Network Analysis – Exploring company linkages with machine learning techniques

In this internship you will be looking at a big network of companies and how these companies interact with each other. Modern financial markets consist of many individual companies that operate from all over the world. In this global economy there are many linkages across firms, e.g. via common suppliers or clients, country or sector exposures etc.. In this project you will focus on these links across companies, from both an equity and bond holder’s perspective. You will explore various ways of unraveling this network using state-of-the art statistical techniques.

The project covers the entire quant model development cycle: conducting a literature review, analyzing the data, programming the back-tests, analyzing the results, discussing results with researchers and portfolio managers, writing a research report and giving a presentation. As with all Super Quant internships, the assignment will be supervised by an experienced empirical researcher of Robeco’s Quantitative Research department. Practical feedback will be provided by several equity and credit portfolio managers. Creative, analytic and programming skills are essential in order to successfully complete the project.

Are you interested?

Let us know your motivation and send it together with your CV and list of grades to


Cohen, L. & Frazzini, A. (2008), Economic links and predictable returns, The Journal of Finance 63(4), 1977-2011.

Rapach, Strauss, Tu & Zhou (2015). Industry Interdependencies and Cross-Industry Return Predictability. Working Paper

Baitinger & Papenbrock (2016). Interconnectedness Risk and Active Portfolio Management. Working Paper