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Risk Management

Overview

Identify, quantify, and control market, liquidity, and operational risks. This topic underpins resilient trading by translating uncertainty into limits, monitoring, and action.

Status: 🟧 Intermediate

Who should learn this?
✅ Traders and portfolio managers
✅ Quants/analysts building risk models
✅ Engineers adding controls and monitoring

Prerequisites

  • Probability and statistics; distributions and tails
  • Time series and volatility modelling
  • Python/R for analytics and reporting

Learning Objectives

  • Compute VaR/ES via parametric, historical, bootstrap methods
  • Stress test scenarios and shocks; model liquidity/impact
  • Implement exposure, drawdown, and kill-switch controls

Key Concepts

  • Tail risk – VaR/ES, EVT, drawdowns
  • Exposures – Factor, sector, concentration
  • Stress testing – Historical and hypothetical shocks
  • Liquidity/impact – Costs under scarcity

Applications in Algorithmic Trading

  • Pre-trade – Sizing and limits
  • In-trade – Real-time exposure/PNL monitoring
  • Post-trade – Reporting, breaches, remediation

🧠 Study Materials

📚 Books

📘 Beginner

Title Author(s) Description Link
Financial Risk Forecasting Jon Danielsson Practical VaR/ES, volatility https://press.princeton.edu/books/paperback/9780691166278

📗 Intermediate

Title Author(s) Description Link
Value at Risk Philippe Jorion Comprehensive VaR treatment https://www.mheducation.com

📙 Advanced

Title Author(s) Description Link
Quantitative Risk Management McNeil et al. EVT, copulas, advanced models https://press.princeton.edu/books/hardcover/9780691166278/quantitative-risk-management

🎓 Courses

📘 Beginner

Course Title Provider Level Description
FRM Concepts GARP/Prep Beginner Overview of risk domains

📗 Intermediate

Course Title Provider Level Description
Financial Engineering & Risk Management Columbia (Coursera) Intermediate Practical models and cases

📙 Advanced

Course Title Provider Level Description
Advanced Risk Topics University/Industry Advanced Liquidity, EVT, stress frameworks

🏅 Certifications & Developer Programs

Credential Provider Description
FRM GARP Global risk certification
PRM PRMIA Risk management credential

🛠️ Tools & Libraries

  • Python – pandas, NumPy, scipy, statsmodels, arch
  • Risk – Riskfolio-Lib, PyPortfolioOpt (risk budgets)
  • Monitoring – Prometheus, Alertmanager, Grafana

🧪 Hands-On Projects

  • Compute rolling VaR/ES with bootstrap backtesting
  • Implement risk limits and a kill-switch in a paper trader
  • Build daily risk reports with exposures and drawdowns

✅ Assessment

  • Explain differences among VaR methods and pros/cons
  • Evaluate backtesting results for risk model accuracy
  • Design stress scenarios relevant to your portfolio

❓ FAQs

Q: VaR vs ES?
A: ES measures expected loss beyond the VaR quantile and captures tail severity.

Q: How to avoid risk model blindness?
A: Combine models with stress tests, limits, and human review.

🔗 Next Steps