AI Based Commercial Decisions: The Cryptocurrency Market Case

The cryptocurrency market is a fast-growing and highly volatile market that poses significant challenges for investors seeking to make informed decisions. As the market continues to evolve and become more mainstream, there is a growing need for accurate forecasting methods to help investors navigate this unpredictable terrain. This study examines the potential of machine learning techniques, specifically Long Short-Term Memory (LSTM), for predicting future trends in the cryptocurrency market. The study evaluates the effectiveness of various machine learning algorithms in predicting the price movements of different cryptocurrency assets. The research employs historical data analysis and machine learning techniques, focusing on LSTM. LSTM is a neural network that can capture long-term dependencies in time-series data suited for predicting trends in the cryptocurrency market. The study uses performance criteria such as recall precision, measuring how well an algorithm can identify true-positive and negative cases in a dataset, required for assessing its accuracy and effectiveness. This study has the potential to provide valuable insights into the effectiveness of machine learning techniques, specifically LSTM, for predicting trends in the cryptocurrency market. Investors can make better decisions in this highly volatile and unpredictable market by identifying the most effective and efficient algorithm expanding the use of machine learning in the financial forecasting domain.