Applied Financial Data Analytics: Stock Analysis and Portfolio Risk

Making sense of financial market data requires more than just looking at spreadsheets. Understanding how to leverage data analytics is key to evaluating investment risks, stock performance, and portfolio strategies. This course guides you through the foundational concepts of financial analytics, showing you how to turn raw market data into actionable investment insights. You will transition from understanding basic stock metrics to analyzing complex time-series data and exploring the mechanics of algorithmic trading. What you'll learn: - Understand foundational financial concepts, including stock prices, returns, and market volatility. - Analyze historical stock trends and asset performance using modern time-series data techniques. - Evaluate the risk-reward trade-offs of investment portfolios using modern portfolio theory. - Apply modern dataframe libraries to clean, manipulate, and structure financial datasets efficiently. - Explore the fundamentals of algorithmic trading and how automated systems execute market strategies. You will start with core terminology and financial definitions before moving into the practical analysis of stock returns, risk metrics, and portfolio optimization techniques. Through clear written explanations and structured code snippets, you will build a practical understanding of how data shapes modern finance. This course is designed for beginners, aspiring financial analysts, and business professionals with no prior experience in financial modeling or data science. Start reading today to unlock the power of data in the financial markets.