By the time most investors closed the book on 2015, many had become familiarized with the FANG acronym, which singled out the four technology bellwether stocks — Facebook, Amazon, Netflix and Google — that drove much of the market's growth last year.
With a full quarter now in the books and only Facebook still riding last year's momentum, it has already become clear that if the market is going to climb again in 2016, it won't necessarily be on the back of these four names.
In fact, as the drivers for growth become less obvious and the market assumes a more volatile posture, many investors are again adopting a far more expansive scope in their hunt for alpha, as they realize these types of markets often favor a systematic strategy that can uncover either value or momentum in the areas overlooked amid the flight to safety.
Even in last year's FANG market, the reality is that within the MSCI ACWI IMI Index, there were 2,067 stocks that posted a higher total return than Facebook, 1,398 stocks higher than Google, 251 higher than Amazon and 180 higher than Netflix over the same 12-month period. Of course, the number of stocks to choose from expands when investors are not limited to an index's constituents.
While this illustrates the opportunity set available to unconstrained global investment managers, the challenge, of course, is in actually picking the winners, not identifying them after the fact. And this is where the "quantamental" approach tilts the playing field in favor of those with exposure to an extensive and far-reaching universe of stocks and a process that marries both quantitative and fundamental analysis to identify the most appealing opportunities.
Quant investing, for the uninitiated, utilizes mathematical prediction models to filter out certain stocks aligned to a given strategy, with a typical bias toward company fundamentals as opposed to corporate developments or company news.
As a result, press releases, earnings calls or management meetings will always take a backseat to the raw data — be it measures of market cap, profitability, valuation, volatility or momentum — all of which feed into factor-driven quant strategies.
The benefit of a quant model is that it turns a seemingly limitless investment universe into a manageable pool of potential "buy" candidates, while eliminating the noise due to behavioral sentiment that can often lead to poor investment decisions.
Moreover, quant models can quickly identify market inefficiencies and, with supporting data, offer the conviction required to invest in out-of-favor areas that may offer the most potential upside.
"Quantitative analysis coupled with this fundamental underpinning broadens an investor's universe ... to 15,000 investable options. In a FANG market, this may not matter, but in 2016 and beyond, investors will clearly benefit from breadth."
These models will often turn up investment ideas that go against conventional wisdom but make sense given the supporting data. Real estate investment trusts in Sweden, Finland and Denmark, for instance, would seem counterintuitive, given the negative interest rates in Europe, but the data tells a different story.
Swiss office REIT PSP Swiss Property AG, for instance, since hitting its 52-week low last June, has climbed nearly 20 percent as of mid-April. Decelerating growth in China has also scared off many global investors over the past six months, yet our model is currently recognizing the relative stability and attractive growth profile of toll-road operators in the country.
While investors can certainly recognize the benefits of a systematic approach, in many circles quant strategies have taken on the specter of a closely guarded family secret.
A Reuters story in 2012, for instance, called attention to BlackRock's editorial decision to alter its prospectus for its Large Cap Series funds. The firm formerly attributed its investing strategy to a "multifactor quantitative model" but replaced this characterization to instead credit "third-party research firms."
Many other fund managers go out of their way to downplay the role of quantitative analysis, using watchwords such as "analytical," "repeatable" or "well-defined" to discuss their processes, with no mention at all of quant investing. Perhaps they recognize the "algorithm aversion" that David Siegel gave voice to in an editorial in the Financial Times last year.
To be sure, the Quant Meltdown of August 2007 brought to light many of the largest criticisms around quant strategies, particularly the white-labeled, third-party models that may lend themselves to the creation of similarly constructed portfolios across the industry.
Researchers Amir Khandani and Andrew Lo of MIT Sloan School of Management, in the school's Laboratory for Financial Engineering, highlighted in a research paper the potential for systemic risk through recreating a simulation that attributed the 2007 August unwind to long/short equity portfolios using five specific valuation factors.
If anything, though, this speaks to the necessity of a proprietary model and the continual refinement needed to drive uncorrelated quant strategies. It also underscores why human intervention and in-depth fundamental research are so critical to long-term performance.
Most quant strategies will establish composite scores to winnow down the investable universe to a subset of the most appealing stocks, based on the available data. From there the "quantamental" investor will go one step further and dig into the company fundamental and macroeconomic data in order to really understand the business, economy and the potential catalysts or risks that may exist.
If an investor is also "benchmark aware," that provides guardrails when investing in small caps, frontier markets or other segments. Even if a quant investor has conviction in their model, the addition of fundamental analysis and human intervention permits them to override areas of the market that may be trading irrationally (think energy in late 2015 or Brazilian equities in January).
They can also gain a better grasp of the implications of corporate actions or fine-tune the diversification of the portfolio to ensure we're not overexposed directly or indirectly to any one market, area or theme.
However, quantitative analysis, coupled with this fundamental underpinning, broadens an investor's universe from a couple of hundred stocks to 15,000 investable options. In a FANG market, this may not matter, but in 2016 and beyond, investors will clearly benefit from breadth.
Arthur C. Clarke, in his 1982 sequel to "2001: A Spacy Odyssey," wrote that "whether we are based on carbon or on silicon makes no fundamental difference; we should each be treated with appropriate respect." More than 30 years after Clarke published his fictional account of the future, we would agree that today the two go hand in hand.
— By Ram G. Gandikota, principal, senior portfolio manager and associate director of research at Ativo Capital Management
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