Lesson 4 of 14 · All lessons in this module
  1. Portfolio expected return and varianceVideo lesson
  2. Portfolio returns over time: drift and rebalancing
  3. The covariance matrix and many-asset portfolios
  4. Correlation and diversification
  5. Scenario-based portfolio risk and the many-asset limit
  6. Integrated cases: three-asset risk from volatilities, correlations and scenarios
  7. Minimum-variance and efficient frontiersVideo lesson
  8. Finding the minimum-variance portfolio and optimising weights
  9. Risk aversion and utilityVideo lesson
  10. Indifference curves and the capital allocation lineVideo lesson
  11. Theory assumptions, risk-aversion measures and the Sharpe ratio of the CAL
  12. Optimal risky portfolio and the optimal investor portfolioVideo lesson
  13. The risk-free asset, the market portfolio and the CMLVideo lesson
  14. 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 4 of 14 · 12 min

Correlation and diversification

Lower covariance between holdings lowers portfolio risk without lowering expected return; that free risk reduction is the diversification benefit.

In short

  • Portfolio variance = squared-weight variance terms + covariance terms. Only the covariance terms depend on co-movement.
  • Independent (zero-covariance) assets leave only the variance terms; negative covariances cut risk further.
  • Expected return does not depend on correlation, so lower correlation means less risk for the same expected return: the diversification benefit.
  • At ρ\rho = +1 there is no benefit: σp\sigma_p is the weighted average of the σ\sigmas. The lower ρ\rho, the bigger the benefit.
  • Changing weights traces out a curve of risk–return combinations; with low correlation, adding some of a riskier asset can even lower total risk.

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