You are here:

Alumni Interview: Quantitative Equity Researcher Menno van Dijk

23/04/2021

- Can you introduce yourself?

 Hi everyone! My name is Menno, I’m 25 years old and grew up in the small village of Udenhout which lies quite close to Tilburg, which where I currently live. I have been working as a quantitative equity researcher at Robeco for just over 1 year now. Prior to working at Robeco I was a student at Tilburg University, where I completed a Bachelors in Economics as well as a Masters in Data Science and a Masters in Finance. During my time studying at Tilburg University I used to be part of an investment club quite similar to B&R Beurs, which was called the A&F Investments Committee. At this committee we ran a student-managed portfolio of around €50k. Everyone could pitch for new securities to be added to the portfolio, or pitch for selling of an existing position. On top of that, we had a risk management team at this committee, which I was heading in the final year of me being in that committee. In my final year of studying at Tilburg University, I also decided to apply for the Super Quant Internship of Robeco. Luckily I was accepted into this internship, since it was definitely a very enjoyable experience. After completing my internship I eventually got offered a position to join Robeco full-time, which I happily accepted.

 

- What does it mean to be a Quant Researcher at Robeco?

You can see the role of a quantitative researcher as one of a data scientist, financial analyst and detective all-in one. You need the data science skills of programming, modelling and data wrangling/visualization in order to get value out of the large amounts of financial data that we have available to us. On top of that, it is very helpful to have the skills of a financial analyst in order to get a solid grasp of how certain aspects of the world or a company can affect share prices. And finally, in order to put all of the pieces together that you might need in order to be able to explain stock returns, you need the skillset and creativity of someone like a detective. The role of a quantitative researcher at Robeco in that sense is really diverse, as it requires you to have knowledge on a various different fields of science. But because the skillset required to do the work of a quantitative researcher is so diverse, it also makes it a lot of fun!

 

- Where do you see yourself in 10 years from now on?

Difficult question! As quantitative researchers we tend to be very happy if we can even predict 1 year ahead, so let alone predicting 10 years ahead. But let me try to answer your question as best as I can: I would love to still be active in any field that will allow me to work on developing predictive models using large amounts of data, whether that be in the financial industry (at Robeco) or in any other industry.

 

- Which skills do you need to be a successful Quant Researcher?

I think the answer here is very similar to what it means to be a quantitative researcher at Robeco. The most important skills that you will need are regarding programming, predictive/prescriptive modelling and data wrangling/visualization. It’s also very helpful if you have a healthy dose of creativity. Eventually though, if you are proficient in all of the skills mentioned above, it all boils down to having a sound judgement on the work you are delivering. If you are able to think critically and extensively about topics relevant to your research, you have a high probability of becoming a successful quant researcher.

 

- What are some of the most important things that you learned at Robeco?

Something that you learn very early on in your career at Robeco is to always be critical. We really have a culture where it is okay to critize other’s work (in a friendly manner of course), as long as you can base your criticism on evidence. Not only should you be critical on the work of others, but also on your own work. On top of that, we really value initiative a lot at Robeco. If you have a great idea that you would like to test, there is no one that will hold you back. By being in an environment like Robeco’s which stimulates initiative a lot, it really helped me to voice my own opinion and ideas a lot more than I used to do.

 

- What kind of projects are you currently working on, or have you worked on? 

Recently I have been mostly working on alternative data research. Given that Robeco is striving towards being a next-generation asset manager, we are always looking for ways that we can capture value on top of the traditional quantitative factors that we are currently using in our models. One of the ways we think we can achieve this is by using non-traditional datasets to capture information that is relevant to stock returns. This is an area of research that I have really focussed on the past couple of months. If everything goes according to plan, this research will also be approved to be used in our models soon!

 

- Which trends do you currently observe in quantitative asset management and/or factor investing? 

As I also mentioned in my previous answer, there seems to be a tendency of asset managers to largely enrich the pool of factors beyond the well-known traditional quantitative factors such as value, momentum, quality and low-risk, and going more into alternative style factors derived from, for example, machine-learning techniques and alternative data. Additionally, we see a very large push towards sustainable investing across the (quantitative) asset management industry. Since Robeco really is a global thought-leader in this regard we are working very hard to remain in this position.This means that a lot of the research agenda of our quantitative research teams is dedicated towards performing research into sustainable investing.

 

- What is your favorite mathematical formula, and why?

I think that would have to be the formula used to arrive at the beta coefficients within OLS ([X’X] -1X’y). While it is a very simple formula, it is extremely useful and I would bet that almost all asset managers still use OLS in one way or another within their investment process.

 

- Before you started as a Quant Researcher at Robeco, you also joined their “Super Quant” internship. Can you tell us something about this internship, and your own experiences?

The Super Quant Internship is an internship wherein you will be writing your thesis on a specific topic together with experienced researchers at Robeco. Every year Robeco publishes a large list of internship topics on their website that every master student can apply for. After a selection procedure where you will have to send your motivation letter and CV, as well as having talks with your possible supervisors, you will be invited to join Robeco to write your thesis. I was part of the 2018 cohort of Super Quant Interns and I can tell that my experience was very positive. It was great to work together with experienced researchers towards a common goal, namely writing a very solid master thesis on an interesting topic. Additionally, the fact that there are many other interns who are writing their thesis at the same time makes it so that you always have other students that you can go to for a quick chat or some help. Other than that, it is also a great opportunity for both Robeco and all interns to get to know each other, which might eventually lead to a job offer to work inside the quantitative research team of Robeco.

 

- What is your favourite factor or asset pricing anomaly, and why?

I would have to say that this would be the momentum factor. For one I like it because it has been proven time after time again that it is a persistent driver of returns, across a wide variety of financial assets, regions, countries as well as time periods. Additionally, I believe that the momentum factor in particular rewards investors that are willing to take on some risk as it is quite a risky factor, which can be seen by the large drawdowns that can happen as soon as market regimes switch (the 2009 momentum crash is a nice example of that). Given the fact that I am personally more of a risk-seeking investor, I really like this fact about the momentum factor. Now of course there are great ways of reducing this “crash risk” of the momentum factor (at Robeco we have written many papers on this), but if you would ask me about my favourite “pure” asset-pricing anomaly, then momentum would be it.

 

- What was a memorable moment for you at Robeco?Or what achievement did you make at Robeco so far?

I think my most memorable moment is when I completed my first research project and heard that my research was accepted to be used in our models. When you are working on a research project it is usually a relatively lengthy process that starts with investigating what you can find in the academic literature. After the exploratory step is completed, you perform all of your research and communicate the results of this research to internal and external stakeholders. Finally, after the research project gets accepted for use within our models, you will still have to implement your research. Whenever that process is finished and you get an e-mail from your managers that the research you have worked on for a long time is accepted and will play a part in selecting stocks within our models, it’s a really cool feeling!

 

- Do you have any advice for students that want to dive into the world of quantitative asset management?

I would say if you are interested in working in the world of quantitative asset management, it is important to be proficient at programming, (predictive) modelling and working with (large) datasets. The best way I know how you can combine learning about all of these three areas is by going to Kaggle.com and participating in their data-science challenges. Even if you have no clue on how to start, this website has tons of examples and tutorials from other people that will go through their code step-by-step and discuss every choice they made for a particular challenge. Other than that, read papers! A lot of the things that we do in quantitative asset management can be learned from reading academic papers. Good papers to start with are the quite famous Fama and French (1992) and Fama and French (2015) papers. By reading these and by diving deeper in the references that are mentioned in these papers you will get a good overview of the type of research we are conducting at Robeco as well. Good luck!

partner

Become a partner?