Weak Solutions for an SDE with a Discontinuous Sign Drift
Summary
The document considers a stochastic differential equation whose drift switches between positive and negative values according to the sign of the state. The drift is bounded but discontinuous, so it fails the usual Lipschitz condition associated with standard strong-solution results. The accepted explanation uses Girsanov’s theorem: a drift with bounded linear growth is sufficient for existence of a weak solution in this setting.
It also suggests approximating the discontinuous sign function with smooth functions and studying the resulting equations. The original proposed construction attempts to build a Brownian motion directly, but the response redirects to a general existence result. This is a mathematical discussion rather than a trading method, and it provides no numerical simulation or market application. The stated growth condition addresses existence of a weak solution; it does not establish uniqueness or guarantee that a strong solution exists.
Key ideas
- A bounded sign drift can fail the Lipschitz condition used in common strong-solution results.
- The response invokes Girsanov’s theorem to establish weak-solution existence under a linear-growth bound.
- The sign function satisfies the growth condition cited in the explanation.
- Smooth approximations can be used to investigate equations with discontinuous drift.
- Existence of a weak solution does not by itself establish uniqueness or strong solvability.
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Full text
# Weak solution of a SDE
# Weak solution of a SDE
$\text { Consider the } \operatorname{SDE} d X_{t}=\operatorname{sign}\left(X_{t}\right) d t+d B_{t} \text { on } 0 \leq t \leq T, \text { where } \operatorname{sign}(x)=1\\ \text { for } x>0 \text { and } \operatorname{sign}(x)=-1 \text { for } x \leq 0 \text { . Show that it has a weak solution. }$
I am not sure if this is the way I am suppose to answer the question but this is how I did it:
$d x_{t}-\operatorname{sign}\left(x_{t}\right) d t=d B_{t}$
$\text { let } Y_{t}=\int_{0}^{t}-\operatorname{sign}\left(X_{s}\right) d s+\int_{0}^{t} d X_{s}$
We can see here that $\int_{0}^{t}\left|\operatorname{sign}\left(x_{s}\right)\right| d s<\infty$ as sign$(X_s)$ is bounded between -1 and 1.
We can also see that $\int_{0}^{t}\left(d x_{s}\right)^{2}=T<\infty$
Hence $Y_t$ is well defined and is a martingale as $[y, y]_{t}=\int_{0}^{t} \operatorname{sign}^{2}\left(X_{s}\right) d s=T \text { and }$ $\int_{0}^{t} d X_{S}=\int_{0}^{t} d t=T$
Therefore $[Y, Y]_{t}$ is a constant value which is a martingale. And $Y_t$ is Brownian Motion that satisfies the SDE $dX_t$
## Answer by ir7 (score 1)
https://quant.stackexchange.com/a/64042
Based on Karatzas and Shreve's book, section 5.3.B, Weak Solutions By Means of Girsanov, Proposition 3.6., "the principal method for creating weak solutions is the transformation of drift via the Girsanov theorem". Their proof of the proposition illustrates the approach.
The only condition that needs to be met is for the drift to have bounded growth: if
$$ |b(t,x)| \leq K(1+|x|) $$
for all $t$ and $x$, for some positive constant $K$, then SDE
$$ dX_t = b(t,X_t) dt + dB_t $$
has a weak solution.
Function $\operatorname{sign}$ does meet the condition:
$$ |\operatorname{sign}(x)| < 1 + |x| $$
for all $x$.
Notes:
- Contrast with the 'usual' conditions for strong solutions: both drift and diffusion coefficients are to satisfy global linear growth and Lipschitz conditions. Note that $\operatorname{sign}$ fails Lipschitz badly.
- The other thing worth mentioning is that, for practical investigations, one can approximate $\operatorname{sign}$ by a sequence of smooth functions that converges pointwise to it (see this article for such research):
$$ f_n(x) = -1_{x<-1/n} + (-n^3x^3/2 + 3nx/2)1_{-1/n\leq x \leq 1/n} + 1_{x>1/n} $$ and study SDE $$ dX_t = f_n(X_t) dt + dB_t. $$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.