How quant techniques are transforming fundamental investing

This blog is a summary of a panel discussion held during CFA Society New York's Fintech Week, featuring Kim Shannon - President Sionna Investment Partners; Nelson Yu - CIO Investment Sciences, Alliance Bernstein; Neudata; Amy Dafnis - Sr. Analyst, Neudata; Rodney Pedersen - Chief Revenue Officer, Visible Alpha

Technology is driving an unprecedented rate of change in asset management, and no part of the industry is immune. This panel discussed how it’s transforming fundamental investing and how the tools and techniques historically used only in quantitative investing are increasingly being integrated into fundamental investing.

It all starts with data. There has been an order-of-magnitude increase in the amount of data available to fundamental asset managers. Whether it’s screen scraping airline seating patterns, using satellite data to count cars in parking lots or analyzing bulk credit card transactions, the “alternative” data sources offer myriad opportunities to identify investable events – if asset managers know how to use them.

Fundamental asset managers are plugging quantitative techniques into their process in a variety of ways. Some examples include:

• Industry trends: Gone are the days when analysts relied on issuers for data about their target markets. Now analysts are expected to have things like demographics surrounding retail store footprints.
• Surveillance: Alternative data can provide signals of inflection points in market demand, particularly when sources are combined to identify changing correlations.
• Cluster analysis: Quantitative techniques can be a great way to compare firms of different types in response to an event (eg. Pandemic winners and losers).
• Risk analysis: Stock-picking can often have unintended risk consequences at a portfolio level that quantitative techniques are well suited to identify.

Firms need to be intentional about combining quantitative and fundamental investing processes. You can’t just throw data at the problem and magically get an answer. You need some prior knowledge and a starting point. Also, data sets vary by industry so the domain expertise and contextual knowledge of fundamental analysts needs to guide data sourcing and analysis. It’s important to be clear on what questions you want to ask to identify which parts of a data set are relevant. Portfolio Managers who have a strong understanding of their process are better positioned to embrace quant techniques because they understand what gaps need to be filled; when they ask a question of the data, they know what they’re going to do with the answer.

As often happens with industry innovation, regulation has lagged in the alt data space – but it’s catching up quickly. In particular, privacy regulation is shaping the landscape because so much alt data is created from the digital exhaust created by other industries. For example, Google and Apple are modifying how they collect location data, and this is changing attributes of the data itself. Analysts need to understand these nuances to use the data effectively.

Combining fundamental and quantitative techniques can be a powerful enhancement to the asset management firm; however, doing so requires culture change in both disciplines. Quants bring statistical rigor, automation, speed and the ability to work with large data sets. Fundamental analysis brings domain expertise and contextual knowledge to assess how the future might differ from the past. Investment decisions are enhanced by bringing the two together, but it’s a big change for both. Like most other changes, success requires well functioning, cross-functional teams that collaborate well. The best way to start is to walk before you try to run; start small, find tangible successes, and build as you go.