this thread because you are the knowledgeable (expert) person in 'Advanced probability and statistics'.

Right now, what happened, I am studying Mathematics, Statistics, Quantitative Finance, R and Octave programming, MS Office (Online) etc. So I don't get any idea to answer these questions.

Please suggest me any reading material , educational videos useful for solving such types of questions.

I found these questions in 'Introduction to Quantitative Finance'. PDF. But the author didn't provide answers to these questions in that PDF.
 
Part of the challenge is that I don't know of an easy introduction to the subject. If I were in your shoes, I would first go through the conditional expectations chapter in the Blitzstein and Hwang book -- that will be useful for martingales and many other things

https://projects.iq.harvard.edu/stat110/home

I think Karlin and Taylor's "A First Course in Stochastic Processes" (try 2nd edition) has a decent chapter on martingales and some extremely good exercises at the end (in particular the 'elementary problems'). Ross's "Stochastic Processes" (2nd edition) has a decent chapter on them. If you want to go the long route, Williams' "Probability with Martingales" is recommended. All 3 of these are difficult books and the first two are typically used in graduate courses on stochastics, while Williams is sometimes grad, sometimes undergrad.

Learning martingales from any of those books are going to take an enormous amount of effort and time. It may well be that your time is better spent elsewhere, for the time being at least.

It certainly is possible that there is an accessible video collection on e.g. youtube that teaches martingales -- I just don't know of any such thing.
 

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