Big data: How to get quality from quantity

The ins and outs of utilizing data to improve investment outcomes of both quantitative and fundamental managers in the digital age

For many in the financial community, big data has become synonymous with quantitative investing and quantitative investing alone. Who, after all, is better equipped to handle the growing reams of information now available at the push of a button or swipe of a screen than those who base their investment decisions on facts and figures, selected and sorted by powerful computer models?

But as the influence of big data on “quants” has continued to grow, so too has its pull on fundamental managers seeking new ways of assessing opportunities and mitigating risk. 

As a result, the silos that once separated and created friction between these two styles of investment management are now being torn down to create a shared intelligence, utilizing the proliferation of data more efficiently in all of its various forms.

Members of AGF’s quantitative and fundamental investment teams sat down recently to discuss these collaborative efforts and also how they use and share data to improve their own unique investment processes.

Why is data becoming more important to investment management?

Stephen Way: Data simplifies our investable universe and has helped us create a more disciplined, systematic process over the years. The key is how you analyse the data and the judgement you apply to it.

Mark Stacey: What’s most important is the story within the data that tells us how companies are doing. To make thoughtful decisions, you need to be able to harness this information.

Stephen Duench: I think you could make a strong case that there is nothing more important in investment analysis than data. In the last few decades the breadth of data in investment management has gone parabolic and only in the last few years have we reasonably started to understand its importance to a more robust investment process.

How has data changed your job?

Rune Sollihaug: Data has become more granular, and there is now more focus on shorter term data. In the past, there was very little focus on factor exposures, for instance. Systems have become more sophisticated as well, resulting in the benefit of more detailed reports.

MS: More and better data now provides so many different perspectives on the market beyond traditional financial statement analysis.

SW: We’ve been using data related to factors to inform our country allocation since 1995, but back then we relied solely on a third party provider. Now we get a lot of it from Mark’s quantitative team and we have more ways to slice it to come up with new approaches.

SD: Having built my entire career on the quantitative side of investment management, I’ve always had a strong respect for the power of data, and also the importance of having quality data. The better it is the more trust there is in our analysis.

Does utilizing data represent any specific challenges for asset managers?

RS: Both accuracy and getting timely data are crucial. Without a proper quality assurance process in place there is a risk that the data quality could end up being poor.

MS: Whether it’s financial statements or an earnings call transcript, it’s crucial to get the right data source. You also have to be able to understand the data, “scrub” it, organize it and maintain it. It’s easy to become overloaded with too much data if you don’t have a proper process for handling it in place.

SW: Figuring out what is not worth knowing is just as critical. Otherwise, you can spend months crunching data in a so-called analysis paralysis.

SD: For those managers utilizing third-party sources of data, the biggest challenge is trust, and I’m unsure one can fully trust a source they don’t initially create. As the industry becomes more and more quantitatively inclined, sourcing and building the data internally is the only way to achieve legitimate trust with the data.