Introduction to Financial Markets and Time Series

This lecture covers the basics of financial markets and financial time series, including topics such as available data sources, equity products, no arbitrage pricing, stylized empirical facts like autocorrelation and volatility clustering, sample statistics, and confidence intervals. It also delves into the application of machine learning in finance, discussing the goals, applications, and timeline of machine learning, as well as the main types of algorithms used. The lecture concludes with a focus on natural language processing and its applications in sentiment analysis and document analysis.