Analysis of Various Machine Learning and Deep Learning Algorithms for Bitcoin Price Prediction

Abstract

Bitcoin (BTC) is a cryptocurrency meaning that it is a virtual asset that works on encryption systems to control production of units and verify the funds transfer. Bitcoin's operation is independent of central bank and can be used as a decentralized medium of exchange. Being an emerging domain, the blockchain systems on which these cryptocurrencies are based, are a great source of investment among enthusiasts. However, there is high volatility in the price of Bitcoin and thus it paves the way for its prediction so as to get a clear insight on its trend. Forecasting Bitcoin prices can provide valuable insights for investment portfolio management, risk assessment, and the identification of profitable trading or arbitrage opportunities. Furthermore, Bitcoin price predictions may assist firms that accept Bitcoin payments in enhancing their financial management practices by improving their revenue and cash flow forecasting. Additionally, governmental entities and regulatory bodies could leverage Bitcoin price forecasting as a tool for monitoring and regulating the cryptocurrency industry. This paper explores the effectiveness of ML models in predicting Bitcoin price by analyzing a diverse set of historical data. We evaluate several ML algorithms, and compare their performance in terms of accuracy to find out best algorithms for short term and long-term Bitcoin price prediction.