Quantitative Analysis.
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I.Basic math.
1.Conditional probability.
2.Normal distribution.
3.Brownian motion.
4.Poisson process.
5.Ito integral.
6.Ito calculus.
7.Change of measure.
8.Girsanov's theorem.
9.Forward Kolmogorov's equation.
10.Backward Kolmogorov's equation.
11.Optimal control, Bellman equation, Dynamic programming.
A.Deterministic optimal control problem.
B.Stochastic optimal control problem.
C.Optimal stopping time problem. Free boundary problem.
II.Pricing and Hedging.
III.Explicit techniques.
IV.Data Analysis.
V.Implementation tools.
VI.Basic Math II.
VII.Implementation tools II.
Bibliography.
Forum Notation Index Contents

Optimal stopping time problem. Free boundary problem.


e are investigating a model with a state variable MATH given by the SDEMATH where the $W_{t}$ is a standard brownian motion in $\QTR{cal}{R}^{n}$, MATH, MATH.

Let $U$ be an open subset of $\QTR{cal}{R}^{n}$, $X_{0}=x\in U$ and $\tau$ be the time of first exit of $X_{t}$ from $U$:MATH

Let $\QTR{cal}{F}_{t}$ be the filtration generated by $X_{t}$ and $\theta$ denote a stopping time with respect to $\QTR{cal}{F}_{t}$.

We introduce the following cost functionMATH and the functionMATH We proceed to calculate the PDE for MATH. There are two cases. In the event of the stopping at MATH we haveMATH We introduce the convenience notationMATH If the stopping time does not occur at $\left( t,x\right) $ thenMATH where MATH ThereforeMATH

Note that only one of equalities $u=\psi$ or $0=f+u_{t}+Lu$ is true at all times. If the stopping does occur then MATH thus math. If the stopping does not occur then math.

Summary

The functionMATH satisfies on MATH the conditionsMATH where only one of the inequalities is strict at all times, thusMATH The boundary and final conditions areMATH

Given MATH the optimal stopping strategy is defined byMATH

LetMATH then

MATH(Free boundary problem 1)





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