Forecasting the Early Market Movement in Bitcoin Using Twitters Sentiment Analysis An Ensemble based Prediction Model

Analyzing BTC’s Trend During COVID-19 Using A Sentiment Consensus Clustering (SCC)
Ibrahim, A. 2021. Analyzing BTC’s Trend During COVID-19 Using A Sentiment Consensus Clustering (SCC). 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). Vancouver, Canada 27 - 30 Oct 2021 IEEE . https://doi.org/10.1109/IEMCON53756.2021.9623182

Predicting market movement direction for bitcoin: A comparison of time series modeling methods
Ibrahim, A., Kashef, R. and Corrigan, L. 2021. Predicting market movement direction for bitcoin: A comparison of time series modeling methods. Computers and Electrical Engineering. 89 106905. https://doi.org/10.1016/j.compeleceng.2020.106905

Predicting the Demand in Bitcoin Using Data Charts: A Convolutional Neural Networks Prediction Model
Ibrahim, A., Corrigan, L. and Kashef, R. 2020. Predicting the Demand in Bitcoin Using Data Charts: A Convolutional Neural Networks Prediction Model. IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). London, Ontario, Canada 30 Aug - 02 Sep 2020 IEEE . https://doi.org/10.1109/CCECE47787.2020.9255711

Bitcoin Network Mechanics: Forecasting the BTC Closing Price Using Vector Auto-Regression Models Based on Endogenous and Exogenous Feature Variables
Ibrahim, A., Kashef, R., Li, M., Valencia, E. and Huang, E. 2020. Bitcoin Network Mechanics: Forecasting the BTC Closing Price Using Vector Auto-Regression Models Based on Endogenous and Exogenous Feature Variables. Journal of Risk and Financial Management. 13 (9) 9. https://doi.org/10.3390/jrfm13090189