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Non-linear Autoregressive with Exogeneous input (narx) bitcoin price prediction model using PSO-optimized parameters and moving average technical indicators
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References

  • 2014Stock Price Prediction Using the ARIMA Model1,153 cited
  • 2015A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price175 cited
  • 2012Stock Market Prediction Using Artificial Neural Networks150 cited
  • 2012Stock Price Prediction using Neural Network with Hybridized Market Indicators122 cited

Cited by

  • 2018Forecasting Price of Cryptocurrencies Using Tweets Sentiment Analysis78 cited
  • 2019An Optimized Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO) for Cryptocurrency Forecasting76 cited
  • 2019Cryptocurrency Price Analysis with Artificial Intelligence74 cited
  • 2020Predicting changes in Bitcoin price using grey system theory63 cited
  • 2020Sentiment-Driven Price Prediction of the Bitcoin based on Statistical and Deep Learning Approaches63 cited
  • 2023Forecasting cryptocurrency returns with machine learning59 cited
  • 2020ETH analysis and predictions utilizing deep learning50 cited
  • 2019An Agent-Based Artificial Market Model for Studying the Bitcoin Trading44 cited
  • 2018Crypto-Currency Investing Examined40 cited
  • 2022Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach40 cited

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  • 2021Predictions of bitcoin prices through machine learning based frameworks39 cited
  • 2024An ensemble learning method for Bitcoin price prediction based on volatility indicators and trend37 cited
  • 2020Bitcoin Price Prediction Based on Deep Learning Methods37 cited
  • 2019Systematic Erudition of Bitcoin Price Prediction using Machine Learning Techniques36 cited
  • 2019Prediction of Cryptocurrency Price Dynamics with Multiple Machine Learning Techniques34 cited
  • 2019Forecasting of BTC volatility: comparative study between parametric and nonparametric models26 cited