What is a Stochastic Integral and How Does it Differ from a Regular Integral?

In summary, the conversation discusses the definition of a stochastic integral and its similarities to a regular integral. It also touches on the use of variables and functions in determining the behavior of the integral. The Weiner process and its statistical aspects are also mentioned.
  • #1
courtrigrad
1,236
2
Hello all

Let's say we define a stochastic integral as:
[tex] W(t) = \int^{t}_{0} f(\varsigma)dX(\varsigma) = \lim_{n\rightarrow\infty} \sum^{n}_{j=1} f(t_{j-1})(X(t{j})) - X(t_{j-1})) [/tex] with [tex] t_{j} = \frac{jt}{n} [/tex] IS this basically the same definition as a regular integral?

Also if we have [tex] W(t) = \int^{t}_{0} f(\varsigma) dX(\varsigma) [/tex] then does [tex] dW = f(\varsigma) dX [/tex]?

Thanks
 
Physics news on Phys.org
  • #2
In the first integral i can see a strong resemblence with the Riemann sum...As for the second (and for the first too),who's zeta...?

Daniel.
 
  • #3
The Weiner process the one you are looking for and luckily old Norbert worked it out for us. This really becomes more statistical than anything because we have to talk about the average or standard deviation of each step in the integral. It has been a little while and I don't have any notes with me at the present moment but Norbert is the man to look into to wrap your mind around stochastic integrations!
 
  • #4
zeta is a variable corresponding to time
 

Related to What is a Stochastic Integral and How Does it Differ from a Regular Integral?

1. What is a stochastic integral?

A stochastic integral is a mathematical concept used to calculate the area under a stochastically varying curve. It is a generalization of the standard integral, which is used to calculate the area under a deterministic curve.

2. How is a stochastic integral different from a standard integral?

A stochastic integral takes into account the randomness and uncertainty of a curve, while a standard integral assumes a deterministic curve. This means that a stochastic integral can handle more complex and unpredictable data.

3. What are some common applications of stochastic integrals?

Stochastic integrals are commonly used in fields such as finance, economics, and physics to model and analyze random processes. They are also used in the field of statistics to estimate the parameters of a stochastic process.

4. What are the different types of stochastic integrals?

There are several types of stochastic integrals, including the Itô integral, the Stratonovich integral, and the Malliavin integral. These integrals differ in their methods of approximation and their handling of stochastic processes.

5. How are stochastic integrals calculated?

Stochastic integrals are typically calculated using numerical methods, such as Euler's Method or the Milstein Method. These methods involve breaking down the integral into smaller, more manageable pieces and then summing them to approximate the overall area under the curve.

Similar threads

  • Introductory Physics Homework Help
Replies
12
Views
2K
  • Introductory Physics Homework Help
Replies
14
Views
2K
  • Introductory Physics Homework Help
Replies
2
Views
556
  • Introductory Physics Homework Help
Replies
8
Views
1K
  • Introductory Physics Homework Help
Replies
12
Views
275
  • Classical Physics
Replies
0
Views
276
  • Introductory Physics Homework Help
Replies
7
Views
727
  • Calculus and Beyond Homework Help
Replies
2
Views
301
  • Differential Equations
Replies
3
Views
550
  • Introductory Physics Homework Help
Replies
1
Views
243
Back
Top