Optimization of Network-Based Matrix Investment Portfolio and Comparison with Fuzzy Neural Combination Pattern and Genetic Algorithm(ANFIS)

Document Type : Original Article

Authors
ALI SheidaeiNarmigi 1
Fraydoon Rahnamay Roodposhti 2
Reza Radfar 3
1 Ali Sheidaei Narmigi Student of Industrial-Financial Management, Department of Industrial Management, Science and Research Branch, Islamic Azad University
2 Department of Financial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Abstract
Researchers have been researching portfolio optimization issues for several years. One of the main issues is to determine the optimization method, which is to form an optimal investment portfolio, ie to minimize investment risk and maximize investment profit. The aim of this study is to investigate the strategic capability of network matrix and fuzzy genetic neural model (ANFIS) in optimizing the investment portfolio among companies on the Tehran Stock Exchange. Grouping stocks by network matrix based on new variables including aggressive, indifferent and defensive stocks provided by Roodpashti (2009) and traditional variables including growth, growth-value and value stocks and classification of companies based on their market value and use. From the law of quarters and finally their weighting is considered in proportion to the return of that share. The design and presentation of a stock portfolio optimization model using adaptive fuzzy neural inference system and its combination with genetic algorithm (ANFIS) in which two different categories of technical and fundamental variables are used as model inputs. Research outputs show that these systems have the necessary ability to optimize the stock portfolio. Therefore, a combined model of neural networks and fuzzy reasoning theory with genetic algorithm has been used to weight the factors affecting stock portfolio optimization in the 7 years leading up to 1398.
Keywords
Stock portfolio optimization
artificial neural networks
fuzzy logic
genetic algorithm
adaptive fuzzy neural inference system
  • بشیر خداپرستی ، رامین (1397) ، کارایی مدل پنج عامل فاما و فرنچ در سهام تهاجمی و تدافعی ، راهبرد مدیریت مالی ، زمستان 97.
  • رهنمای رودپشتی و همکاران (1390)، گروه بندی پورتفوی سرمایه گذاری براساس ماتریس شبکه و مقایسه عملکرد پورتفوی های حاصل از این روش با استفاده از نسبت پتانسیل مطلوب ، تحقیقات مالی دانشگاه تهران ، شماره 32 ، 1390.
  • رهنمای رودپشتی و همکاران (1391) ، مقایسه عملکرد پورتفوی های حاصل از گروه بندی سهام بوسیله مدل شبکه مبتنی بر متغیرهای نوین و سنتی با استفاده از شاخص های شارپ و ترینر ، فصلنامه علمی و پژوهشی دانش سرمایه گذاری ، پاییز 1392.
  • سروش ، البرز و همکاران (1395) ، بهینه سازی سبد سهام با استفاده از الگوریتم بهینه سازی مبتنی بر آموزش و یادگیری در بورس ، تحقیقات مالی دانشکده مدیریت دانشگاه تهران ، تابستان 1396.
  • فشاری ، مجید و مظاهری فر ، پویا (1395) ، مقایسه الگوریتم های پیش بینی و بهینه سازی پورتفوی در بورس اوراق بهادار تهران ، فصلنامه سیسات گذاری و پیشرفت اقتصادی دانشگاه الزهرا ، شماره 11 ، تابستان 1395.
  • مهرگان ، محمدرضا و همکاران (1396) ، طراحی سیستم استنباط عصبی فازی تطبیقی به منظور بهینه سازی مصرف گاز طبیعی ایران ، رساله دکتری ، دانشگاه تهران.
  • Chen Z, Li G, Guo J . Optimal investment policy in the time consistent mean-variance formulation.Insur. Math. Econ. 52:145-156, 2013.
  • Chen, Z, and Liu, J . Multi-period robust measures and portfolio selection models with regime-switching. Optimization Online Links-Optimization related societies, 2015 .
  • DeMiguel, V. and Nogales, F. J. (2009) Portfolio selection with robust estimation. Operations Research 57(3):560-577
  • Fabozzi, F. J. , Huang, D., and Zhou, G. (2010) Robust portfolios: contributions from operations research and _nance. Annals of Operations Research 176(1):191-220.
  • Goldfarb, D. and Iyengar, G. (2003) Robust portfolio selection problems. Mathematics of Operations Research 28(1):1-38.
  • Liu J, Chen Z . Regime-dependent robust risk measures with application in portfolio selection. Procedia Computer Science 31:344-350 , 2014.
  • Markowitz, H. (1952) Portfolio selection. Journal of Finance 7(1):77-91