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Girsanov Densities and Uniqueness of the Pricing Measure

Article Quant Q&A · Author: BCLC

Summary

The document examines a Brownian change-of-measure problem in which a process equals Brownian motion plus a deterministic drift. Applying Girsanov’s theorem with the drift as its kernel constructs an equivalent measure under which the process is Brownian, and Novikov’s condition is cited to ensure the exponential density is a martingale. The question is whether this construction identifies the measure specified in the problem, or merely supplies one possible measure.

The accepted response argues that the stated conditions do not uniquely determine the Radon–Nikodym density: additional density components can preserve the required martingale property, so the Girsanov construction gives a candidate rather than necessarily the only measure. It recommends specifying the density first and then verifying equivalence and the desired process property. The discussion is conceptual rather than a full proof, and its broad claim about alternative densities needs careful interpretation: uniqueness depends on the exact filtration and on requiring the process to be Brownian, not merely a martingale.

Key ideas

  • Girsanov’s theorem constructs a measure under which a drift-adjusted Brownian process is Brownian.
  • Novikov’s condition is used to establish that the exponential density is a martingale.
  • A measure constructed by the theorem need not be identified with an independently stated measure without a uniqueness argument.
  • Whether the measure is unique depends on the filtration and on the precise process requirements.

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Full text
# 28003


# Given $\mathbb Q$ and $X_t$ is $\mathbb Q$-Brownian, find $\frac{d\mathbb Q}{d\mathbb P}$ / Uniqueness of Brownian or Radon-Nikodym derivative












The problem:

> Let $T >0$, and let $(\Omega, \mathscr F, \{ \mathscr F_t \}_{t \in [0,T]}, \mathbb P)$ be a filtered probability space where $\mathscr F_t = \mathscr F_t^W$ where $W = \{W_t\}_{t \in [0,T]}$ is standard $\mathbb P$-Brownian motion. Let $X = \{X_t\}_{t \in [0,T]}$ be a stochastic process where $X_t = W_t + \sin t$, and let $\mathbb Q$ be an equivalent probability measure s.t. $X$ is standard $\mathbb Q$-Brownian motion. Give $\frac{d \mathbb Q}{d \mathbb P}$.

Girsanov Theorem:

> Let $T >0$, and let $(\Omega, \mathscr F, \{ \mathscr F_t \}_{t \in [0,T]}, \mathbb P)$ be a filtered probability space where $\mathscr F_t = \mathscr F_t^W$ where $W = \{W_t\}_{t \in [0,T]}$ is the standard $\mathbb P$-Brownian motion. Let the Girsanov kernel $\{\theta_t\}_{t \in [0,T]}$ be a $\mathscr F_t$-adapted stochastic process s.t. $\int_0^T \theta_s^2 ds < \infty$ a.s. and $\{L_t\}_{t \in [0,T]}$ is a $( \mathscr F_t , \mathbb P)$ martingale where $$L_t := \exp(-\int_0^t \theta_s dW_s - \frac 1 2 \int_0^t \theta_s^2 ds)$$ Let $\mathbb Q$ be the probability measure defined by $$Q(A) = \int_A L_T dP \ \forall A \in \ \mathscr F$$ or $$L_T = \frac{d \mathbb Q}{d \mathbb P}$$ Then $\{W_t^Q\}_{t \in [0,T]}$ defined by $$W_t^Q := W_t + \int_0^t \theta_s ds$$ is standard $\mathbb Q$-Brownian motion.

The solution given:

$$X_t = W_t + \int_0^t \cos s ds$$

Let $\theta_t = \cos t$:

- It is $\mathscr F_t$-adapted

- $\int_0^T \theta_s^2 ds < \infty$ a.s.

- $E[\exp(\frac 1 2 \int_0^T \theta_t^2 dt)] < \infty$

Then $\{L_t\}_{t \in [0,T]}$ is a $( \mathscr F_t , \mathbb P)$ martingale, by Novikov's condition, where

$$L_t := \exp(-\int_0^t \cos s dW_s - \frac 1 2 \int_0^t \cos^2 s ds)$$

Thus, by Girsanov's Theorem, we have

$$\frac{d\mathbb Q}{d\mathbb P} = L_T...?$$

How exactly does that last line follow?

What I find strange is that the Girsanov Theorem defines $\mathbb Q$ and then concludes $X_t$ is standard $\mathbb Q$-Brownian motion while the problem says there is some $\mathbb Q$ s.t. $X_t$ is standard $\mathbb Q$-Brownian motion and then asks about $\frac{d \mathbb Q}{d \mathbb P}$. Is the problem maybe stated wrong?

To say that $L_T$ is indeed the required density $\frac{d \mathbb Q}{d \mathbb P}$, I think we need to use the converse of the Girsanov Theorem), or maybe the problem should instead give us $\frac{d \mathbb Q}{d \mathbb P}$ and then ask us to show that $L_T = \frac{d \mathbb Q}{d \mathbb P}$ possibly showing that $E[\frac{d \mathbb Q}{d \mathbb P} | \mathscr F_t] = L_t$ or some other route.

I tried something slightly different:

I define $\hat{\mathbb P}$ s.t.

$$L_T = \frac{d\hat{\mathbb P}}{d\mathbb P}$$

or

$$\hat{\mathbb P} = \int_A L_T d\mathbb P$$

It follows by Girsanov Theorem that $X_t$ is standard $\hat{\mathbb P}$-Brownian motion. Since we are given that there is some $\mathbb Q$ equivalent to $\mathbb P$ s.t. $X_t$ is also standard $\mathbb Q$-Brownian motion, it follows by the uniqueness of the Radon-Nikodym derivative that

$$\frac{d\hat{\mathbb P}}{d\mathbb P} = \frac{d\mathbb Q}{d\mathbb P}$$

$\therefore, \frac{d\mathbb Q}{d\mathbb P}$ is given by $L_T$.

Is that right? I think I'm missing a step somewhere.

So, is that indeed what the solution given is meant to be but just omitted pointing out uniqueness of the Radon-Nikodym derivative, if such justification is right?

Edit based on this: Even if Radon-Nikodym derivative is unique, $\mathbb Q$ may not be unique? If so, is it then that $\hat{\mathbb P}$ is merely a candidate for one of many possible $\mathbb Q$'s?

I think we conclude $\hat{\mathbb P} = \mathbb Q$ based on $X_t$ being standard Brownian motion under both measures. Is there a proposition for that? Uniqueness of Brownian motion measure or something?

## Answer by Quantuple (score 7, accepted)

https://quant.stackexchange.com/a/28006

IMHO the problem isn't stated correctly indeed, in the sense that the Radon-Nikodym derivative provided as the "solution" is not the unique way to define a measure $\mathbb{Q}$ equivalent to $\mathbb{P}$ and under which $X_t$ is a martingale. Just take $$\frac {d\mathbb{Q}}{d\mathbb{P}} =\mathcal{E}\left(-\int_0^t \cos(s) dW_s + a\right)$$ for any $a \in \mathbb{R}$ (or any finite variation process for that matter, the point being that $a $ should not contribute in terms of quadratic (co)variation) and $\mathcal {E}(.) $ figures the stochastic (or Doleans-Dade) exponential. Note that the solution provided corresponds to picking $a=0$.

As such, I think that the exercice should have been written the other way around as you mention in your question. Something like: show that, given the following Radon-Nikodym derivative specification, the resulting measure $\mathbb{Q}$ is equivalent to the original measure $\mathbb{P}$ and such that $(X_t)_{t\in [0,T]}$ is a $(\mathbb{Q},\mathcal{F}_t^W)$-martingale.

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.