Financial Risk Analysis and Management with R

Managing investment risk is a critical skill in modern finance. Understanding how to quantify market fluctuations allows analysts to protect portfolios and make data-driven investment decisions. This written course guides you through the fundamentals of portfolio risk management, teaching you how to measure and analyze financial market risk using the R programming language. You will learn to work with real-world financial datasets, clean and manipulate financial data, and build standard risk models. What you'll learn: - Learn the foundational concepts of financial risk, asset returns, and portfolio diversification. - Calculate portfolio returns and volatility using modern R packages and tidy data principles. - Implement Value-at-Risk (VaR) models to estimate potential portfolio losses. - Compute Expected Shortfall (ES) to analyze extreme market events and tail risk. - Apply historical simulation and parametric methods to analyze stock data. - Practice writing clean, reproducible R code for financial data analysis. You will start with core financial definitions and basic statistical concepts before progressing to practical risk modeling techniques with step-by-step code explanations and written exercises. This course is designed for aspiring financial analysts, risk managers, and beginners to R who want a structured introduction to quantitative finance. No prior programming experience is required. Start reading today to build your quantitative risk management skills.