‘The scope for portfolio customization is really wide’

What was your personal journey that led you to the field of quant investing?

“My journey started when I moved from Indonesia to the Netherlands back in 2011 to pursue my bachelor's and master's degrees in quantitative finance at Erasmus University Rotterdam. I have always loved working with data and numbers. In fact, physics was my favorite subject, so I surprised many people when I decided to take the finance route. But it was an easy choice for me as I grew up around many family members who have worked in related industries.”

“Following my studies, I subsequently landed an internship in the Robeco Quant Research team. This is where I got to apply the knowledge I had acquired by working on high-quality research and practical implementations. After I completed my internship, I got hired as a full-time researcher in the team and got to work on many research projects across various themes such as factor investing and alternative data.”

“After a few years in the role, I decided to explore the world of data science outside of finance. This led me to a data scientist role at a market research consultancy. There my love for data analytics and data visualization was deepened, and I also developed my skills in the field. Through this role, I started to discover many layers of data science beyond the cool graphs and complex programming.”

“I believe that data science is ultimately a way of communicating by transforming data into insights that allow you to answer questions. Three years later, and as fate would have it, I came back to Robeco in a unique role where the two worlds of data science and portfolio management blend. And as they say, the rest is history.”

What is the most interesting project you have worked on as part of the Quant Equities team?

“One of my main responsibilities is to develop and improve one of our proprietary tools – together with the Data Engineering and Quant Research teams – that we call the Quant Customizer. This tool is the ultimate embodiment of the blend between data science and portfolio management.”

“Over the past few years, we have seen increased demand for customized solutions and our quant platform is well suited to cater to these needs. In the past, it used to be a challenging process to translate client requests into solutions, and then to build and analyze the conceptual portfolios in order to create a proposal – all done with limited client interaction. Moreover, discussions on the proposal could end up leading to new requests.”

“The Quant Customizer is designed to speed up this process and to facilitate the joint development of customized solutions on the spot during client meetings. There are three main elements that we can customize. Firstly, we can choose an index that we want to enhance or base the portfolio on. Secondly, we can cater to clients’ specific risk and return objectives – such as factor exposures, information ratios, tracking errors, etc. Thirdly, we can also outline different sustainability goals.”

“Regarding sustainability, the tool is flexible in covering multiple client preferences including exclusions, ESG factors and environmental footprints such as those related to carbon emissions. In fact, we can even steer portfolios on specific UN Sustainable Development Goals (SDGs). The sustainability element has propelled the importance of the tool to the next level, as it is now one of the main topics of discussion in many of our client meetings.”

“The Quant Customizer enables the client to assume control. It is comparable to online software that allows a user to design a car, where they can choose the specifications such as the color or the type of rims.”

So how does the Quant Customizer tool benefit clients?

“Clients tend to differ in terms of the returns they are looking for, the risk they are willing to take and the sustainability elements they value most. From this perspective, customization is really vital.”

“I can mention a few examples to make this more tangible. Some clients have a specific tracking error restriction and aim for enhanced returns relative to a benchmark. Others accept benchmark-like returns while targeting a superior sustainability profile versus an index, while remaining within a tight tracking-error budget. Some focus on increasing their exposure to factors such as low risk, momentum, quality or value, while others might want to prioritize risk reduction.”

“So the scope for portfolio customization is really wide and the Quant Customizer allows us to take an in-depth look at the characteristics of a customized portfolio in its conceptual phase. What used to take days, weeks or months can now be done in a matter of seconds. This dramatically shortened lead time enables us to share these insights with clients in real-time during a meeting. This keeps the conversation rolling and enriches early discussions with clients.”

And from a different perspective, how does it benefit you as quant investors?

“The Quant Customizer can benefit us in various ways. Firstly, it can assist us in addressing specific client objectives in a targeted way, as opposed to just offering generic solutions. This is because it enables us to be flexible and equipped to perform customization. Its functionality allows us to visualize a conceptual portfolio at a point in time. This is helpful for our conversations with clients as we can quickly incorporate feedback during a meeting to better align our thinking with theirs.”

“Secondly, the tool allows us to present multiple options to a client. For example, one iteration could be predominantly sustainability driven, another could mainly be performance focused, while a further iteration could be somewhere in between these two.”

“A client is better able to assess what really works for them when they see the potential characteristics across the various portfolios, such as factor exposures, tracking errors and sustainability characteristics. Also, we are able to analyze the impact of specific choices – such as exclusions – on expected risk or return levels. We can therefore offer our clients a greater range of potential solutions.”

“Thirdly, the Quant Customizer could help us in the design of products. On the one hand, common client needs could become more apparent if we see significant design similarities when using the tool across many client discussions. On the other hand, if there are similar objectives that are repeatedly mentioned by different clients, we can use these insights to roughly map out a product to cater to those general needs, by using the tool.”

We have seen how client preferences can evolve over time. With this in mind, how does the team plan to keep the tool relevant?

“We have been continuously developing and improving the Quant Customizer since its creation. In particular, there are three areas that we always try to stay on top of, namely data engineering, research and client relevance.”

“From a data engineering perspective, we keep abreast of developments concerning the technologies and techniques that we use. From a research angle, we ensure that the optimization machinery behind the tool is always in line with the latest research developments and insights from our Quant Research team. And from a client point of view, we strive to keep the tool relevant by incorporating the risk, return or sustainability elements that our clients view as important.”

I assume the journey has not always been smooth sailing. What have been the main challenges in building the Quant Customizer?

“I believe that with any idea or initiative, the main challenge always lies in developing the concept into the intended outcome. When it came to the Quant Customizer, we wanted to build a holistic, properly functioning and client-ready tool. This required expertise from many areas such as data engineering, infrastructure and research, as well as input from the client-facing side.”

“We therefore put together a team of individuals from all these areas specifically for the development and enhancement of this tool. This approach helps us to safeguard the accuracy, stability and relevance of the tool.”

“Another big challenge we faced was establishing the sweet spot or the balance between meeting client needs and having a tool for mass customization. In terms of our thinking, we wanted to develop the Quant Customizer so that we could use it with multiple clients with varying needs. So we strive to keep it agile and flexible enough.”