Cryptocurrency Price Prediction Using LSTM, ARIMA, and Linear Regression

Abstract

Cryptocurrencies have emerged as a popular investment option, characterized by their high volatility and potential for significant price fluctuations.The ability to accurately predict cryptocurrency prices is crucial for investors to make informed decisions.In this research paper, we conduct a comprehensive comparative analysis of three widely used forecasting models -Long Short-Term Memory (LSTM), Autoregressive Integrated Moving Average (ARIMA), and Linear Regression -for cryptocurrency price prediction.We evaluate and compare the performance of these models using historical cryptocurrency data, considering various evaluation metrics and scenarios.