survey

A Survey on Gaps between Mean-Variance Approach and Exponential Growth Rate Approach for Portfolio Optimization

Authors:
Zhao-Rong Lai

Jinan University, Guangzhou, Guangdong, China

Jinan University, Guangzhou, Guangdong, China

0000-0002-7631-8512
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,
Haisheng Yang

Sun Yat-Sen University, Guangzhou, Guangdong, China

Sun Yat-Sen University, Guangzhou, Guangdong, China
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ACM Computing Surveys Volume 55 Issue 2Article No.: 25pp 1–36https://doi.org/10.1145/3485274

Published:19 January 2022Publication History

ACM Computing Surveys

Abstract

Portfolio optimization can be roughly categorized as the mean-variance approach and the exponential growth rate approach based on different theoretical foundations, trading logics, optimization objectives, and methodologies. The former and the latter are often used in long-term and short-term portfolio optimizations, respectively. Although the mean-variance approach could be applied to short-term portfolio optimization, the performance may not be satisfactory (same with the exponential growth rate approach to the long-term portfolio optimization). This survey mainly explores the gaps between these two approaches, and investigates what common ideas or mechanisms are beneficial. Besides, the evaluating framework of this field and some unsolved problems are also discussed.

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Index Terms

A Survey on Gaps between Mean-Variance Approach and Exponential Growth Rate Approach for Portfolio Optimization
1. Computing methodologies
  1. Artificial intelligence
  2. Machine learning
2. Information systems
  1. Information systems applications
    1. Data mining

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ACM Computing Surveys Volume 55, Issue 2
February 2023
803 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/3505209
Editor:
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Publication History
- Published: 19 January 2022
- Accepted: 1 September 2021
- Revised: 1 May 2021
- Received: 1 November 2020
Published in csur Volume 55, Issue 2

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Portfolio optimization
rebalancing frequency
mean-variance
exponential growth rate
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A Survey on Gaps between Mean-Variance Approach and Exponential Growth Rate Approach for Portfolio Optimization

ACM Computing Surveys

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