Journal
OPEN PHYSICS
Volume 17, Issue 1, Pages 41-47Publisher
DE GRUYTER POLAND SP ZOO
DOI: 10.1515/phys-2019-0005
Keywords
Markowitz; mean-variance; fuzzy investment portfolio; optimization
Categories
Funding
- Key project of the National Social Science Fund of the year 2018 [18AJY013]
- National Social Science foundation project [17CJY072]
- The 2018 planning project of philosophy and social science of Zhejiang province [18NDJC086YB]
- 2018 Fujian Social Science Planning Project [FJ2018B067]
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There are many non-probability factors affecting financial markets and the return on risk assets is fuzzy and uncertain. The authors propose new risk measurement methods to describe or measure the real investment risks. Currently many scholars are studying fuzzy asset portfolios. Based on previous research and in view of the threshold value constraint and entropy constraint of transaction costs and transaction volume, the multiple-period mean value -mean absolute deviation investment portfolio optimization model was proposed on a trial basis. This model focuses on a dynamic optimization problem with path dependence; solving using the discrete approximate iteration method certifies the algorithm is convergent. Upon the empirical research on 30 weighted stocks selected from Shanghai Stock Exchange and Shenzhen Stock Exchange, a multi-period investment portfolio optimum strategy was designed. Through the empirical research, it can be found that the multi-period investments dynamic optimization model has linear convergence and is more effective. This is of great value for investors to develop a multi-stage fuzzy portfolio investment strategy.
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