Bitcoin price forecasting using hybrid genetic algorithm
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Bitcoin and digital currencies have emerged as a new market for investment. Therefore, the prediction of their future trend and prices is highly significant. In this research, the factors influencing the price of bitcoin were identified and extracted based on previous researches. The identified factors include the US dollar index, CPI index, S and P 500, Dow Jones, and gold price. Considering the performance of metaheuristic algorithms in predicting bitcoin price, this research utilized genetic algorithm and particle swarm optimization algorithm, and proposed a hybrid algorithm to improve their performance.According to our results, among the investigated factors, the US dollar index has the greatest impact on bitcoin price, followed by inflation rate and the CPI index. Additionally, the proposed hybrid algorithm outperforms the particle swarm optimization and genetic algorithms, with a prediction error of 7.3%. It should be noted that the type and magnitude of the impact of the investigated factors may change over time. For example, a factor that previously had a direct impact may become reversed or neutralized over time.
Keywords:
Language:
English
Published:
Mathematics and Computational Sciences, Volume:5 Issue: 2, Spring 2024
Pages:
34 to 48
https://www.magiran.com/p2739959
سامانه نویسندگان
مقالات دیگری از این نویسنده (گان)
-
Investigating financial information asymmetry in pharmaceutical companies listed on Tehran Stock Exchange and prediction their financial crisis using Artificial Neural Network
Fatemeh Heirani, Najmeh Neshat *,
Journal of Modern Research in Decision Making, -
Identification and Evaluation of Profitable Technical Trading Rules in the Cryptocurrency Market: A Mixed Method Approach
Milad Abbasi, Somayeh Al-Sadat Mousavi *, Abbasali Jafari Nodoushan
Financial Research,