What inspired you to enter the field of quant investing?
“I got into quant investing probably due to a mixture of inclination and skill, but also because of many fortunate coincidences. When I was very young, my father switched professions, from being a math professor to becoming an early adopter of quant investing. Hence, I grew up with that notion from an early age. Later, I was therefore naturally lured into studying mathematical finance at the University of Konstanz.”
“Importantly, I was part of the first group of students to study this course. As a result, I had a close connection with the finance faculty and developed a liking for academic rigor. But I also realized that I was genuinely motivated whenever I saw the practical relevance of the academic problems we had to solve. Thus, the desire to seize the best of both worlds in terms of investment theory and portfolio management ultimately put me on the path to quant investing.”
Why did you decide to join Robeco?
“Given my career path in academia and asset management, I have always had an affinity with research and have encouraged my younger colleagues to follow a similar route to achieve personal and professional growth. This is reflected in my connection with Lancaster University, where I co-supervise a group of PhD students. Therefore, I was naturally attracted by Robeco as an organization that puts research first.”
“The opportunity to join Robeco’s group of like-minded investment professionals is a treat, and it broadens the opportunity set for joint academic ventures and will have positive spillover effects for the PhD collaborations. Robeco is a household name in quant investing. This boils down to it having a highly-functioning team of quant investment professionals, who are focused on nurturing a strong research culture. This was a key feature for me, as our shared beliefs made it a natural move.”
What type of culture generates the best research?
“Culture is key. And that’s not just in research. If we think about the quality of our products and services, these are crucially driven by the quality of our research. Therefore, it is important to embrace a research culture that rewards high-quality research. Meritocracy is central to this, as the best ideas should always win, regardless of who proposes them. For this to happen, a safe environment that offers everyone an opportunity to engage and speak up is key.”
“With regard to quant investing, the problems we are trying to solve have become quite complex, and often call for collaboration across disciplines. In this sense, quant investing is very much a team sport, in fact more so than ever. In my view, you need a sense of togetherness, where everyone is accountable for making a difference. In terms of actual research, you need to follow a strong research protocol, especially if you want to separate sheep from goat factors in an ever-expanding zoo of factors.”
What is your favorite factor?
“Being a father of four, there can only be one answer: you have to love them all. But jokes aside, one should avoid such favoritism from an investment perspective too. All factors come with strengths and weaknesses. And these can play out at different times throughout the cycle. Yet, given how challenging it is to predict the latter, a diversified approach to factor investing is a prudent choice.”
緊貼荷寶量化投資
獲取荷寶的電郵月報及最新觀點報告,構建最綠色的投資組合。
What is a relevant academic paper you have recently read?
“The paper1 that comes to mind looks at navigating the factor zoo, with and without transaction cost considerations. This is very much in line with our objective. Translating factors into portfolios comes with costs and frictions, and this paper analyzes how much portfolio decisions differ when costs are either considered or not considered. The researchers use a parametric portfolio policy framework to evaluate these choices and trade-offs against investor utility.”
“I believe this is a meaningful perspective, as it does not just focus on what returns are attached to a given factor, but also on how this ultimately translates into investor utility, and what factors an investor will choose in light of the transaction costs. It turns out that an investor would actually choose significantly more factors if transaction costs are taken into consideration. This sheds some light on the underlying trading cost diversification investors can benefit from if they have exposure to more factors in their portfolio.”
What lessons have you drawn from the recent quant winter of 2018-2020?
“The quant winter was a very humbling event for me. It was an extremely difficult period as many of our key beliefs were truly tested given the protracted nature of the phase. Specifically, we construct portfolios based on certain factor characteristics that we deem relevant over the long run, leading to diversified portfolios. However, over this period, the winning strategy was represented by a few growth stocks that would, in turn, result in more concentrated market indices. As a result, our investment paradigm was temporarily turned upside down.”
“Yet, further down the road, we have now seen the resurrection of value and other factor premia, confirming our long-held investment rationale. Ultimately, this provides a good lesson about sticking to your investment philosophy. And while it has been the right thing to do, it was a true test of character. Of course, it is vital to regularly question your approach and to leave no stone unturned. But one must refrain from overreacting. A strong research culture enables you to stay true to your investment philosophy in such difficult periods and to communicate your approach accordingly so as to keep focused on the long-term perspective.”
How do you see the future of quant investing?
“I believe the future of quant is bright. Investing is all about processing information into portfolio decisions. In this era of burgeoning novel data sources, it is more important than ever to carefully look for genuine signals. But this is exactly what quant investing has been about since the start. If you think about recent advances in computing power, methodology, machine learning and natural language processing, they have all progressed in lockstep with the increase in data availability. These advances ultimately enable quant investors to tap such data sources to develop a deeper understanding of markets, thus helping us to keep our investment proposition relevant.”
“But turning investment theory into practice is tough. If you scour the academic literature, you tend to mostly learn about the good things that seem to work. For us, it is always a question of whether it really works in practice. Given positive publication bias, we often have sobering outcomes on this front. But ultimately, our job is to separate the wheat from the chaff and to distinguish between what really adds value and what does not. Again, this all falls back on having a strong research culture and a robust process. I look forward to navigating this sea of information alongside my new colleagues at Robeco.”
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