Volume 9, Issue 1 (5-2023)                   mmr 2023, 9(1): 484-311 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Usefzadeh H R, Karrabi A, Heidari A. FRACSION: A Novel Hybrid Algorithm for Forecasting the Industry Index Trend in Tehran Stock Exchange. mmr 2023; 9 (1) :484-311
URL: http://mmr.khu.ac.ir/article-1-3146-en.html
1- payam noor university , usefzadeh.math@pnu.ac.ir
2- payam noor university
Abstract:   (719 Views)
Due to the dynamic structure and nonlinear fluctuations of the stock market, it is difficult to accurately predict the trend of this market using the old methods. In this study, in order to improve the accuracy of predicting the index trend in different industries, we propose a new algorithm that combines algorithms fractal interpolation and support vector machine regression, abbreviated as fracsion algorithm. . For this purpose, after recognizing the fractal structure of industries using the Hurst exponent of each industry, we consider the value of the index in each fractal industry as the primary data to predict the trend of the index. Then, by modifying the fractal interpolation algorithm, we will generate new data, and finally, by calling the support vector regression algorithm on the obtained data, we will predict the index trend. The results of the implementation of the Hybrid fracsion algorithm and its comparison with two conventional methods, namely artificial neural network and support vector machine regression, indicate the superiority of the predictive accuracy of the proposed algorithm.
Full-Text [PDF 5306 kb]   (182 Downloads)    
Type of Study: Research Paper | Subject: Mat
Received: 2020/10/27 | Revised: 2024/01/7 | Accepted: 2021/05/9 | Published: 2023/06/20 | ePublished: 2023/06/20

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Mathematical Researches

Designed & Developed by : Yektaweb