Proof: How do we use Ito's formula

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Homework Help Overview

The discussion revolves around the application of Ito's formula in the context of stochastic calculus, specifically related to the expectation of powers of a Wiener process at a fixed time. The original poster seeks to prove a relationship involving the expected value of these powers.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the definition of the expectation notation and the nature of the Wiener process. There are attempts to clarify the relationship between the expected value and the application of Ito's formula.

Discussion Status

Some participants have provided insights into the nature of the problem, suggesting that it may not require Ito's formula for a straightforward solution. Others have raised questions about the definitions and assumptions involved, indicating a mix of interpretations and approaches being considered.

Contextual Notes

There is mention of the original poster's lack of experience with induction, and some participants express uncertainty about the correct interpretation of the expectation notation used in the problem statement.

squenshl
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Homework Statement


For all integers n >= 1 define zn = E[W(1)]n. Use Ito's formula to prove that zn+2 = (n+1)zn. Compute zn for all integers n >= 1. z = mu.


Homework Equations





The Attempt at a Solution


How do we use Ito's formula, do we use it directly?
 
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It looks like you're doing some work in stochastic here, but it's impossible to tell what you're trying to do. Could you define a few more things?

I assume E[] is the expectation, what is W(1)?
 


Sorry.
I have proved the Ito formula for the special case W(1)3 = 3*integral from 0 to 1 of W(1)2 dW(t) + 3*integral from 0 to 1 of W(1) dt
 
I was told to try doing it by induction but I have never done induction before. Please help.
 
squenshl said:

Homework Statement


For all integers n >= 1 define zn = E[W(1)]n. Use Ito's formula to prove that zn+2 = (n+1)zn. Compute zn for all integers n >= 1. z = mu.


Homework Equations





The Attempt at a Solution


How do we use Ito's formula, do we use it directly?

If by {W(t)} you mean a standard Wiener process with W(0)=0, then calculation of E[W(1)^n] does not need Ito's formula (although you could use Ito, but that would be doing it the *hard* way). Your problem, as written, does not involve stochastic integration, but is just a simple problem in elementary probability theory! Think about the nature of W(t): what is its probability distribution for any fixed value of t?

RGV
 
Both the problem and the title of the original post say to use Ito's formula, so we should consider how to do this.

Does [itex]E(W(1))^n[/itex] mean [itex]E(W(1)^n)[/itex]

I'm not an expert on the stochastic calculus. So let me ask if [itex]E(W(t)^n)[/itex] , as a function of T, is equal to [itex]\int_0^T W(t)^n dW_t[/itex]? If so, perhaps section 1.8 of these class notes is relevant: http://www.google.com/url?sa=t&sour...sg=AFQjCNG1sNKK8JK-WNvfqVq8MHAz6dXmug&cad=rja
 
Stephen Tashi said:
Both the problem and the title of the original post say to use Ito's formula, so we should consider how to do this.

Does [itex]E(W(1))^n[/itex] mean [itex]E(W(1)^n)[/itex]

I'm not an expert on the stochastic calculus. So let me ask if [itex]E(W(t)^n)[/itex] , as a function of T, is equal to [itex]\int_0^T W(t)^n dW_t[/itex]? If so, perhaps section 1.8 of these class notes is relevant: http://www.google.com/url?sa=t&sour...sg=AFQjCNG1sNKK8JK-WNvfqVq8MHAz6dXmug&cad=rja

The answer to your question is NO. If f is a C^2 function, and W(t) is a standard Wiener process, the Ito formula says: for [tex]Y(t) = f(W(t))[/tex] we have
[tex]\displaystyle dY = f'(W) dW + \frac{1}{2} f''(W) dt[/tex]
Apply this to f(W) = W^n and use the fact that {W(t)} is non-anticipatory (i.e., events in {W(s), s > t} are independent of those in {W(s), s <= t}) to simplify the expectation E[d(W(t)^n)] = dE[W(t)^n] and get an ODE connecting Fn(t) to F_{n-2}(t), where Fk(t) = E[W(t)^k]. Then use the known values of F1(t) and F2(t) to get all the Fn(t), at least in principle. As I said, this is doing it the hard way.

RGV
 

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