Research On The Efficiency Evaluation Of Fuzzy Portfolios

How to effectively evaluate portfolio efficiency is a hot issue in the field of financial engineering.An effective portfolio evaluation can not only provide a basis for rational investor decision-making,but also play an important role in promoting the development of financial markets healthily and orderly.Traditional portfolio efficiency evaluation studies are based on probabilistic theory.They only consider the random uncertainty of the financial market.Moreover,the risk measure of fuzzy portfolio is relatively simple.A large number of studies have shown that there are highly fuzzy and uncertain phenomena in the financial markets.Ignoring the fuzzy and uncertain financial markets may lead to ineffective portfolio strategies.In this paper,we discuss the fuzzy portfolio efficiency evaluation problem indifferent risk measures.We first present three kinds of DEA(Data envelopment analysis)based fuzzy portfolio estimation models in different risk measures,i.e.,possibilistic variance,possibilistic semi-variance,and possibilistic semi-absolute deviation,to evaluate the portfolio efficiency(PE).Furthermore,we carry out large amount of simulations with different sample sizes to demonstrate our proposed models.In real life,investors need to constantly adjust their investment strategies based on market feedback in order to effectively spread risks and achieve stable asset growth.Therefore,this work further explores multi-period fuzzy portfolio efficiency evaluation.And we divided this issue into 4 categories,according to whether the wealth held by investors in each investment cycle is accumulated,and whether the efficiency of each investment phase affects the final efficiency.Then data envelopment analysis methods are used to construct four different multi-period fuzzy portfolio efficiency evaluation models respectively.Finally,the validity of the model is verified by the large-scale data simulation,and the impact of the efficiency of each investment stage on the final efficiency is compared and analyzed.