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Stochastic calculus provides a consistent theory of integration for stochastic processes and is used to model random systems. Its applications range from statistical physics to quantitative finance.

3 votes
Accepted

Girsanov theorem and the density of a process

Short answer: it follows directly from the Radon-Nikodym theorem. Longer answer: Let $\mu$ denote the law of $Y(t)$ under $\mathbb P_{y_0}$ and let $\nu$ denote the law of $Y(t)$ under $\mathbb Q_{y_ …
Joris Bierkens's user avatar
3 votes
1 answer
340 views

Example of Girsanov change of density with finite relative entropy, but with infinite integr...

Let $(\Omega, (\mathcal F_t), \mathbb P)$ denote the usual Wiener space where $\Omega = C[0,\infty)$, etc., and where $(W_t)_{t \geq 0}$ denotes the Wiener process. Let $Z \in L^1(\mathbb P)$ with $Z …
Joris Bierkens's user avatar
2 votes
Accepted

Example of Girsanov change of density with finite relative entropy, but with infinite integr...

I can now answer my own question. There exists no such counterexample. I can show that finite relative entropy in this setting implies $\mathbb E^{\mathbb Q} \int_0^{\infty} \theta_t^2 \ d t < \infty$ …
Joris Bierkens's user avatar
0 votes

On the existence and uniqueness of solution to SPDE with nonlinear growth coefficients

flawed, see Martin Hairer's comment below. Step I) Perform substitution $u_t(x) = \exp(\psi_t(x))$. The SPDE for $\psi$ becomes, after dividing by $u_t(x)$, \begin{equation} \frac{\partial}{\partial …
Joris Bierkens's user avatar
4 votes

A Stochastic Taylor Expansion/Asymptotics

Write $f(t) := \mathbb E \left[ \exp\left( - \int_0^t r_s \ d s \right) \right]$. Define stochastic processes $y_t = \exp \left( -\int_0^t r_s \ d s \right)$ and $z_t = r_t y_t$. Then $y_t = 1 - \int_ …
Joris Bierkens's user avatar