People use big data in an increasing number of applications, such as to investigate what makes their customers satisfied or unhappy or reveal the long-term effects of marketing campaigns. Those are still valid uses, but big data is also affecting an industry that might seem unexpected: investment trading.
Big Data Gives a Competitive Advantage
Whether people are just getting started with investment trading or doing it with small, independent operations, they may feel like perpetual underdogs. They might also feel as if they’ll never have adequate resources to succeed in the marketplace, at least compared to more experienced traders or those associated with successful and well-known operations.
However, because big data crunches the numbers related to a large quantity of information in a short amount of time, it creates a competitive advantage with results that are faster and more accurate than what humans can achieve.
While getting involved with the stock market online, people frequently rely on what’s known as algorithmic trading. It involves using computer-generated algorithms that make decisions and act on behalf of humans without their direct and constant interventions. That approach improves the investment power of individual traders and trading firms.
Big Data Could Reduce the Burdens Investment Managers Carry
People familiar with big data in the financial and investment trading say algorithms are already handling many of the tasks typically assigned to humans but at an error rate lower than real people’s efforts. Analysts say, then, that eventually, investment managers will not be relied upon as heavily as they have been in the past.
Moreover, the use of such algorithms will likely help bring an entirely different method of determining stock prices. If these suspected developments come to pass, investment managers may lose some of the worth they enjoy now in their industry. But, they could also develop their skills to excel in things technology cannot do.
Big Data Increases the Availability of Information
Some big data platforms pull news from dozens of sources, thereby making individuals and investment firms more informed than they might otherwise be about emerging trends. Without technology, it could take hours for investors to be sufficiently informed about market activity and the best times to invest.
However, robust tools can focus on news sources originating from certain places or search for articles containing specified keywords. Then, it’s possible for users to get informed in the most useful ways without digging through a substantial amount of information that ultimately isn’t relevant.
Combing Through Social Media for Valuable Information
Some big data platforms even analyze tweets. There have been debates about whether social media buzz about the stock market is just noise or has some worthy tidbits.
A research study carried out by a team at Erasmus University’s Rotterdam School of Management confirmed that stock-related content posted on Twitter could help predict short and long-term market developments. The researchers looked at over a million stock-related tweets during their analysis.
They also made an algorithm that examined the signals in those tweets that tell people to buy, hold or sell. Next, they compared the signals to the actual fluctuations of stocks and found that tweets about an individual stock could influence its performance on the market as soon as 15 minutes later, as well as through the next day.
The researchers noticed so-called power-users who were particularly influential on Twitter had even more of an effect on making stocks perform positively during a given day, thanks to their bullish tweets.
In conclusion, the scientists said their results indicated that analyzing tweets can give a snapshot of market sentiment and help individual traders or firms make better investment decisions. Big data tools make such use of social media possible, whereas it would be prohibitively cumbersome and time-consuming without them.
Turning to Big Data to Reduce Risks
All investment trading involves risk, but big data platforms could reduce them by offering price data. Allan Timmermann is a finance professor at the University of California at San Diego. One of his goals is to understand the various factors that determine security prices, and Timmermann has developed a big data tool to help him find out.
It needs an input of daily data from publicly traded firms in the U.S. that declare earnings or dividends. Understanding stock price shifts could be exceptionally beneficial for traders. When people are more aware of the characteristics that make prices change, they can watch out for them and use that knowledge to choose when to invest or hold off.
Lance Roberts, the chief portfolio analyst and economist for Clarity Financial, believes Americans disregard the risk inherent in the stock market because of bad market advice. Then, they can’t capitalize on the wealth that the stock market can bring to savvy investors.
Even if an investor does not knowingly ignore the present risks, they could feel more confident about future investments by depending on big data platforms before making any substantial decisions. Then, they could avoid outcomes that may be financially devastating.
The Use of Big Data Is Still in the Early Stages
We are still only in the emerging period of understanding how to use big data for the benefit of people who work in the financial sector, particularly as investment traders. That means that although the overview above gives an idea of how it’s changing the industry, there’s more to come.