AI for Predictive Analytics in Cryptocurrency Markets

Abstract

The dynamic crypto-assets business is famous for its highly changing prices, quick price swings, and the influence of global socio-economic factors on the prices. The workflows of traders and investors have to deal with these complications because they are looking for safe ways to manage risk and maximize profits. This research investigates how Artificial Intelligence (AI) for predictive analytics could be used to improve decision-making in cryptocurrency markets. Using the state-of-the-art machine learning techniques, model deep learning strategies, and assessment of the opinion of the audiences and sentiments, the research is verifying the feasibility of the synthesis of the structured data such as the historical price movement and the unstructured data comprising social media and news sources. By building and comparing different predictive models, this research shows that AI-powered methods can be effectively used for predicting the movements of cryptocurrency prices and the discovery of irregularities in the market. Aspects identified in this research include the fact that AI is successful in providing conclusions that can be acted on and automating time-consuming research in such a capricious and unpredictable environment.