Online portfolio selection: A survey

Author

Bin LI, Nanyang Technological University
Steven C. H. HOI, Singapore Management UniversityFollow

Publication Type

Journal Article

Version

publishedVersion

Publication Date

1-2014

Abstract

Online portfolio selection is a fundamental problem in computational finance, which has been extensively studied across several research communities, including finance, statistics, artificial intelligence, machine learning, and data mining. This article aims to provide a comprehensive survey and a structural understanding of online portfolio selection techniques published in the literature. From an online machine learning perspective, we first formulate online portfolio selection as a sequential decision problem, and then we survey a variety of state-of-the-art approaches, which are grouped into several major categories, including benchmarks, Follow-the-Winner approaches, Follow-the-Loser approaches, Pattern-Matching--based approaches, and Meta-Learning Algorithms. In addition to the problem formulation and related algorithms, we also discuss the relationship of these algorithms with the capital growth theory so as to better understand the similarities and differences of their underlying trading ideas. This article aims to provide a timely and comprehensive survey for both machine learning and data mining researchers in academia and quantitative portfolio managers in the financial industry to help them understand the state of the art and facilitate their research and practical applications. We also discuss some open issues and evaluate some emerging new trends for future research.

Keywords

Machine learning, optimization, portfolio selection

Discipline

Databases and Information Systems | Finance and Financial Management | Numerical Analysis and Scientific Computing | Portfolio and Security Analysis

Research Areas

Data Science and Engineering

Publication

ACM Computing Surveys

Volume

46

Issue

3

First Page

1

Last Page

33

ISSN

0360-0300

Identifier

10.1145/2512962

Publisher

ACM

Citation

LI, Bin and HOI, Steven C. H.. Online portfolio selection: A survey. (2014). ACM Computing Surveys. 46, (3), 1-33.
Available at: https://ink.library.smu.edu.sg/sis_research/2263

Copyright Owner and License

Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

https://doi.org/10.1145/2512962