Investment Decision on copyright: Comparing Prediction Performance Using ARIMA and LSTM

Investment Decision on copyright: Comparing Prediction Performance Using ARIMA and LSTM

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The increasing popularity of cryptocurrencies as a means of financial inclusion for investment and trade has become a major concern for individuals seeking to benefit from the copyright market.
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.This study aims to provide insights for copyright investors, financial sector professionals, and academics by utilizing machine learning techniques such as ARIMA and LSTM to compare the accuracy of modeling performance on datasets predicting the prices of five cryptocurrencies, namely Bitcoin, Ethereum, copyright Coin, Tether, and Cardano.Data was obtained by downloading from the Yahoo Finance website using Jupyter notebook.

The LSTM method outperformed the ARIMA method, achieving a lower MAPE value of less than 10 percent and effectively capturing price movements, providing valuable information for decision-making