Open AccessBeetle swarm optimisation for solving investment portfolio problems
Author(s) -
Chen Tingting,
Zhu Yongjian,
Teng Jun
Publication year - 2018
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8287
Subject(s) - particle swarm optimization , portfolio , mathematical optimization , investment portfolio , investment (military) , swarm intelligence , swarm behaviour , computer science , value (mathematics) , economics , mathematics , machine learning , financial economics , politics , political science , law
A portfolio model is established after analysing the investment environment of the artificial intelligence concept stocks in China. To reduce the risk of investment, the beetle swarm optimisation (BSO) is proposed. BSO, based on the beetle antennae search (BAS) and the standard particle swarm optimisation (PSO), is derived from the standard PSO but the update rules of each particle originate from BAS. In global searching, BSO, making the model get a lower value at risk, is more capable than standard PSO, which is easily trapped in local optimal defects. This study tries to solve portfolio model by using BSO algorithm. The results prove that BSO can do better in dealing with optimisation problems of constrained multi‐dimensional functions.