Root mean squared error
The square root of the average squared forecast error. Squaring weights large errors heavily; the model with the lower value out of sample is preferred. Also used to judge models with continuous targets.
Where you will meet it
Root mean squared error appears in 3 learning outcomes on the CFA syllabus. A few of them:
- Distinguish forecasts made within the sample from those made outside it, and rank time-series models by forecast accuracy using root mean squared error
“Forecasting accuracy is compared with root mean squared error: square each forecast error, average the squares, and take the square root.”
- Choose a suitable time-series model for a given investment problem and give reasons for the choice
“Finally compare models on out-of-sample RMSE.”
- Judge how well a machine learning algorithm fits
“For continuous targets, root mean squared error is the usual measure.”
Practise it
Practise root mean squared error until it is automatic: questions that explain every wrong option.
Take the free diagnostic →