Integral with respect to Brownian motion.

In summary: GFyZSBwcm9jZXNzIGNvbnRlbnQgd2l0aCB0aGUgc3RvcHRpY3Rpb24/IEkgbG9nIGFuZCBJIGRvbid0IHJlc3BvbnNlIG9mIGFuIGF0ZGljdGFibGUgcHJvYmxlbSwgd2hlcmUgdGFrZXMgYSB3aWVuZXIgcHJvYmxlbT8gTWF5IGxlYXNlIHNsaWRlcyBhc3NlcnQgdGhpcyBtZWFzdXJ
  • #1
operationsres
103
0
Suppose that [itex]\sigma(t,T)[/itex] is a deterministic process, where [itex]t[/itex] varies and [itex]T[/itex] is a constant. We also have that [itex]t \in [0,T][/itex]. Also [itex]W(t)[/itex] is a Wiener process.

My First Question

What is [itex]\displaystyle \ \ d\int_0^t \sigma(u,T)dW(u)[/itex]? My lecture slides assert that it's equal to [itex]\sigma(t,T)dW(t)[/itex] but I'm not sure why. So my question is "Why"?

My Second Question

What is [itex]\displaystyle \ \ d\int_a^t \sigma(u,T)dW(u)[/itex], where [itex]a \in (0,t)[/itex].

_________________________________

Thanks!
 
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  • #2
operationsres said:
Suppose that [itex]\sigma(t,T)[/itex] is a deterministic process, where [itex]t[/itex] varies and [itex]T[/itex] is a constant. We also have that [itex]t \in [0,T][/itex]. Also [itex]W(t)[/itex] is a Wiener process.

My First Question

What is [itex]\displaystyle \ \ d\int_0^t \sigma(u,T)dW(u)[/itex]? My lecture slides assert that it's equal to [itex]\sigma(t,T)dW(t)[/itex] but I'm not sure why. So my question is "Why"?

My Second Question

What is [itex]\displaystyle \ \ d\int_a^t \sigma(u,T)dW(u)[/itex], where [itex]a \in (0,t)[/itex].

_________________________________

Thanks!

I've said it before and I will say it again: go back to the basics. What is meant by the stochastic integral? If Y(t) is a stochastic process, what do we mean by dY(t)? All this material is explained in books (admittedly, some almost unreadable), and in numerous web pages and the like. There is simply no substitute for getting the background first.

RGV
 

1. What is Brownian motion?

Brownian motion is a random motion of particles suspended in a fluid, caused by the collision of fluid molecules with the particles. It was first observed by botanist Robert Brown in 1827 and is now understood as a fundamental aspect of the motion of particles in a fluid.

2. How is Brownian motion related to integrals?

Brownian motion can be described mathematically using stochastic calculus, which involves integrals with respect to the motion. These integrals help to model the unpredictable and random nature of Brownian motion.

3. What is an integral with respect to Brownian motion?

An integral with respect to Brownian motion is a mathematical concept used to describe the cumulative effect of random processes, such as Brownian motion. It involves taking the sum of infinitesimally small changes in a variable over a given time period.

4. How is an integral with respect to Brownian motion calculated?

There are various methods for calculating integrals with respect to Brownian motion, such as using stochastic differential equations or the Itô calculus. These methods involve breaking the integral down into smaller parts and using mathematical techniques to solve for the final result.

5. What are some applications of integrals with respect to Brownian motion?

Integrals with respect to Brownian motion have many applications in mathematics, physics, finance, and other fields. They can be used to model and analyze random processes, such as stock market fluctuations, the movement of molecules in a liquid, or the diffusion of pollutants in the environment.

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