Natixis creates model to ‘learn’ how factors interact

Random forest technique sheds light on flux in how factors mix, manager says

factor-connections-0219.jpg

A team of quants at Natixis Investment Managers has developed a machine learning approach to risk modelling that they say will help them understand better how risk factors combine to drive asset prices.

The new model uses random forests, a type of supervised machine learning algorithm, to draw out non-linear relationships and interactions between the four Fama-French-Carhart factors – market risk, size, value and momentum – that may have been missed by traditional models.

“Over the years I

To continue reading...

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an indvidual account here: