NDLI: Log-optimal portfolio models with risk control of VaR and CVaR using genetic algorithms

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Log-optimal portfolio models with risk control of VaR and CVaR using genetic algorithms

Content Provider	ACM Digital Library
Author	Qin, Sen
Abstract	Value-at-risk (VaR) and conditional value-at-risk (CVaR) have become two very popular measures of market risk during the last decade. Log-optimal portfolio problem with risk control of VaR and CVaR is put forward firstly. Then, we propose the portfolio models with VaR and CVaR and prove the existence and uniqueness of the optimal solutions of these two models. We provide a newly genetic algorithm based on real-code strings of assets' returns to overcome the problem of local optima. Finally, an empirical study is carried out to illustrate the optimal solutions of the log-optimal portfolio models with VaR and CVaR. The numeric results indicate that the optimal portfolio of the log-optimal portfolio model with CVaR gives a balance between the investment risk and the return simultaneously, and is more effective than the corresponding portfolios of the VaR model and the mean-variance model.
Starting Page	941
Ending Page	944
Page Count	4
File Format	PDF
ISBN	9781605583266
DOI	10.1145/1543834.1543979
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-06-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Conditional value-at-risk Genetic algorithm Risk control Log-optimal portfolio model Value-at-risk
Content Type	Text
Resource Type	Article

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