Credential program on the practitioner path
Certificate in Quantitative Portfolio Management
Seven courses and a capstone on building portfolios with numbers: mean-variance and its failures, robust optimization, Black-Litterman views, factors, asset allocation, bonds, attribution and risk.
Mean-variance optimization is easy to write down and hard to use. Feed it estimated returns and it builds extreme, unstable portfolios that fall apart out of sample. Quantitative portfolio management is the craft of making optimization useful: better inputs, sensible constraints, views expressed with honest uncertainty, and measurement that tells you whether the process added anything.
What does the certificate cover?
Modern portfolio theory and its limits; optimization with constraints, shrinkage and robust methods; the Black-Litterman model; CAPM, factor investing and the Fama-French models; strategic asset allocation and risk parity; yield curves and bonds in a portfolio; time series for return and risk forecasts; performance measurement and attribution; and value at risk and expected shortfall for portfolio oversight.
Who is it for?
Portfolio managers and analysts, wealth and pension professionals who want quantitative methods, and engineers joining asset management firms.
The courses in this program
- Modern Portfolio Theory and the CAPM Markowitz's framework from first principles: expected return and covariance, the benefit of diversification, the efficient frontier, the minimum variance and tangency portfolios, and the capital market line, all computed in Python. It also teaches the capital asset pricing model.
- Portfolio Optimization, Risk Parity and Black-Litterman Portfolio construction that survives real data: estimating covariance with shrinkage, constrained and robust optimization, risk budgeting and risk parity, hierarchical risk parity, and the costs of rebalancing. It also teaches asset allocation and risk parity and the Black-Litterman model.
- Factor Investing and the Fama-French Models How equity factors are defined, built and tested: value, momentum, size, quality and low volatility, the construction of long-short factor portfolios, combining factors, and the multiple-testing problem that hides behind hundreds of published factors. It also teaches the Fama-French factor models.
- Quantitative Trading: Edge, Sizing and the Sharpe Ratio The research process behind quantitative trading: forming a hypothesis, building a signal, turning signals into positions, accounting for costs and capacity, and deciding whether an edge is real. It also teaches the Sharpe ratio and the other measures of trading performance and position sizing with the Kelly criterion.
- Value at Risk, Expected Shortfall and Stress Testing 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. It also teaches expected shortfall, also called CVaR and stress testing and scenario design.
- Bond Pricing, Yield Curves and Mortgage-Backed Securities Bond pricing and the yield curve from first principles to desk practice: price and yield, duration and convexity, bootstrapping and fitting curves, carry and roll-down, and hedging a bond portfolio's interest rate risk. It also teaches mortgage-backed securities and prepayment risk.
- Time Series Analysis and Financial Econometrics The time series methods behind trading signals and risk forecasts: stationarity, autocorrelation, ARMA models, unit roots, volatility clustering and honest forecast evaluation. It also teaches financial econometrics: regression, its failures and their fixes.
What every course contains
Every paid course comes with the first seven and the certificate, whichever level it sits at. The proctored exam and the credential come when the course is taken as part of a Certificate, Diploma or Fellowship. Everything is self-paced: the material is yours to study in any order, at any hour, for the whole of the license.
- Workbooks. Written to train the thinking patterns and the important concepts of the course, with worked problems and the reasoning behind each answer, so that you learn to think the way the subject is thought.
- Audio edition. Focused, well-presented recordings with explainers and examples of the material, made to be interesting, relevant and entertaining, so that the general subject can be learned away from the desk.
- Notes. Pre-produced notes with every fact the course relies on, written out in full, so that nothing has to be transcribed from the films or the audio.
- Cheat sheet. One sheet with every important learning concept of the course on it, to keep beside you during the work and to revise from before the exam.
- Named sources. Every fact in the notes names its source, the paper, the book or the dataset, for anyone who wants to dig in further.
- Explainer films. Focused films, in the style of the sample films on the catalog page, that walk through the most difficult concepts of the course with visual explanations of a high standard.
- Transcript. A full transcript of every film and every audio recording, searchable and quotable.
- Proctored exam. Taken as part of a Certificate, Diploma or Fellowship, the course ends in a proctored multiple-choice questionnaire, with a pass mark of 60% and three retakes included. A course taken on its own is assessed by its coursework and has no exam.
- Verifiable certificate. A certificate of completion that a third party can verify: an employer sends the code on it to the credentials office and receives written confirmation of the course, the date and the result.
- Credential of the program. The Certificate, Diploma or Fellowship of the program, track or path the course belongs to, awarded when every course in it is passed. Which one depends on the program you choose.
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: the academy office.
- Algorithmic Trading Foundations: From Idea to Paper to Live An algorithmic trading course on the working basics: how electronic markets match orders, the order types an algorithm uses, three simple strategy families, the costs of trading, and a first backtest you can defend. It also teaches paper trading, and how to decide when a strategy is ready for real money.
- Python and SQL 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. It also teaches SQL for finance, so your data lives in a database rather than in files.
- Financial Markets and Instruments A financial markets course for people who will build models of markets: what each instrument is, who trades it, where and how it trades, and what happens between the click and the settled position.
- Probability for Quantitative Finance, with Statistics The probability every quant course assumes: distributions, expectation, conditioning and the limit theorems, with each idea tested on real return data. It also teaches the statistics for finance that every model rests on.
- Mathematics for Quantitative Finance: Calculus and Linear Algebra The calculus, linear algebra, optimization and differential equations that pricing, risk and portfolio models are built on, revised and applied to finance. It also teaches the linear algebra for finance behind portfolios and factor models.
What is the portfolio management capstone?
You build and run a multi-asset portfolio process: estimate inputs, express views with Black-Litterman, optimize under realistic constraints, rebalance with costs and report performance and risk to an investment committee. The report is judged on whether a committee could approve or reject the process from it.
What does the credential record?
It records that you passed the proctored exam of every course listed on this page and the capstone, assessed by the Institute's faculty. The credential is issued by the Institute. Each one carries a verification code that an employer can check with the credentials office.
Questions applicants ask
Is this a CFA preparation course?
No. It overlaps with parts of the CFA curriculum on portfolio theory, but it is a practical, code-based program and does not prepare for any exam.
Which tools are used?
Python with NumPy, pandas and open-source optimization libraries. No commercial software is required.
How long does the certificate take?
76 hours of material across the seven courses, each hour with its audio edition and workbook, and a capstone of 20 hours of your own work. The license runs 12 months, so you set the pace around a job.