Machine learning is not the hype anymore — it is already a part of each industry in multiple verticals. From commerce to manufacturing, health care, finance, delivery, and more, ML-based solutions act to help with tasks to make everyday life easier.
Find out more about top use cases of machine learning for trading and the opportunities that the application of AI and ML opens up.
Sentiment Analysis
Sentiment analysis is a field of study that uses ML, natural language processing and AI techniques to reveal people’s feelings and sentiments hidden behind a text.
In trading, sentiment analysis tools are used for predicting stock movements based on publicly accessible information from microblogging networks such as Twitter and StockTwits as well as financial data from Finance Yahoo. Such information gives crucial insights into public perception towards сertain firms, and generally helps traders make informed decisions on whether to buy or sell stocks.
Pattern Recognition
Patterns play a crucial role when analyzing and forecasting the stock market. However, the processes for identifying ever-changing patterns in the data consumes much time and energy. ML makes these grueling tasks a lot easier that coupled with experience-based intuition of traders leads to quicker and more accurate decisions.
Real-time Data Forecasting
In fact, such real-world problems like pandemics, political unrest, resource depletion ect. have a very profound impact on the trading industry. In this regard, real-time forecasting can become a superpower for traders and trading establishments.
ML algorithms can be trained to gather data from a wide range of sources (news headlines, social media comments, and other platforms) and make human-like judgements, forecasting the results of the world’s issues at speeds that humans cannot.
Chatbots In Trading
AI-powered chatbots are the present and the future of trading. A single bot is able to interact with multiple traders at the same time, providing them with such valuable information like real-time quotes, account statements, central bank announcements, stocks with the greatest price movements, etc.
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