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Quantitative investing with a simple formula

Quantitative investing with a simple formula

09-05-2018 | インタビュー

Quantitative investing should be easy to understand. In a new research paper,1 Pim van Vliet and David Blitz explain how a simple investment formula based on three variables (the Conservative Formula) can outperform the market by a wide margin in the long run. Does this mean that all investors should set up their own low volatility strategies? Not necessarily.

  • Pim  van Vliet, PhD
    Pim
    van Vliet, PhD
    Head of Conservative Equities and Quant Allocation
  • Quant investing can be explained in an accessible way
  • Actual implementation remains a challenge
  • Naïve quant strategies are often suboptimal

How did the idea for this paper develop? What was your goal?

“Last year, I co-wrote a book on low-risk investing with my colleague Jan de Koning2, which introduced this simple investment formula based on three variables: volatility, payout yield, and share-price momentum. The book was intended for a broad audience and presented the main results in a very accessible way.

“Since then, however, I have felt the need to dig deeper into the robustness of the formula, to check if it passes all the hurdles and tests that are usually applied to rigorous academic research. And that is what this paper is really about. In a way, it can be considered a follow-up to the book, but also a kind of teaser for those who haven’t read it yet. The paper has in fact enjoyed great popularity since we posted it on SSRN3 last month.”

“For those who have already read the book and are looking for more in-depth analysis, this paper provides more detailed evidence based on a slightly longer data series. At the same time, the paper may encourage other investors who don’t know about the book to read it and become more familiar with low volatility investing and how we approach this at Robeco.”

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Does that mean low volatility investing boils down to something that can be done at home with a simple spreadsheet?

“If you really bring it down to the basics, yes: it can be done very easily at home. If you read all the existing academic literature and listen to the debates around factor-based investing, you might think: ‘Wow, I’m lost’. So, our objective is to bring things down to the essentials: three key ingredients that lead to positive exposure to well-vetted factor premiums.”

How does this paper fit with your role as a professional portfolio manager?

“I often say that we should sell ‘quant’ to ‘non-quants’. Robeco is a well-respected ‘quant’ house, but the quantitative investment market remains a niche. So, as a professional asset manager, if you can explain in a very simple and accessible way what quantitative investing is about and people understand it, you can aim for a much bigger market. Some investors may choose to do it themselves, but the vast majority won’t.”

“The reason is that the devil is in the details: execution is key and the actual implementation of quantitative strategies can be quite demanding in terms of resources. You need to consider issues such as how to implement your positions in practice, how often you need to rebalance your portfolio, how to minimize turnover, how to manage investment flows and how to deal with transaction costs.”

“So, we are not revealing our secret ingredients by explaining this simple investment formula. We are simply sharing three of the variables that we take into account in our models and showing that the combination of these three elements is very powerful. We are also showing potential clients that they could actually do it themselves, if they want.”

“This is very important because it is the level of understanding that we would like our prospects to have. We want to make sure they understand what we do and our investment philosophy. But we also want them to recognize that execution is key and that there are some implementation issues that they can delegate to Robeco.”

“Our ultimate goal is to promote quantitative investing, in particular factor-based defensive investing. We want to show as large an audience as possible that this empirically-tested way of investing can be easily understood and that Robeco is good at translating scientific insights into simple and reliable solutions. The paper and the book are just another way to get this message across.”

OK. But don’t you run the risk of over-simplifying your message and driving investors towards cheap generic smart beta products?

“I don’t think so. As I said, the devil is in the details: implementation and execution remain crucial. Many empirical studies, including some carried out by Robeco’s Quantitative Research team4, show that naïve low volatility strategies, frequently offered through low-cost ETFs, and the more sophisticated ones, such as Conservative Equites, do not lead to the same investment results.”

“For example, one common pitfall of low volatility ETFs is that they are too transparent, because they are often based on publicly available indices. All market participants know which trades are going to be executed and some investors can take advantage of this. Once people see the pitfalls of generic low volatility investing, they naturally turn towards active asset managers such as Robeco, who address all of these issues.”

“The paper and the book were not designed as sales material for Robeco products, but they can be considered part of our overall knowledge-sharing effort. And we have tried to do this in a very balanced way, giving the reader an overview of the different options available, from the ‘do-it-yourself’ approach to the sophisticated actively-managed funds. I see this as a sign of strength: we’re confident enough about our position in this market.”

1 P. van Vliet and D. Blitz, The Conservative Formula: Quantitative Investing Made Easy, March 2018.

2 P. van Vliet and J. de Koning, High Returns from Low Risk, Wiley, December 2016.

3 The Social Science Research Network (SSRN) is an online platform dedicated to the dissemination of academic research.

4 See for example: D. Blitz, ‘Factor Investing with Smart Beta Indices’, 2016

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