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Oct. 29, 2018, 8:23 a.m. EDT

The next frontier in investing is ‘quantamental’ stock picking

A merger of computing power and human expertise is lowering costs and increasing gains

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By William Watts

Peter Grundy

The quantitative analyst and the fundamental stock picker, from different worlds and often working on separate floors, are increasingly putting their heads together to produce better results for investors.

That’s why the term “quantamental,” a blend of the two styles, may soon become common parlance among ordinary investors.

“There’s a very important synergy that is not hard to recognize coming from the quant perspective and coming from the fundamental perspective,” said Savita Subramanian, head of U.S. equity and quantitative strategy at Bank of America Merrill Lynch in New York.

Buffett vs. Simons

Fundamental investors track corporate earnings, balance sheets, industry trends, the economy and other sources of information to make informed investment decisions. Billionaires Warren Buffett and Charlie Munger of Berkshire Hathaway /zigman2/quotes/200060694/composite BRK.B -0.29% epitomize the midnight-oil-burning fundamental approach, with their focus on the ins and outs of a corporate balance sheet combined with their application of common-sense judgment. The finance world has worked that way for decades.

Quantitative analysis, on the other hand, uses mathematical and statistical modeling that pulls in a sometimes-dizzying array of inputs to screen investment ideas. The rising popularity of quantamental investing reflects advances on the quantitative front. Pioneering quant-focused hedge-fund managers, such as Renaissance Technologies’ James Simons, are more famous than ever, at least in the financial world. Colleges are even offering courses of study, such as the Hoboken, N.J.-based Stevens Institute of Technology’s bachelor’s degree in quantitative finance .

Quantitative hedge funds will soon top $1 trillion: They had $967 billion in assets under management as of the second quarter, roughly double the figure in 2010, according to Hedge Fund Research in Chicago. The number of quant-oriented hedge funds recently surpassed 2,000.

At the same time, fundamental stock pickers are under pressure from low-cost, passive, index-tracking strategies that have capitalized on the inability of the majority of active managers to beat their benchmarks in the long run. Data from New York-based S&P Dow Jones Indices, for example, found that nearly 97% of active, large-cap equity mutual funds underperformed their benchmark, after fees, in the five years through 2017.

Meeting of the minds

But now a growing number of fundamental money managers who had relied on traditional research to make investment decisions are beginning to incorporate computer-based methods that use algorithms to sift through reams of often arcane data in search of trading signals. Still, they’re not scrapping fundamental analysis, which relies on expertise and human judgment to add value.

Long-only, active managers with $680 billion in assets under management use a blend of quantitative and fundamental analysis, more than double that of a decade ago, according to data-analytics company eVestment in Atlanta. (“Long” refers to a bet on rising securities prices; “short,” the opposite.) Among high-profile investors, New York-based fund manager BlackRock /zigman2/quotes/207946232/composite BLK +0.04% in 2017 announced it was moving $30 billion in assets to strategies that would rely on more computers and fewer humans.

The combination makes sense, proponents say, because quants scour data such as forecasts for sales and corporate earnings or macroeconomic reports looking for anomalies. They need that data, produced by fundamental analysts who know their companies and sectors well, for their analysis. Fundamental analysts, meanwhile, can benefit from the clinical approach taken by the quants.

“Experience has taught me that if you look at even the most fundamentally oriented fund managers, they have a need for systematic output that shields them from being emotionally attached to particular investment ideas,” said Brian Cho, the head of quantitative research at Chiron Investment Management, a New York money-management firm that uses quantamental techniques.

‘Alpha surprise’

An example of the quantamental approach is offered by Bank of America Merrill Lynch’s “alpha surprise” model, which applies a quantitative overlay to forecasts by the firm’s fundamental analysts. The strategy has beaten the benchmark S&P 500 Index /zigman2/quotes/210599714/realtime SPX +0.50% in 23 of the past 30 years, Bank of America’s Subramanian said.

Fundamental analysts “fly around and visit the companies and talk to management and analyze the nitty-gritty,” she said. “Then we say, ‘OK, removing the emotion around the buy or sell decision, what stocks from this disciplined screening framework look like the highest-conviction picks from our fundamental team?’ ”

Data on the alpha surprise model go back to 1986, underlining the fact that the blending of quantitative and fundamental analysis isn’t brand new. But it’s just one way that the average investor can now use a growing toolbox of quantitative techniques. Analysts say the past decade in particular, with the advent of big data and the computer power to rapidly crunch a variety of data sets relatively cheaply, has helped drive interest in quant strategies.

“I don’t see a real fine line between fundamental and quant — it’s a spectrum,” said Dan Culloton, director of equity strategies at the Chicago investment-research firm Morningstar. “Every quant model begins with a fundamental decision about what factors to include.”

Competition from passive products

Meanwhile, a number of drivers are contributing to the growth of quantamental investing.

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