Expressing a Wiener process with indicator functions.

In summary, the conversation discusses the equality of two expressions involving a Wiener process, with the speaker attempting to determine if they are equal in distribution. The speaker also mentions their efforts to prove this equality by checking certain conditions for a Wiener process. They express uncertainty about how to proceed with the problem and ask for help.
  • #1
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Homework Statement



Suppose that [itex]W_t[/itex] is a Wiener process (i.e. standard Brownian Motion).

Is it true that [itex]W_t = \mathbf{1}_{\{W_t \geq 0\}}W_t + \mathbf{1}_{\{W_t < 0\}}W_t[/itex] ?

The Attempt at a Solution



No idea. This isn't even homework it's part of my attempt of a solution to a homework problem. It feels correct, as the LHS = RHS in every possible state of the world. But stochastics has surprised me before!

We can at least show that they're equal in distribution, by checking if some of the conditions for a Wiener process hold:

[itex]\text{var}(\mathbf{1}_{\{W_t \geq 0\}}W_t + \mathbf{1}_{\{W_t < 0\}}W_t) = (\mathbf{1}_{\{W_t \geq 0\}}W_t)^2 + (\mathbf{1}_{\{W_t < 0\}}W_t)^2[/itex]
[itex] =\mathbf{1}_{\{W_t \geq 0\}}t + \mathbf{1}_{\{W_t < 0\}}t [/itex]
[itex]= t[/itex]

That's good. Also;

[itex]E[\mathbf{1}_{\{W_t \geq 0\}}W_t + \mathbf{1}_{\{W_t < 0\}}W_t | \mathscr{F}_0] [/itex]
[itex] = 0[/itex]

Which is also good. Then the next steps would be to show that it's continuous everywhere and that increments are stationary and independent.
 
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  • #2
But I don't know how to do that. This is a problem where I just have to guess and check, right? Any help would be greatly appreciated!
 

Related to Expressing a Wiener process with indicator functions.

1. What is a Wiener process?

A Wiener process, also known as a Brownian motion, is a stochastic process that describes the random movement of particles in a fluid or gas. It is often used to model continuous-time processes in physics, finance, and other fields.

2. How is a Wiener process expressed with indicator functions?

A Wiener process can be expressed as a sum of indicator functions, which are mathematical functions that take on the values of 0 or 1 depending on whether a certain condition is met. This representation allows for easier analysis and calculation of probabilities in the process.

3. What is the role of indicator functions in expressing a Wiener process?

Indicator functions help to define the state of the Wiener process at any given time. They indicate whether the process has crossed a certain threshold or boundary, and can be used to calculate probabilities and expected values for the process.

4. Are there any limitations to expressing a Wiener process with indicator functions?

While expressing a Wiener process with indicator functions can be useful for analysis and calculation, it may not always be possible to fully capture the complexity of the process with this representation. Some scenarios may require more advanced mathematical techniques to accurately model the process.

5. How is a Wiener process related to other stochastic processes?

A Wiener process is a specific type of stochastic process that is continuous and has independent, normally distributed increments. It is closely related to other processes such as the random walk and the Ornstein-Uhlenbeck process, and can be used as a building block for more complex models.

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