Optimal Online Selection of an Alternating Subsequence: A Central Limit Theorem

Loading...
Thumbnail Image
Penn collection
Finance Papers
Degree type
Discipline
Subject
Finance and Financial Management
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Arlotto, Alessandro
Steele, J. Michael
Contributor
Abstract

We analyze the optimal policy for the sequential selection of an alternating subsequence from a sequence of n independent observations from a continuous distribution F, and we prove a central limit theorem for the number of selections made by that policy. The proof exploits the backward recursion of dynamic programming and assembles a detailed understanding of the associated value functions and selection rules.

Advisor
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Publication date
2014-01-01
Journal title
Advances in Applied Probability
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation
Collection