Comparative Analysis of Stock Portfolio Optimization in Fireworks and Genetic Algorithms Using Conditional Value at Risk
Devaluation of assets in the future is one of the most important investment concerns that has led investors to choose the set of assets that have the lowest risk and highest return. The present study deals with the problem of stock portfolio optimization according to the Conditional Value at Risk based on the new and intelligent fireworks algorithm and compares it with genetic algorithm with the historical simulation method using MATLAB software. The parameters of meta-heuristic algorithms were adjusted by Taguchi method using MINITAB software. Not suspended, used. For reliability of the study, generalized Dickey-Fuller test and Phillips-Prone test were used. To evaluate the accuracy of the Conditional Value at Risk model, the kupiec proportion of failure test, Christoffersen independence test and Conditional coverage test are used. A comparison was also made between the models by Lopez test. Findings showed that at %95 and %99 confidence levels, the conditional risk value model using the fireworks algorithm has a suitable and reliable validity for measuring market risk and optimizing the stock portfolio.
-
The Impact of Globalization, Demographic, and Economic Development Variables on Entrepreneurship Using the Pooled Mean Group (PMG) Approach (Case Study: Selected Developing Asian Countries)
Karrar Burhan Abed, Saeed Daei-Karimzadeh*, Amjed Jafar Habib Bahrul Uloom, Hossein Sharifi Renani
Business, Marketing, and Finance Open, Jan-Feb 2024 -
The Nonlinear Effects of Macroeconomic Variables on the Flow of Foreign Direct Investment in Selected Middle Eastern Countries
Mohammedmajeed Rasooli Al-Mamar, Saeed Daei-Karimzadeh *, Mayih Shabeeb Hadhood AL-Shammari, Mostafa Rajabi
Journal of Accounting, Finance and Computational Intelligence,