Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market

The purpose of this paper is to demonstrate that a portfolio optimization model using the L 1 risk (mean absolute deviation risk) function can remove most of the difficulties associated with the classical Markowitz's model while maintaining its advantages over equilibrium models. In particular,...

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Bibliographic Details
Published in:Management science 1991-05, Vol.37 (5), p.519-531
Main Authors: Konno, Hiroshi, Yamazaki, Hiroaki
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Financial portfolios
Investment return rates
Investment risk
Investors
Japan
L1 risk function
Linear programming
Markowitz's model
Mathematical models
Operational research and scientific management
Operational research. Management science
Optimization
Portfolio analysis
Portfolio management
portfolio optimization
Portfolio performance
Quadratic programming
Risk
single-factor model
Standard deviation
Statistical analysis
Stock exchange
Stock market indices
Stock markets
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Summary:The purpose of this paper is to demonstrate that a portfolio optimization model using the L 1 risk (mean absolute deviation risk) function can remove most of the difficulties associated with the classical Markowitz's model while maintaining its advantages over equilibrium models. In particular, the L 1 risk model leads to a linear program instead of a quadratic program, so that a large-scale optimization problem consisting of more than 1,000 stocks may be solved on a real time basis. Numerical experiments using the historical data of NIKKEI 225 stocks show that the L 1 risk model generates a portfolio quite similar to that of the Markowitz's model within a fraction of time required to solve the latter.
ISSN:0025-1909
1526-5501
DOI:10.1287/mnsc.37.5.519