Quantitative investing
Taking emotions out of investing
Quantitative solutions exploit deeply entrenched cognitive biases that afflict investors. Our disciplined, transparent and systematic approach keeps emotions at bay and takes advantage of market inefficiencies driven by human behavior to deliver risk-adjusted performance for our clients over time.
start of track record
years of applied quantitative innovation
bn USD assets (as of March 2024)
Proprietary research
Our multi-decade track record in quantitative investing is based on proprietary research, including several seminal publications that have made valuable contributions to the academic literature.
Given our heritage and strong research-driven culture, we aim to remain at the forefront of quantitative investing and we aim offer the best possible solutions to our clients. Our research agenda is focused on improving and diversifying our investment approach, for example, through the use of additional novel data sources or techniques as well as looking more deeply at areas such as sustainable investing.
Our most important quant papers
Next-generation quant
We are convinced that developments in alternative data, artificial intelligence and machine learning are pivotal to the evolution of quantitative investing. Not only can they widen the opportunity set by unearthing new and uncorrelated alpha signals, they can also improve our existing investment processes by leading to better model predictions on risk, return and sustainability.
As pioneers, our driving force is a healthy appetite for client-centric innovation that results in state-of-the-art solutions: to cater to evolving financial and sustainability needs. We are therefore focused on improving our current offering and developing next-generation quantitative solutions that are diversified from traditional quantitative portfolios. Importantly, this will be carried out in the context of sticking to our investment philosophy based on strong empirical evidence, sound economic rationale and a prudent approach.
Meet the team
We have a large quantitative investment team in the industry with over 40 dedicated portfolio managers, researchers, client portfolio managers and investment specialists. This allows us to simultaneously focus on cutting-edge research, manage portfolios and serve our clients from all corners of the world.
Our well-resourced team is experienced and diversified in terms of academic, career and personal backgrounds. We also actively look to recruit top talent as this helps ensure a culture of independent thinking and innovation.
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Weili Zhou
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David Blitz
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Wilma de Groot
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Patrick Houweling
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Pim van Vliet
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Mike Chen
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Harald Lohre
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Jan de Koning
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Integrating sustainability
Given our institutional knowledge in the areas of quantitative and sustainable investing, we are well positioned to design and manage sustainable quantitative solutions. The rules-based and systematic nature of our investment processes makes them well equipped to integrate various sustainability dimensions.
As such, we can explore and implement various ways of combining multiple sustainability preferences with financial objectives for our clients. We acknowledge that investors might have differing beliefs and values. Our platform is suitable for the development of customized portfolios. Beyond integration, our engagement and voting activities can play a role in reshaping corporate agendas towards more sustainable practices.
Tailoring solutions to your needs
To cater to your specific needs, we offer a wide variety of quantitative equity, fixed income and multi-asset solutions that range from factor-based (equity, fixed income), to dynamic market-timing (fixed income), to sustainability-focused (equity, fixed income) portfolios. These solutions are underpinned by our proprietary inputs that set us apart from other quantitative managers.
We rely on our enhanced factor definitions which mitigate unrewarded risks and result in superior risk-adjusted performance compared to generic factor definitions. Our proprietary portfolio construction algorithms give us full oversight of the process versus off-the-shelf optimization tools which tend to resemble a 'black box'. Moreover, our algorithms help us aim to avoid unnecessary trading costs, resulting in lower turnovers and better after-cost returns in the long term.
View our Quant strategies