Machine Learning for Finance and Trading

Catalog description

Machine learning (ML) has become an essential tool in finance and trading by automating the process to identify patterns and providing more accurate estimates of risk and valuation. Topics of this course will include the acquisition of financial data, working with time series, computing well-known technical features, visualization, trading signals, backtesting, training and evaluating ML models, supervised learning. Additional topics may include unsupervised and reinforcement learning, deep learning models, and working with different data sources such as sentiment. This course uses Python and Python libraries used in the industry for analysis and visualization. The course assumes a college/master's level statistics course, with some knowledge of computer programming. Some knowledge of python, NumPy, and pandas, also, basic familiarity with machine learning such as classification and logistic regression are helpful. Data and examples use both traditional and crypto-asset markets.