Market Risk & Stress Testing in Python is a practical, career-focused course that teaches you how banks and institutional risk teams measure, report, and communicate market risk.You will build end-to-end Value at Risk (VaR), tail risk, and stress testing workflows in Python, starting from raw market data and finishing with a professional risk report similar to those used in front office risk, market risk, and quantitative risk roles.This course focuses on implementation, interpretation, and reporting — not trading strategies, alpha generation, or academic derivations.You’ll learn how to:• Load and prepare market data the way risk teams do• Analyze return distributions and understand fat tails• Build historical and parametric VaR models• Backtest VaR and interpret exceptions for governance• Measure tail losses beyond VaR• Run hypothetical and historical stress scenarios• Analyze drawdowns and worst-case periods• Consolidate everything into a clear market risk summary tableThroughout the course, every concept is tied back to real-world usage, including risk limits, reporting cycles, management decision support, and model limitations.This course is ideal for students, analysts, quants, and developers who want job-relevant Python skills in market risk, stress testing, and financial risk management — the exact skills demanded by banks, asset managers, and institutional risk teams.
What you'll learn
load and prepare market data for analysis
build and backtest historical and parametric VaR models
measure tail losses beyond VaR
run hypothetical and historical stress scenarios
analyze drawdowns and worst-case periods
Course objectives
understand and report on market risk
develop practical skills in Python for financial risk management
communicate effectively about market risk findings