A Question about Stochastic Integral

In summary: Your name]In summary, the Ito Integral int_0^t e^s dB_s is normally distributed, which can be proven by showing that it is a linear combination of normal random variables, has a mean of 0 and a variance of t, and tends towards a normal distribution as the number of Riemann sums increases.
  • #1
hzzhangyu
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Homework Statement



How to prove that the Ito Integral int_0^t e^s dB_s is normally-distributed, for a given t?

Homework Equations





The Attempt at a Solution



This Ito Integral could be defined as a R-S Integral, and the Riemann Sum should be a linear function of normal r.v.s, thus the Riemann Sum is normal. However I don't know how to prove that the limit of a sequence of normal random variable is normal... Or is there another way to prove it?

Thanks!
 
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  • #2




Thank you for your question. The Ito Integral int_0^t e^s dB_s is indeed normally distributed, and this can be proven using the following steps:

1. First, recall that the Ito Integral is defined as the limit of Riemann sums, where each Riemann sum is a linear combination of normal random variables. This means that the Ito Integral itself is a linear combination of normal random variables, and therefore it is also normally distributed.

2. Next, we can use the properties of normal distributions to show that the Ito Integral is normally distributed with mean 0 and variance t. Recall that the mean of a linear combination of random variables is equal to the linear combination of their means. In this case, the mean of the Ito Integral is 0, since the mean of each Riemann sum is 0. Similarly, the variance of a linear combination of independent random variables is equal to the sum of their variances. Since the Riemann sums are independent, the variance of the Ito Integral is equal to the sum of the variances of the Riemann sums, which is t.

3. Finally, we can use the central limit theorem to show that the Ito Integral is normally distributed. The central limit theorem states that the sum of a large number of independent and identically distributed random variables will tend towards a normal distribution. Since the Riemann sums are independent and identically distributed, as the number of Riemann sums increases, the Ito Integral will tend towards a normal distribution.

I hope this helps to answer your question. If you have any further questions or concerns, please let me know. Best of luck with your research.


 

FAQ: A Question about Stochastic Integral

What is a stochastic integral?

A stochastic integral is a mathematical tool used in stochastic calculus to calculate the integral of a stochastic process, which is a random function that evolves over time. It is used to model and analyze random phenomena in various fields such as finance, physics, and engineering.

How is a stochastic integral different from a regular integral?

A stochastic integral takes into account the random nature of a stochastic process while a regular integral deals with deterministic functions. This means that a stochastic integral involves probabilistic calculations and can result in a random variable, while a regular integral produces a single numerical value.

What are some applications of stochastic integrals?

Stochastic integrals are widely used in finance to model and analyze the behavior of financial assets, such as stock prices and interest rates, which are inherently random. They are also used in physics to study the movement of particles in a random environment and in engineering to analyze the performance of systems with random inputs.

What is the difference between a Stratonovich integral and an Itô integral?

The Stratonovich integral and the Itô integral are two different approaches to calculating stochastic integrals. The main difference is that the Stratonovich integral takes the average of the integrand over the interval, while the Itô integral takes the value of the integrand at the beginning of the interval. This results in different formulas and interpretations of the integral.

Do stochastic integrals have real-world applications?

Yes, stochastic integrals have numerous real-world applications in various fields, including finance, physics, engineering, and biology. They are used to model and analyze random phenomena, making them an essential tool for understanding and predicting complex systems and processes.

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