When Big Data Meets Big Finance
Cal State East Bay research connects search trends to stock prices — the result is good news for amateur investors
Obi-Wan Kenobi, Donald Trump, Tesla. Any Google search term pops up instant information on your screen. But behind the screen, all search terms are saved anonymously, counted, ranked and publicly shared on Google Trends for anyone looking for patterns in consumer interests. More commonly known as “big data,” the aggregation of large quantities of statistical information is widely accessible and has near limitless applications in understanding what humans are curious about — including financial investments.
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Big data has long been used in the financial realm to track gold prices, IPOs, Bitcoin and more. But one of the early researchers to study big data in the stock market is Eric Fricke, interim associate dean of the College of Business and Economics, and a professor in Cal State East Bay’s Department of Accounting and Finance.
“The availability of [big data] information has made it harder for hedge funds and other professional investors to get an edge [over individual investors],” Fricke says. “Investors are constantly looking for more information and markets have become more competitive as a result. The bottom line is that the availability of information is making it more difficult for the professional investor to gain an edge over the amateur investor.”
In a series of academic research papers, Fricke and fellow Cal State East Bay finance scholars Professor Scott Fung and Associate Professor Sinan Goktan are studying not only how small investors can benefit from big data, but how Google searches for a company’s earnings affect the price of its stock. Although one publication found that the high-end tools of professional investors still yield better information and returns for clients, Fricke says the gap is narrowing for everyday people who want to make informed decisions on their own — it’s getting harder for hedge funds to maintain their edge.
“This is not a get-rich quick scheme,” Fricke says. “What we’re finding is that the availability of information is making markets more efficient — it’s very difficult to beat the market and make returns higher than average. Historically, the best way to do that was to turn over your money to a big investment company that could offer insights into market behavior, but the internet has given people the ability to make educated investment decisions on their own.”
The capacity to study trends and make sense of them is an evolving tool of financial strategy that Cal State East Bay students are also learning from. Alumnus Gary Tsan helped Fricke, Fung and Goktan with their research during his time as an undergraduate.
“The research we did was fascinating,” Tsan says. “When you search Bitcoin or Ethereum (an alternative digital currency) on Google Trends, you can actually see how search history correlates to the price of [each stock]. I’ve used the information myself to make a few bucks.”
Although he was already eyeing a doctoral degree, the research experience inspired Tsan to continue his education at Cal State East Bay.
“I’ve always been interested in financial markets and … in the future, everything is data,” he says. “[Dr. Fricke] taught me a lot about how to do research and how different it is than just reading a paper — he taught me the process of research, how I should approach it, and how to collect and clean and interpret data. After I finished [the project] I wanted to know more about big data and it’s why I pursued my master’s degree in statistics.”
Building upon that experience, Tsan, who now works as a business analyst and leverages data each day to craft marketing solutions, is studying for the GRE and looking into Ph.D. programs.
“I will be studying to be an actuary,” he says, “but I do think I’ll continue to work with big data and focus on the financial track.”
For Fricke, it’s a win-win no matter whether his students delve straight into the world of money markets, contribute to scholarly research or journey into other possibilities entirely.
“Data informs every job and I want our students to understand its endless applications,” he says. “In finance specifically, students being able to apply these mass quantities of new information that are available via the internet, and to understand what people are interested in and how that affects markets is definitely going to be useful in the future.”
Big Data and You
Historically, when a company’s quarterly earnings announcement contains a “surprise” — unexpected losses or gains — the stock of that company not only drops or rises immediately but also in the months that follow. Hence, buying into a stock just before an earnings announcement is risky business. However, the team’s research showed that the more searched a stock is, the less change occurred in its price after an announcement.
“You could not use the data to predict if there would be a positive or negative surprise, but you can predict that higher search activity will reduce the margin of the rise or fall of the stock,” Fricke says. The professor additionally cautions that there is no such thing as a safe investment.
And, if using Google Trends to decipher where and how much to invest sounds daunting, fear not: Online information about companies and stocks is also changing the type of investments many people are interested in, which, according to Fricke, underscores the holy grail of investment portfolios — diversification.
“Our research supports a movement that’s been happening over the past decade or so from what’s called active investing to passive investing,” Fricke says. “People no longer want to hand over all their money to big companies hoping they’ll cash in big for them, which actually hasn’t been very effective in the last several years. They’d rather passively buy into funds that spread their money across different stocks, which is showing better returns.”
It’s the most reliable way of investing at the moment, the professor says, at least until more is known about how big data can be leveraged to predict investment outcomes — a task he and other Cal State East Bay scholars will continue working on in the future.
“Big data is relevant in that is shows an application for original research out there and uses new information to solve a question,” he says. “We weren’t the first to publish about Google searches, but we were one of the first few papers to take new information and read it in a new way.”
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