Correlation turns positions into a portfolio.
Measure shared movement, find hidden concentration, and understand why diversification can disappear during stress.
Different names do not guarantee different risks
Diversification comes from distinct return drivers. A correlation matrix helps expose positions that may respond to the same shock.
Pearson correlation
Measures linear co-movement from -1 to +1. It is useful, but can miss nonlinear dependence.
Rank correlation
Spearman correlation compares ranks and can capture monotonic relationships less sensitive to outliers.
Rolling correlation
Recalculates relationships through time so regime changes and stress convergence become visible.
Correlation is conditional
Relationships estimated in calm periods can converge toward +1 when investors sell risk broadly. Always inspect rolling and stressed samples.
Two-asset diversification lab
See how weights, individual volatility, and correlation combine into portfolio volatility.
Asset B receives the remaining 50% weight.
Portfolio result
14.19%
estimated portfolio volatility
Diversification reduction
3.31 pts
Difference from the simple weighted average of standalone volatilities. Correlation is an estimate, not a permanent property.
Portfolio risk is more than the sum of positions
Concentration
Several trades depend on the same factor.
Covariance
Volatility and correlation interact with portfolio weights.
Breakdown
Relationships change precisely when protection is most valuable.
Lesson complete
Diversify drivers, not labels
Use rolling estimates, factor grouping, and stress assumptions before trusting a low correlation number.