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Concept
Optimal stopping
Summary
In mathematics, the theory of optimal stopping or early stopping is concerned with the problem of choosing a time to take a particular action, in order to maximise an expected reward or minimise an expected cost. Optimal stopping problems can be found in areas of statistics, economics, and mathematical finance (related to the pricing of American options). A key example of an optimal stopping problem is the secretary problem. Optimal stopping problems can often be written in the form of a Bellman equation, and are therefore often solved using dynamic programming.
Stopping rule problems are associated with two objects:
A sequence of random variables , whose joint distribution is something assumed to be known
A sequence of 'reward' functions which depend on the observed values of the random variables in 1:
Given those objects, the problem is as follows:
You are observing the sequence of random variables, and at each step , you can choose to either stop observing or continue
If you stop observing at step , you will receive reward
You want to choose a stopping rule to maximize your expected reward (or equivalently, minimize your expected loss)
Consider a gain process defined on a filtered probability space and assume that is adapted to the filtration. The optimal stopping problem is to find the stopping time which maximizes the expected gain
where is called the value function. Here can take value .
A more specific formulation is as follows. We consider an adapted strong Markov process defined on a filtered probability space where denotes the probability measure where the stochastic process starts at . Given continuous functions , and , the optimal stopping problem is
This is sometimes called the MLS (which stand for Mayer, Lagrange, and supremum, respectively) formulation.
There are generally two approaches to solving optimal stopping problems. When the underlying process (or the gain process) is described by its unconditional finite-dimensional distributions, the appropriate solution technique is the martingale approach, so called because it uses martingale theory, the most important concept being the Snell envelope.
Official source
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