Market Risk & Stress Testing in Python

Descripción

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 table Throughout 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.

Lo que aprenderás

• Implement historical and parametric Value at Risk (VaR) models in Python and interpret their results
• Analyze tail risk, stress scenarios, and drawdowns to understand losses beyond standard VaR
• Backtest market risk models and evaluate their strengths and limitations using real market data.
• Build a concise, decision-ready market risk report combining VaR, tail risk, stress tests, and drawdowns.

Requisitos

• Basic Python knowledge is recommended. Familiarity with financial markets is helpful, but no prior risk management experience is required.