Work

On-line portfolio selection

Year: 1996

Type: conference-paper

Abstract: We find an on-line portfolio selection strategy which minimizes the worst case regret with respect to the growth rate of wealth achieved by the best off-line optimized constant rebalanced portfolio.The resulting regret is compared to that of the infinite horizon Dirichlet-weighted universal portfolio.Both strategies track the performance of the best off-line constant rebalanced portfolio to first order in the exponent.1

Source: Conference on Learning Theory

DOI: 10.1145/238061.238161

Authors: Erik Ordentlich, Thomas M. Cover

Institution: Stanford University

Language: English

Topic: Advanced Bandit Algorithms Research

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: bronze

OpenAlex ID: W2052215974

FWCI: 6.955

Cites: 3

Cited by: 41

Related to: 10