Application of meta-heuristic algorithms in portfolio optimization with capital market bubble conditions

Subject Areas : Financial and Economic Modelling

Iman  Mohammadi ¹ (Department of Management, Najafabad Branch, Islamic Azad University, Najaf Abad, Iran)
Hamzeh  Mohammadi Khoshouei ² (Department of Accounting, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.)
Arezo  Aghaee chadegani ³ (Department of Accounting, Najafabad Branch, Islamic Azad university, Najafabad, Iran)

Received: 2022-09-06 Accepted : 2023-06-07 Published : 2024-02-26

Keywords: Portfolio optimization, Meta-heuristic Algorithm, Returns, Risk, Price Bubble,

Abstract :

The existence of bubbles in the market, especially the capital market, can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country. On the other hand, due to the goal of investors in achieving a portfolio of high returns with the least amount of risk, the need to pay attention to these markets increases. In this research, with the aim of maximizing return and minimizing investment risk, an attempt has been made to form an optimal portfolio in conditions where the capital market has a price bubble. According to the purpose, the research is of applied type, and in terms of data, quantitative and post-event, and in terms of type of analysis, it is of descriptive-correlation type. In order to identify the months with bubbles in the period from 2015 to 2021 in the Tehran Stock Exchange market, sequence tests and skewness and kurtosis tests were used. After identifying periods with bubbles, the meta-heuristic algorithms were used to optimize the portfolio. The results indicate the identification of 14 periods with price bubbles in the period under study. Also, in portfolio optimization, selected stock portfolios with maximum returns and minimum risk are formed. This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions.

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