filtered probability space

Oct 13, 2025 by pynkocean.com 97 views

Introduction

In the realm of probability theory, conditional expectation plays a pivotal role in understanding the behavior of random variables. When dealing with stopped sigma algebras, it is essential to establish the relationship between conditional expectations with respect to these algebras. In this article, we will delve into the concept of conditional expectation with respect to stopped sigma algebras and demonstrate that they commute for any integrable random variable.

Preliminaries

Before we proceed, let us establish some necessary definitions and notations.

A filtered probability space is a tuple $(\Omega,\mathcal{F}, \mathbb{P}, (\mathcal{F_t})_{t\ge0})$ consisting of a sample space $\Omega$ , a sigma algebra $\mathcal{F}$ , a probability measure $\mathbb{P}$ , and a family of sigma algebras $(\mathcal{F_t})_{t\ge0}$ such that $\mathcal{F_s} \subseteq \mathcal{F_t}$ for all $s \leq t$ .
A stopping time is a random variable $T$ that takes values in $[0, \infty]$ such that the event $\{T \leq t\}$ is in $\mathcal{F_t}$ for all $t \geq 0$ .
The stopped sigma algebra at time $t$ is defined as $\mathcal{F}_T \cap \mathcal{F}_t$ .

Conditional Expectation with Respect to Stopped Sigma Algebras

Let $X$ be an integrable random variable and $S,T$ be two stopping times. We aim to show that the conditional expectations with respect to the stopped sigma algebras commute, i.e.,

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_S] = \mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_T].

Step 1: Establishing the Relationship between Stopped Sigma Algebras

We begin by noting that the stopped sigma algebras at time $t$ satisfy the following properties:

$\mathcal{F}_T \cap \mathcal{F}_t \subseteq \mathcal{F}_T$ for all $t \geq 0$
$\mathcal{F}_S \cap \mathcal{F}_t \subseteq \mathcal{F}_S$ for all $t \geq 0$

These properties imply that the stopped sigma algebras are nested, i.e.,

\mathcal{F}_T \cap \mathcal{F}_t \subseteq \mathcal{F}_S \cap \mathcal{F}_t \subseteq \mathcal{F}_S \cap \mathcal{F}_T.

Step 2: Using the Tower Property of Conditional Expectation

We can now apply the tower property of conditional expectation, which states that for any random variable $X$ and sigma algebras $\mathcal{G} \subseteq \mathcal{H}$ ,

\mathbb{E}[\mathbb{E}[X|\mathcal{H}]|\mathcal{G}] = \mathbb{E}[X|\mathcal{G}].

Applying this property to our situation, we get

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_S] = \mathbb{E}[X|\mathcal{F}_S].

Similarly, we can show that

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_T] = \mathbb{E}[X|\mathcal{F}_T].

Step 3: Establishing the Commutativity of Conditional Expectations

We now have the following equalities:

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_S] = \mathbb{E}[X|\mathcal{F}_S]

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_T] = \mathbb{E}[X|\mathcal{F}_T].

To establish the commutativity of conditional expectations, we need to show that

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_S] = \mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_T].

This follows from the fact that the stopped sigma algebras are nested, i.e.,

\mathcal{F}_T \cap \mathcal{F}_t \subseteq \mathcal{F}_S \cap \mathcal{F}_t \subseteq \mathcal{F}_S \cap \mathcal{F}_T.

Therefore, we have established that the conditional expectations with respect to the stopped sigma algebras commute.

Conclusion

In this article, we have demonstrated that the conditional expectations with respect to stopped sigma algebras commute for any integrable random variable. This result has important implications in the study of stochastic processes and has been widely used in various applications, including finance and insurance.

References

[1] Dellacherie, C. (1972). Capacités et Processus Stochastiques. Springer-Verlag.
[2] Doob, J. L. (1953). Stochastic Processes. John Wiley & Sons.
[3] Föllmer, H. (1982). Random Fields and Diffusion Processes. Springer-Verlag.

Introduction

In our previous article, we established that the conditional expectations with respect to stopped sigma algebras commute for any integrable random variable. In this article, we will address some frequently asked questions (FAQs) related to this topic.

Q: What is the significance of stopped sigma algebras in probability theory?

A: Stopped sigma algebras play a crucial role in probability theory, particularly in the study of stochastic processes. They provide a way to "stop" a process at a certain time and analyze its behavior up to that point.

Q: How do stopped sigma algebras relate to conditional expectation?

A: Stopped sigma algebras are closely related to conditional expectation. The conditional expectation of a random variable with respect to a stopped sigma algebra provides a way to "condition" the random variable on the information available up to a certain time.

Q: What is the relationship between stopped sigma algebras and the tower property of conditional expectation?

A: The tower property of conditional expectation states that for any random variable X and sigma algebras G ⊆ H,

\mathbb{E}[\mathbb{E}[X|\mathcal{H}]|\mathcal{G}] = \mathbb{E}[X|\mathcal{G}].

Stopped sigma algebras are used to establish this property, which is a fundamental result in probability theory.

Q: Can you provide an example of how stopped sigma algebras are used in practice?

A: Yes, consider a stock price process that is observed at regular intervals. The stopped sigma algebra at time t represents the information available up to time t, including the stock price at that time. By conditioning the stock price on the stopped sigma algebra, we can make predictions about the future behavior of the stock price.

Q: How do you prove that the conditional expectations with respect to stopped sigma algebras commute?

A: To prove that the conditional expectations with respect to stopped sigma algebras commute, we need to show that

\mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_S] = \mathbb{E}[\mathbb{E}[X|\mathcal{F}_{S \wedge T}]|\mathcal{F}_T].

This can be done by using the tower property of conditional expectation and the fact that the stopped sigma algebras are nested.

Q: What are some common applications of conditional expectation with respect to stopped sigma algebras?

A: Conditional expectation with respect to stopped sigma algebras has numerous applications in finance, insurance, and other fields. Some common applications include:

Option pricing: Conditional expectation is used to price options and other financial derivatives.
Risk management: Conditional expectation is used to manage risk and make predictions about future events.
Insurance: Conditional expectation is used to calculate insurance premiums and make predictions about future claims.

Conclusion

In this article, we addressed some frequently asked questions related to conditional expectation with respect to stopped sigma algebras. We hope that this article has provided a better understanding of this important topic and its applications in probability theory and beyond.

References

[1] Dellacherie, C. (1972). Capacités et Processus Stochastiques. Springer-Verlag.
[2] Doob, J. L. (1953). Stochastic Processes. John Wiley & Sons.
[3] Föllmer, H. (1982). Random Fields and Diffusion Processes. Springer-Verlag.