The financial gurus who say investing in the stock market is equal parts art and science may need to rethink that.
Certainly, successfully buying and selling securities still requires a strong “feel” for companies and markets — a skill often considered art. But in the digital era, science — or rather scientific analysis of massive amounts of data — is an increasingly critical investment tool, says Ryan LaFond, Ph.D., head of research for the Asia Pacific and Emerging Markets Equity group within the Scientific Active Equity group at BlackRock, an investment company.
Seek and scrutinize
In our modern, hyperconnected world, have research reports, corporate earnings calls and Securities and Exchange Commission filings — the traditional sources of investment information — disappeared? The answer is no. But investors who choose not to look beyond those resources “may be severely limiting their ability to invest successfully,” LaFond says.
“How we do investment research at BlackRock has changed in a fundamental way,” he says. “We still ask the same basic questions we always have: Is the stock attractively priced? Will the business continue to generate cash flow? But the volume and types of data we need to consider have increased significantly.” Some might even say astronomically. (For more, see the infographics on these pages.)
Algorithms, all the time
“One of the main search tools financial analysts use today is the algorithm, which is basically a custom-designed computer program,” says Benjamin Blaisdell, an executive in the Investment Solutions Group at U.S. Trust. “An ‘algo’ can scan terabytes of data quickly. That can mean thousands of research reports a day, web searches in real time, even public messages on services such as Twitter.”
Adds LaFond: “This information might tell us something about a company’s future sales, national shopping trends, the strength of the economy and much more.”
Algos can sometimes flag less quantifiable, more veiled, elements. For example, says LaFond, “we’ve noticed that research analysts seem to post notes in a rush, after meeting with a company’s management. These notes are typically limited to brief textual analysis and rarely, if ever, include formal changes to EPS forecasts or stock recommendations.”
Those kinds of changes require considerably more analysis “and usually appear long after the initial note has been published,” he adds. But by using an algorithm that basically lets a computer read the text, “we can often capture the sentiment revealed in the note,” LaFond says. “This sentiment can sometimes help us predict where the analyst’s EPS forecasts or recommendations might move over the next several months.” It’s this kind of analysis that, when accurate, can put a company slightly ahead of the pack.
From pile to edge
Algorithms may not be the be-all and end-all, but with the global volume of digital data mushrooming they can often help investors make decisions more quickly and accurately than ever before. In a sense, LaFond says, “the future of asset management is being able to access and process these piles and piles of information. It’s one of the ways we think will help us gain an edge in an increasingly competitive environment.”
For more information on BlackRock’s Scientific Active Equity strategy, contact your U.S. Trust advisor.
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OTHER IMPORTANT INFORMATION
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Technology stocks may be more volatile than stocks in other sectors.
International International investing involves special risks, including foreign taxation, currency risks, risks associated with possible differences in financial standards, and other risks associated with future political and economic developments. Investing in emerging markets may involve greater risks than investing in more developed countries. In addition, concentration of investments in a single region may result in greater volatility.