Bitcoin and Cryptocurrency Exchange Market Prediction and Analysis Using Big Data and Machine Learning Algorithms

Adnan Branković; Jukić Samed

doi:10.54060/jieee.2023.64

Authors

Adnan Branković International Burch University, Bosnia and Herzegovina https://orcid.org/0009-0004-4601-4069
Dr. Jukić Samed International Burch University, Bosnia and Herzegovina

DOI:

https://doi.org/10.54060/jieee.2023.64

Keywords:

Big data, Bitcoin, Machine Learning, Prediction

Abstract

Due to economic uncertainty and the financial crisis of 2008, a desire for an unregu-lated currency arose, leading to the invention of Bitcoin. Using a pseudonym called Satoshi Nakamoto, Bitcoin was created in 2009, anonymously or by a group of un-known individuals. Since Bitcoin has been the most valuable cryptocurrency in recent years, its prices have fluctuated dramatically, making it difficult to predict their pric-es. Investors, businesses, risk managers, and market analysts can all benefit from being able to predict Bitcoin prices. By using the Bitcoin transaction data obtained from the Bitstamp website in this study, several different Machine Learning models are employed to determine the most accurate model for predicting Bitcoin prices. These models are based on 1-minute interval exchange rates in USD from January 1, 2012, to January 8, 2022. Analysis was performed primarily with Python, but it was also used and Hadoop, a distributed data storage and processing framework that uses the map-reduce programming model to allow efficient parallel processing of Big Da-ta. Based on the results of our research, comprising three experiments, autoregres-sive-integrated moving average (ARIMA) makes the most accurate prediction of Bitcoin prices, with a 95.98% success rate.

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