Abstract
Abstract 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.
Highlights
There are many non-probability factors affecting financial markets and the return on risk assets is fuzzy and uncertain
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
Summary
Abstract: There are many non-probability factors affecting financial markets and the return on risk assets is fuzzy and uncertain. 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. Considering the entropy and skewness constraints of transaction cost and transaction volume, a multipleperiod mean value – mean absolute deviation investment portfolio model was proposed This model focused on dynamic optimization with path dependence. A discrete approximate iteration method is proposed to solve this model and the algorithm is provento be convergent
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