Quadratic Variation of a Poisson Process?

In summary, a user on PhysicsForums asked for help with finding the quadratic variation of a Poisson process. They explained that their professor did not have a textbook and they were struggling to find a non-zero answer. Another user suggested partitioning the interval and taking the limit as the subintervals become arbitrarily small. The original user then asked if they were trying to find the expected value and clarified that the largest subinterval of time should approach zero. Another user explained that for a Poisson process, the quadratic variation is equal to itself due to the pure jump nature of the process. They also added that the distribution of the process does not affect the calculation. The original user thanked them for their explanation.
  • #1
RedZone2k2
9
0
Hey guys,

This is my first post on PhysicsForums; my friend said that this was the best place to ask questions about math.

Anyways, I have to find the Quadratic Variation of a Poisson Process.

My professor doesn't have a class textbook (just some notes that he's found online), and although I can find a general formula for quadratic variation, I can't seem to plug it in, and get a non-zero answer. My professor said that this question should be pretty easy, but I'm totally lost.

If you guys could offer any help, that would be great. If you guys have any more questions, let me know!

Thanks!
 
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  • #2
So here is what I have so far:

The quadratic variation is the sum of all [N_t_(i+1)-N_t_i]^2, with the max |N_t_(i+1)-N_t_i| --> 0.

Since Poisson distributions are independent, and we want to find N(t), partition the interval [0,t] to n subintervals. Let h = max |N_t_(i+1)-N_t_i|. So, since I'm taking the limit as h becomes arbitrarily tiny, I can rewrite this sum as n*(E(N_h))^2 right? But then, I get n*(lam*(1\n))^2, which goes to zero. This can't be right, so I must have made at least one error here right?
 
  • #3
First, are you trying to find the expected value of the quadratic variation? Second, are you sure it's not max ti+1-ti --> 0. In other words, the largest subinterval of time goes to zero? If it is N(ti+1) - N(ti) --> 0, then yeah, it looks like the answer would have to be zero.

I am not familiar with the term quadratic variation, but I would guess that it is supposed to result in a Riemann sum, or integral.
 
  • #4
A Poisson process has quadratic variation equal to itself.

This is because it is a pure jump process with jump sizes equal to 1. If Nt is the Poisson process then the only contribution to the quadratic variation [N] comes from the jumps,

[tex]
[N]_t=\sum_{s\le t} \Delta N_s^2 = \sum_{s\le t,\Delta N_s\not=0}1 = \sum_{s\le t}\Delta N_s=N_t.
[/tex]
 
  • #5
Just to add - the distribution of the process doesn't matter. Once you know that it is piecewise constant then you can conclude that the quadratic variation is just the sum of the squares of the jumps, which is easily calculated as I did above.
 
  • #6
That makes a lot of sense. Thank you!
 

1. What is a Poisson process?

A Poisson process is a mathematical model used to describe the occurrence of random events over time. It is characterized by the following properties: the events occur independently, the number of events in a certain time interval is proportional to the length of the interval, and the probability of an event occurring is constant over time.

2. How is the quadratic variation of a Poisson process defined?

The quadratic variation of a Poisson process is a measure of the amount of variation or fluctuation in the process over time. It is defined as the sum of squared differences between the number of events observed in consecutive time intervals.

3. What is the relationship between the quadratic variation of a Poisson process and its intensity?

The intensity of a Poisson process is the rate at which events occur. The quadratic variation is directly proportional to the intensity, meaning that as the intensity increases, so does the amount of variation in the process.

4. How is the quadratic variation of a Poisson process calculated?

The quadratic variation of a Poisson process can be calculated using the formula V(t) = λt, where V(t) is the quadratic variation at time t and λ is the intensity of the process. This formula assumes that the time intervals are of equal length.

5. What are some applications of the quadratic variation of a Poisson process?

The quadratic variation of a Poisson process has various applications in fields such as finance, physics, and biology. For example, it can be used to model stock prices, estimate the size of particles in a suspension, and study the spread of disease in a population.

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