Credential program on the practitioner path
Certificate in Quantitative Risk Management
A financial risk management certification in five courses and a capstone on measuring and governing market risk: VaR and expected shortfall, volatility models, stress tests and the validation of the models themselves.
A risk number is only useful if the people relying on it know how it was made and where it fails. Value at risk was built to summarise a trading book in one figure; it was also blamed for the comfort it gave before 2008. This financial risk management certification covers the measures, the models behind them and the checks that keep both honest.
What does the certificate cover?
Value at risk by historical, parametric and Monte Carlo methods; expected shortfall and its estimation; GARCH models for volatility; stress testing and scenario design; and model risk management, from validation to governance.
Who is it for?
Risk analysts and managers in banks, funds and trading firms; quantitative developers building risk systems; and traders who want to understand the limits their risk function sets.
The courses in this program
- Value at Risk How value at risk is calculated, tested and misused: historical simulation, variance-covariance and Monte Carlo methods, volatility-weighted variants, time scaling, regulatory backtesting, and what VaR does not tell you.
- Stress Testing How to design and run stress tests on a portfolio: historical and hypothetical scenarios, shocking risk factors consistently, reverse stress testing, liquidity effects, and presenting results that lead to decisions.
- Model Risk Management How financial institutions control the risk of using models: what counts as a model, inventories and tiering, independent validation, conceptual soundness, benchmarking and outcomes analysis, ongoing monitoring, and the governance expected by supervisors.
- Expected Shortfall and CVaR The risk measure that replaced VaR in bank trading-book rules: coherence and subadditivity, estimating expected shortfall with historical, parametric and extreme value methods, the elicitability debate and backtesting, and minimising CVaR in portfolios.
- ARCH and GARCH Volatility Models The GARCH model and its family, from Engle's original ARCH to asymmetric and multivariate GARCH: derivation, maximum likelihood estimation, diagnostics and forecasting.
What should you know before you start?
The courses in this program build on the courses below. They are not part of the program and not included in its price. If you have not studied this material, take them first. Admissions can tell you whether your background already covers them: [email protected].
- Python for Finance A Python for finance course with the Python every later course assumes: loading and cleaning market data with pandas, computing returns and risk with NumPy, plotting, and writing code another person can rerun.
- Probability for Quantitative Finance The probability every quant course assumes: distributions, expectation, conditioning and the limit theorems, with each idea tested on real return data.
- Statistics for Finance and Trading Estimation, testing and regression for financial data, with the traps that make trading research go wrong: dependence, fat tails and testing too many ideas.
- Time Series Analysis for Finance The time series methods behind trading signals and risk forecasts: stationarity, autocorrelation, ARMA models, unit roots, volatility clustering and honest forecast evaluation.
What is the risk management capstone?
You build a risk report for a trading book: VaR and expected shortfall by several methods with backtests, a set of stress scenarios with their rationale, and a model validation note on one of your own models. Faculty mark it as a second-line risk function would review a first-line submission.
Is this credential accredited?
No. It is an unaccredited Institute credential. It records that you passed every assessed component listed on this page, marked by the Institute's faculty. It is not a university degree and is not issued by Carnegie Mellon University. Each credential carries a verification code that an employer can check with [email protected].
Questions applicants ask
Does this prepare me for the FRM exam?
No. FRM is a designation of the Global Association of Risk Professionals, which does not endorse this program. The Institute offers a separate FRM Exam Preparation course for Part I.
Is the program about regulation?
Regulation appears where it shapes the methods, for example the move from VaR to expected shortfall in bank capital rules. The program is about the quantitative methods, not compliance.
How long does the certificate take?
128 hours of study. At eight hours a week, about four months.