Investment Management with Python

Study portfolio construction through worked calculations, editable Python, and interactive charts. Python runs in your browser.

Start Course 1

Go to Course 2

1. Portfolio Management Fundamentals

Returns, risk, optimization, dynamic allocation, and asset-liability management. Four chapters available.

Course overview

2. Advanced Portfolio Construction and Analysis

Factor exposures, covariance and expected-return estimates, Black–Litterman, and risk budgets. Four chapters and a capstone available.

Course overview

3. Machine Learning for Asset Management

Overview and preparation available. Five chapters planned on learning methods, factor models, diversification, and regimes.

Overview and preparation

4. Alternative Data for Asset Management

Overview and preparation available. Four chapters planned on consumption, text, corporate filings, and media.

Overview and preparation

How to Study

Basic Python and familiarity with percentages and averages are useful. Start with Course 1 if portfolio construction is new to you; Course 2 examines the estimates behind portfolio decisions.

Read the worked calculation, run the Python cells in order, then change one assumption and explain the result. The charts display your calculations. Use the course overviews to choose where to begin.

About This Resource

I developed these notes and Python examples after completing EDHEC Business School's Investment Management with Python and Machine Learning specialization (certificate). They are an independent study resource.