The term “quantamental” has been increasingly used to describe the convergence of fundamental and systematic investing. Driven by the explosion in data over the last decade, open source compute and the continual search for alpha, our portfolio managers and their analysts are blending the best elements of these two distinct approaches to help deliver consistent returns to our investors.
Historically, portfolio managers and their teams mine troves of data to hone their deep company and industry knowledge. They become experts on the drivers and KPIs of companies within their portfolio and leverage that expertise to formulate profitable investment theses. Quantitative investors, in turn, exploit a variety of individual anomalies, or alphas, which are then blended to form a portfolio. These statistical anomalies rely on the law of large numbers to build their strategies. Unlike fundamental analysts, quants may not know individual company names, and they may not typically look at data with a short history.
Our version of ‘quantamental’ investing centers on applying fundamental expertise to analyze data where it matters most. Our teams define an investment thesis and work with the firm’s Data Intelligence Group to identify potential datasets to test and analyze the thesis. These datasets are then cleaned, normalized and evaluated by the investment and data teams through a variety of systematic frameworks. This combinatory approach increases a PM’s ability to confirm and express a trading idea, while minimizing any negative biases.
The rapid expansion and evolution of data has driven much of this change. In the 1980s and early 1990s, company and market data providing technical company information was available via vendors and exchanges. In the late 90s, the velocity of data began to increase exponentially – high frequency trading and automation drove major expansions in technology and engineering. Today’s battle lines are drawn at the intersection of machine learning, artificial intelligence and big data.
Over the last three years BAM has transformed our approach to data science and engineering to support this quantamental evolution. Our Data Intelligence Group, a centralized team supporting all of our investment strategies, was built to give our PMs a competitive advantage in data. We have also invested heavily in building new tools and technologies for data exploration and are one of the first firms to establish a Chief Data Officer position to oversee these efforts. The result is that our PMs are able to gather and process more proprietary data than ever before.
Another key to accelerating BAM’s quantamental success are our Sector Data Analysts. Dedicated to one or two specific sectors, these translators help long / short equity teams evaluate, analyze and systematize company and industry data, bridging the gap between quantitative and fundamental investing. Indeed, fundamental investment teams are increasingly hiring data analysts, or leveraging the capabilities of their internal data intelligence groups, to harness the power of the vast amounts of alternative data and turbo charge their research and analysis.
Our success in quantamental is rooted in data and technology, but it’s the collaborative culture that we foster at our firm, which has led to our greatest outcomes. When it works, quantamental investing gives portfolio managers a competitive edge that can’t be captured using just one approach.
