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Why Combining Brownian Motions Does Not Preserve the Market Filtration

Article Quant Q&A · Author: Steven Hunt

Summary

The example considers a riskless asset and one risky asset whose dynamics are driven by two Brownian motions, while the information available to traders is generated by both. Although the asset equation can be rewritten using their scaled sum, that sum alone does not capture all the information in the original filtration. Market completeness depends on the filtration through the martingale representation property, not simply on the number of Brownian terms visible in the asset equation.

The answer illustrates the information loss by considering an event defined using the difference of the two Brownian motions. That event has positive probability, but cannot be determined from their sum alone. It then gives an indicator claim tied to the event as an example of a payoff that cannot be replicated. The argument is an illustrative mathematical explanation, rather than a full formal treatment of filtration equality or replication conditions.

Key ideas

  • Rewriting asset dynamics with a combined Brownian motion does not automatically reduce the market's information filtration.
  • The sum of two Brownian motions does not reveal their difference.
  • Completeness depends on martingale representation relative to the underlying filtration.
  • A claim depending on information absent from the traded asset dynamics may be unreplicable.

Tags

Full text
# standard/brownian market with different brownian motion


# standard/brownian market with different brownian motion












Consider for simplicity the following brownian market:

$$dS^0_t= r S^0_tdt$$

$$dS^1_t= S^1_t(r dt + dW^1_t + dW^2_t) $$

where the filtration is generated by $W^1,W^2$

Consider now $W_t:= \frac{1}{2}(W^1_t + W^2_t)$, which is a Brownian motion, too.

When I substitute $W_t$ in the above financial market, I would have $1$ Brownian motion and $1$ risky asset, so I could conclude that the market is complete. But that is not correct, since completness depends on martingale representation, which depends again on the underlying filtration.

But why do I have to pick another filtration in this context, since the filtration generated by $W^1,W^2$ is the same as being generated by $W$?

## Answer by algebruh (score 1)

https://quant.stackexchange.com/a/67933

tl;dr: informally: You cannot know the value of the difference of two random variables by knowing their sum.

Consider the following set $A =\{ \omega \in \Omega | W_1(t)(\omega) - W_2(t)(\omega) \in [0,1] \}$ This set is of course in the Filtration generated by $W_1$ and $W_2$ since the addition of measurable functions is measurable. Is this set in the (augmented) generated Filtration of $W$? For that either $P(A) = 0$ (because we consider the augmented filtration) or it exists a borel set $B$ (a set that can be build from intervals through countable set operations) s.t. $$\{ \omega \in \Omega | W(\omega)(t) \in B \} =A \ \mathbb{P}-a.s.$$ (you don't need to consider past time points since the brownian filtration is increasing ).

$P(A) > 0 $ since $W_1(t)- W_2(t)\sim \mathcal{N}(0,2t) .$

Assume it exists such a $B$. Then

$$ \{ \omega \in \Omega |W_1(t)(\omega) + W_2(t)(\omega)) \in B \}=\{ \omega \in \Omega | W_1(t)(\omega) - W_2(t)(\omega) \in [0,1] \} $$ (we absorb the 0.5 factor into the set B) Which is equivalent to:

$$ X + Y \in B \Leftrightarrow X-Y \in [0,1] \ \mathbb{P}-a.s. \ (\#)$$ where $X,Y$ are iid normally distributed. This is equivalent to

$$ Y \in B-X \Leftrightarrow Y \in [-1,0] \ \mathbb{P}-a.s.$$ Thus:

$$ B-X =[-1,0], \mathbb{P}-a.s.$$

inputting into LHS of (#):

$$ Y\in [-1,0] \ \mathbb{P}-a.s.$$

Which is wrong since $ Y$ is normally distributed.

Thus the filtrations are not equal

As an example for incompleteness: The derivative $H(t) = \mathbb{1}_{A}\mathbb{1}_{t}$ cannot be replicated.

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.