• Overfitting is an error that occurs in data modeling as a result of a particular feature aligning too closely with a minimum set of data points.

  • Financial professionals run the risk of overfitting a model based on limited data and end up with erroneous results.
  • When a model is compromised by overfitting, it can lose its value as a predictive investment tool.
  • The data model may also be underfit, i.e. it is too simple and contains too few data points to be effective.
  • Overfitting is a more common problem than underfitting and usually results from an attempt to avoid overfitting.