Financial Markets, Investment Portfolios and Fuzzy Models
On March 3, 2019, Manwen Tian, Shurong Yan and Xiaoxiao Tian have published an article entitled “Discrete approximate iterative method for fuzzy investment portfolio based on transaction cost threshold constraint” in Open Physics.
A Blog Post by Pablo Markin.
In their paper, Manwen Tian, Shurong Yan and Xiaoxiao Tian have focused on “non-probability factors affecting financial markets and the return on risk assets” (41), while proposing a “multiple-period mean value-mean absolute deviation investment portfolio optimization model” (41). Using “dynamic optimization […] [and] discrete approximate iteration method[s]” (41), these researchers have used empirical data from “30 weighted stocks selected from Shanghai Stock Exchange and Shenzhen Stock Exchange” (41).
According to Tian, Yan and Tian, “[m]any non-probability factors affect a financial market, and asset earnings are fuzzy and uncertain” (42). To account for these factors, these authors have incorporated into their model measures of “the entropy and skewness constraints of transaction cost and transaction volume” (42). This paper is, thus, based on theoretical developments from “the 1950s, [during which] Markowitz used a variance measure of investment risk and proposed the mean-variance single-period investment portfolio theory, which [has] laid the basis of the modern finance” (45).
However, as this paper highlights, financial markets can be expected to be affected “by many non-probability factors and the risk assets’ income is fuzzy and uncertain” (45). This article has found that “the multi-period investments dynamic optimization model has linear convergence and is more effective” (45) than its counterparts.
By Pablo Markin
Featured Image Credits: Shanghai, Pudong New Area, May 17, 2012 | © Courtesy of Allan Watt/Flickr.