Quality from quantity

By: Rune Sollihaug, Mark Stacey and Stephen Way • December 12, 2018

Members of our fundamental, quantitative and risk management teams discuss the ins and outs of utilizing data to improve investment outcomes in the digital age.

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 analyze 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.

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.

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.


Source: Wikipedia, “Size of Wikipedia”, October 1, 2018 and AGFiQ Analytics


What data sources do you use/trust?

RS: There are no data sources that I trust 100%. Those I trust most have a solid quality assurance process in place in order to scrub and validate the data.

MS: Trust can become a bit of an issue when you get into Artificial Intelligence (AI) and unstructured data that is being scraped from the Internet. As data moves away from just financial statement analysis, it’s important to note whether the information is audited or self-reported as it tends to be in a lot of environmental, social and governance (ESG) factor data.

SW: Because ESG scores are put together by third parties from a culmination of data, you never know if they are misinterpreting the information unless you do the fundamental analysis and identify the key issues yourself. So, it’s important to triangulate and validate through multiple sources.

Is harnessing proprietary data important?

MS: It’s more the way you use the data that’s important. For our quant team, that means making sure all the inputs for the models we build are proprietary as well as the models themselves. That way, we understand them and are not relying on someone else if something goes wrong.

RS: If you have data or models that give you a competitive advantage, it would certainly be beneficial.

How does a quant use data differently than a fundamental manager? How can they learn from each other?

SW: From a fundamental perspective, we use the quantitative data to help us narrow the universe of stocks down from around 600 names to something more manageable. We can also use data to help capture “red flags” in our investment thesis, allowing us to prioritize our attention to potential risks that fundamental analysis, by itself, might have been slow to recognize.

MS: As quants, we’re analyzing many of the same things that Steve does, like discounted cash flow, for example. But we do it differently. Our heavy lifting is up front when we are creating our models based on the data. Steve’s heavy lifting is after the data has helped him narrow down his universe.

RS: I believe both should be used in both processes, the question is to what degree.

How does data help from a risk management perspective?

RS: It’s become crucial for someone like me who is helping manage risk across a number of strategies. But it has to be accurate. Even small variances in input data can cause significant inaccuracies in any report.

SW: Data is becoming a key enabler of risk management. It provides key insights in terms of active risk contribution, correlations with the rest of the portfolio and scenario analysis.

MS: Data is helping us learn far more about the contributors to risk in a portfolio. Because of that, we are able to identify and get the exposures we want, but also control the exposures we don’t want.

SW: I’m not sure terms like active risk and tracking error were even in my parlance 10 years ago. The bar has been raised and it’s now expected you’ll use this data to help understand, manage and communicate the various risk exposures in your portfolio.

AGFiQ Asset Management (AGFiQ) is a collaboration of investment professionals from Highstreet Asset Management Inc. (HSAM), a Canadian registered portfolio manager, and of FFCM, LLC (FFCM), a U.S. registered adviser. This collaboration makes up the quantitative investment team.

Commentaries contained herein are provided as a general source of information based on information available as of December 7, 2018 and should not be considered as personal investment advice or an offer or solicitation to buy and/or sell securities. Every effort has been made to ensure accuracy in these commentaries at the time of publication; however, accuracy cannot be guaranteed. Market conditions may change and the manager accepts no responsibility for individual investment decisions arising from the use of or reliance on the information contained herein. Investors are expected to obtain professional investment advice.

AGF Investments is a group of wholly owned subsidiaries of AGF Management Limited, a Canadian reporting issuer. The subsidiaries included in AGF Investments are AGF Investments Inc. (AGFI), Highstreet Asset Management Inc. (Highstreet), AGF Investments America Inc. (AGFA), AGF Asset Management (Asia) Limited (AGF AM Asia) and AGF International Advisors Company Limited (AGFIA). AGFA is a registered advisor in the U.S. AGFI and Highstreet are registered as portfolio managers across Canadian securities commissions. AGFIA is regulated by the Central Bank of Ireland and registered with the Australian Securities & Investments Commission. AGF AM Asia is registered as a portfolio manager in Singapore. The subsidiaries that form AGF Investments manage a variety of mandates comprised of equity, fixed income and balanced assets.

Publication date: December 12, 2018

Our website uses cookies to help you get the best experience. Please Accept or click Edit to control your settings.