Actively Traded Models

Use Case

A portfolio manager wants to operate on a fully quantitative basis using machine learning.


The portfolio manager creates a model (using their own unique variables), sets portfolio constraints and then has the model “go live” with current data. They then execute the model’s dynamic trading strategy. 


A fully quantitative portfolio runs using technical variables and/or fundamental data.

Since going live in October 2018, this quantitative model returned 36.8%, with gross exposure of 150% long and 50% short, compared to the benchmark return of 4.9%. 

Actively Traded Models


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