Doob’s optional sampling theorem
Given a filtered probability space , a process is a martingale if it satisfies the equality
for all in the index set . Doob’s optional sampling theorem says that this equality still holds if the times are replaced by bounded stopping times . In this case, the -algebra is replaced by the collection of events observable at the random time (http://planetmath.org/SigmaAlgebraAtAStoppingTime),
In discrete-time, when the index set is countable, the result is as follows.
Doob’s Optional Sampling Theorem.
Suppose that the index set is countable and that are stopping times bounded above by some constant . If is a martingale then is an integrable random variable and
(1) |
Similarly, if is a submartingale then is integrable and
(2) |
If is a supermartingale then is integrable and
(3) |
This theorem shows, amongst other things, that in the case of a fair casino, where your return is a martingale, betting strategies involving ‘knowing when to quit’ do not enhance your expected return.
In continuous-time, when the index set an interval of the real numbers, then the stopping times can have a continuous distribution and need not be measurable quantities. Then, it is necessary to place conditions on the sample paths of the process . In particular, Doob’s optional sampling theorem holds in continuous-time if is assumed to be right-continuous.
Title | Doob’s optional sampling theorem |
---|---|
Canonical name | DoobsOptionalSamplingTheorem |
Date of creation | 2013-03-22 16:43:41 |
Last modified on | 2013-03-22 16:43:41 |
Owner | skubeedooo (5401) |
Last modified by | skubeedooo (5401) |
Numerical id | 8 |
Author | skubeedooo (5401) |
Entry type | Theorem |
Classification | msc 60G44 |
Classification | msc 60G46 |
Classification | msc 60G42 |
Related topic | Martingale |
Related topic | StoppingTime |
Related topic | SigmaAlgebraAtAStoppingTime |