Machine learning (ML) models have already been around for decades. The exponential growth in computing power and data availability, however, has resulted in many new opportunities for ML models. One possible application is to use them in financial institutions’ risk management. This article gives a brief introduction of ML models, followed by the most promising opportunities for using ML models in financial risk management.
A part of the curriculum of the Econometrics & Mathematical Economics master’s degree given in the VU University Amsterdam is the course Time Series Econometrics. In this course, students are taught how to analyze time series with the aid of ‘state-space models’, on the assumption that observations over time (such as the content of the Nile, for example) are driven by non-observed factors.