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Adapted Processes in the Black–Scholes Model

Article Quant Q&A · Author: user10777

Summary

The document clarifies what it means for stock and bank-account price processes to be adapted to a filtration in the Black–Scholes model. Adaptedness means that each process’s value at a given time can be determined from the information available by that time. The stock is driven by Brownian motion, so its path up to a time depends on the Brownian information observed up to then. The bank account follows deterministic growth at a constant interest rate.

Because a deterministic value is measurable with respect to any filtration, the bank-account process is adapted even though it has no Brownian driver. The answers also connect stochastic dynamics with the construction of Ito processes and note that the relevant integrals and calculus must satisfy their usual conditions. This is a conceptual explanation of filtration and adaptedness, not a derivation of option prices or a treatment of stochastic interest rates.

Key ideas

  • A process is adapted when its value at each time is measurable using information available by that time.
  • The stock process is adapted to the Brownian filtration because Brownian motion supplies its uncertainty.
  • A deterministic bank-account process is adapted to any filtration.
  • Writing process dynamics relies on conditions that make the stochastic integrals well defined.

Tags

Full text
# Stochastic process and brownian motion


# Stochastic process and brownian motion












I just read the following and i am having some difficulty to interpret it:

> We begin our analysis in the standard Black-Scholes world consisting of a bank account process of price denoted by $B_t$, and a risky stock process $S_t$, both defined on a filtered probability space $(0, \mathbb{F}, \mathfrak{F}_t, \mathbb{P})$, with the filtration $\mathfrak{F}_t$ generated by the standard Brownian motion $W_t$. Both asset processes are therefore adapted to the filtration $\mathfrak{F}_t$, with local dynamics shown below \begin{eqnarray} \mathrm{d}S_t & = & \mu S_t \mathrm{d}t + \sigma S_t \mathrm{d}W_t,\\ \mathrm{d}B_t & = & r B_t \mathrm{d}t. \end{eqnarray}

The problem is the last sentence in connection with the two equations?

Update: How is $B_t$ adapted to the same filtration $\mathfrak{F}_t$ as $S_t$ since $B_t$ is not driven by any Brownian motion?

## Answer by LocalVolatility (score 2, accepted)

https://quant.stackexchange.com/a/32454

I am not sure I understand your question. If not - then please clarify.

- The process for $S$ follows from the Black-Scholes assumption of the risky asset price following a constant coefficient geometric Brownian motion.

- The process for $B$ follows from the instantaneous interest rate being constant.

- The process being adapted to the filtration $\left( \mathfrak{F}_t \right)_{t \in \mathbb{R}_+}$ simply means that for every $t \in \mathbb{R}_+$, the random variable $S_t$ is $\mathfrak{F}_t$-measurable. Think of this as the information in $\mathfrak{F}_t$ being sufficient to determine the value of $S_t$. Further think of the natural filtration $\mathfrak{F}_t$ of the Brownian motion $W$ as containing all the information of observing $W$ up until time $t$. Given that the process $S$ has only one driving source of uncertainty $W$, it follows that knowing the path of $W$ up to time $t$ is sufficient to determine the path of $S$ up to that time. Consequently, $S$ is adapted to the natural filtration generated by $W$.

Answer to your update:

As Quantuple remarked, the non-random process $B$ is adapted to any filtration. You don't need to know anything about the path of $W$ in order to know the value of $B_t$ for any $t \in \mathbb{R}_+$. I.e., even the information in $\mathfrak{F}_0$ (the trivial sigma-algebra) is sufficient to determine $B_t$. Since $\mathfrak{F}_0 \subseteq \mathfrak{F}_t$ it follows that $B$ is adapted.

## Answer by vanguard2k (score 1)

https://quant.stackexchange.com/a/32463

Your problem seems to lie in the fundamentals of stochastic processes, so you should probalby refresh your knowledge in this field.

Every process, also $W_t$ comes with a "natural" filtration $\mathfrak{F}_t$. It's the minimal (in a certain sense) filtration for which the process is adapted. Adapted means for a process $X_t$ that for every $t$, $X_t$ is measurable on $\mathfrak{F_t}$.

Now to your sentence in question: With the Ito calculus, under certain conditions (basically the stochastic integrals have to be well defined and itos lemma has to hold), you can also "define" a process using its dynamics (also called Ito processes). Thats what the autor does for $S_t$ and $B_t$. Also, the result is an adapted process.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.