Groundlearn / Glossary / Multicollinearity
Multicollinearity
A CFA and FRM term, defined in plain English with the distinction examiners test.
What it means
Two or more independent variables in a regression that are highly correlated.
The exam angle
The giveaway is a high R² with individually insignificant t-statistics. The regression as a whole explains plenty; it cannot attribute the explanation.
Where it appears in the syllabus
- Quantitative MethodsCFA Level II · exam weight 5–10% · Multiple regression, misspecification, time series, machine learning.
- Quantitative AnalysisFRM Part I · exam weight 20% · Probability, hypothesis testing, regression, time series, volatility, simulation.
Related terms
- Coefficient of determinationThe fraction of the dependent variable’s variation explained by the regression.
- HeteroskedasticityRegression errors whose variance is not constant across observations.
- Linear regressionFitting a straight line through data by minimising the sum of squared residuals, to explain a dependent variable by…
- Serial correlationRegression errors correlated with their own past values.
- OverfittingA model that fits the noise in its training data as well as the signal, so it performs well in-sample and poorly on…
- Supervised learningMachine learning that fits a model to examples with known outcomes — labelled data — so it can predict the outcome for…
Educational content only. This is not financial, investment, legal or regulatory advice. Check the official curriculum for your own exam before relying on any definition here.
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