Integral with respect to Brownian motion.

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SUMMARY

The discussion centers on the evaluation of stochastic integrals with respect to Brownian motion, specifically the expressions \(\displaystyle d\int_0^t \sigma(u,T)dW(u)\) and \(\displaystyle d\int_a^t \sigma(u,T)dW(u)\). Participants clarify that \(\displaystyle d\int_0^t \sigma(u,T)dW(u)\) equals \(\sigma(t,T)dW(t)\) due to the properties of stochastic calculus. The importance of understanding the foundational concepts of stochastic integrals and Wiener processes is emphasized as crucial for grasping these expressions.

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  • Understanding of stochastic calculus
  • Familiarity with Wiener processes (Brownian motion)
  • Knowledge of deterministic processes in stochastic contexts
  • Basic concepts of stochastic integrals
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  • Learn about Itô's lemma and its applications
  • Explore the role of deterministic processes in stochastic calculus
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Mathematicians, financial analysts, and researchers in quantitative finance who are working with stochastic processes and seeking to deepen their understanding of Brownian motion and stochastic integrals.

operationsres
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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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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
 

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