Lesson 6 of 14 · All lessons in this module
- Portfolio expected return and varianceVideo lesson
- Portfolio returns over time: drift and rebalancing
- The covariance matrix and many-asset portfolios
- Correlation and diversification
- Scenario-based portfolio risk and the many-asset limit
- Integrated cases: three-asset risk from volatilities, correlations and scenarios
- Minimum-variance and efficient frontiersVideo lesson
- Finding the minimum-variance portfolio and optimising weights
- Risk aversion and utilityVideo lesson
- Indifference curves and the capital allocation lineVideo lesson
- Theory assumptions, risk-aversion measures and the Sharpe ratio of the CAL
- Optimal risky portfolio and the optimal investor portfolioVideo lesson
- The risk-free asset, the market portfolio and the CMLVideo lesson
- Beta, the security market line and the CAPM
This lesson is part of the 2027 curriculum. You are following the 2026 curriculum, where it is not taught in this form. Switch if you are sitting the exam under the 2027 curriculum.
Lesson 6 of 14 · 16 min
Integrated cases: three-asset risk from volatilities, correlations and scenarios
Portfolio-risk cases give volatilities and correlations rather than covariances; the work is to convert, fill the matrix, add the cross terms once each and, when the assets offset, to recognise a correlation of −1 and its zero-risk weight.
In short
- Convert first: . The diagonal of the covariance matrix is the variances .
- Portfolio variance is the double sum : each pair appears twice. Take the square root last.
- Expected return needs only the weights and the expected returns. Correlations and volatilities affect risk only.
- A matrix labelled in %² or '×10⁻⁴' is on a percent scale: divide by 10,000 to get decimal variances.
- With the risk can be driven to zero at ; in a scenario table, two assets whose returns always sum to the same number have .
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