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Advanced · Self-paced2026 Edition

Portfolio Theory

From Markowitz to risk parity and Black-Litterman — the modern portfolio-theory canon as it is actually used at Morgan Stanley, Bridgewater, and AQR. Twelve modules covering mean-variance, CAPM, APT, factor models (Fama-French, momentum, quality), Bayesian portfolio construction, alternative risk measures (VaR/CVaR/drawdown), and the real-world frictions that separate the optimisation output from the position you put on.

12

Modules

~11h 30m

Reading time

Advanced

Level

Self-paced

Format

§

Syllabus

  1. 01

    Returns, log returns, and the risk-return ledger

    Simple vs log returns. Why we annualise the way we do. Expected return, variance, the Sharpe ratio in one slide.

    ~50 minModule 01
    →
  2. 02

    Diversification — the only free lunch

    Two-asset variance algebra, the correlation lever, the variance-of-equal-weighted-portfolio limit, and why 30 random stocks already capture most of the gain.

    ~55 minModule 02
    →
  3. 03

    Markowitz mean-variance optimisation

    The 1952 paper. Setting up the QP. The efficient frontier in closed form. The two-fund theorem.

    ~65 minModule 03
    →
  4. 04

    Risk-free asset, CML, and tangency portfolio

    Adding cash. The Capital Market Line. The tangency portfolio as the single risky portfolio every investor holds.

    ~55 minModule 04
    →
  5. 05

    The CAPM

    Sharpe-Lintner-Mossin CAPM. Beta as systematic risk. The Security Market Line. What it gets right and where the empirics disagree.

    ~60 minModule 05
    →
  6. 06

    APT and multi-factor models

    Ross's APT. From CAPM's single beta to a vector of factor exposures. The arbitrage logic that anchors factor pricing.

    ~55 minModule 06
    →
  7. 07

    Fama-French, momentum, quality — the empirical canon

    Size, value, momentum, profitability, investment. The 3-, 4-, 5-factor models. What survived AQR's replication wars and what didn't.

    ~60 minModule 07
    →
  8. 08

    Black-Litterman — Bayesian portfolio construction

    Combining the equilibrium prior with subjective views. The master formula, the τ and Ω parameters, and why BL fixes the corner-solution disease of raw Markowitz.

    ~65 minModule 08
    →
  9. 09

    Risk parity and risk budgeting

    Equal risk contribution. The marginal-risk identity. Why Bridgewater's All Weather is risk parity dressed in macro intuition.

    ~60 minModule 09
    →
  10. 10

    VaR, CVaR, and drawdown

    Beyond variance. Value-at-Risk, expected shortfall, max drawdown. Coherence axioms and the case against VaR as a primary risk measure.

    ~55 minModule 10
    →
  11. 11

    Performance evaluation

    Sharpe, Sortino, Treynor, Information ratio, alpha, t-stat of alpha. How to read a tear sheet without being fooled by randomness.

    ~55 minModule 11
    →
  12. 12

    Frictions — transaction costs, turnover, capacity

    Why the optimiser's portfolio isn't the portfolio you trade. Linear and quadratic cost models, turnover penalties, capacity constraints, the implementation shortfall.

    ~55 minModule 12
    →

How to use this course

Start with module 01 if the material is new; skip ahead if you have prior exposure. Each module is self-contained but the arc is sequential — the projects in the final module assume the toolkit from modules 1-11. Every module ends with key takeaways and a curated further-reading list with primary sources.