Looking to retail investment trends as a leading indicator of capital markets is like the “Ask the Audience” option on the TV show Who Wants to be a Millionaire. Statistically, a random split between four multiple choice answers would produce equal weightings for each answer, but in reality, a percentage of the audience—even a minority—knows the correct answer and inevitably skews the result towards the correct answer.
In the financial markets, the audience majority doesn’t have to know the right answer, because there isn’t one: essentially, whatever direction they lean becomes the right answer—i.e. the direction in which the market will move. Joe Public may be mistaken about the direction a stock will move. They read a negative report and suppose that the price will fall, and place sell and/or buy orders at the appropriate prices. It really doesn’t matter whether their supposition is correct; it merely matters that a trader can gauge their supposition and act to buy, sell and ride that sentiment up or down to profit between the current price and the public’s consensus price prediction.
For years, traders have pursued all manner of ways of analyzing news and public opinion to get a read on how the markets will react to so-called “market-moving” events, so they can get ahead of a surge of trading and take advantage of any price movements. And when we talk about “how the markets will react,” we ultimately mean “how investors will react,” since it’s their money—either as self-directed investments or via advisors and funds—that drive market prices. But until now, data on consumers’ investing intentions has been hard to obtain.
Twitter, StockTwits and other social media platforms have changed that, providing a window into retail investors’ mindsets, and in fact, providing a platform through which investors openly share their opinions on stocks—both directly with projections or trade ideas, and indirectly via the collective sentiment of their opinions on a company or stock.
Getting someone to give you their direct opinion isn’t hard: you ask them. And if you really want to incentivize them to give you their best predictions, give them something in return. For example, individuals who contribute their predictions to crowd-sourced earnings estimates provider Estimize are part of a platform that—through their input—creates more accurate information that they can then use to inform their investment decisions. Or take trading game providers like Invstr or Nous, which creates a feed of investor price predictions for institutions, sourced from its mobile trading game app, incentivizes users with cash prices for the most accurate “players.” In effect, in poker terminology, it gets investors to show their hand before actually playing it.
But obtaining indirect opinions is a harder proposition that involves turning a statement into a concrete indicator—i.e. turning unstructured content into a sort of structured market data. Vendors began by analyzing news stories to extract their sentiment—whether a story is positive or negative about the companies it mentions. Next came the challenge of quantifying how positive or negative that should be, and how it would translate into price movements. By now, vendors like RavenPack, Market Prophit, Digital Contact and Social Market Analytics have become pretty adept at filtering social media streams for relevant mentions and garnering reliable sentiment data, creating a burgeoning industry that continues to grow—for example, with the additions of startups DragonFish and TheySay, which both outline new initiatives in this week’s issue of Inside Market Data.
And speaking of weekly issues, since many of our dear readers are taking a well-earned break as summer draws to an end, we’ve decided to do the same. The next print issue of IMD will hit your desks on Sept. 7, but between now and then, we’ll continue to post news on insidemarketdata.com, so don’t forget to check the website or download our app to make it easy fo keep up with the latest data industry news, even on vacation.
Jesse Lund talks about real uses for DLT in the capital markets, lessons learned while rolling out IBM's blockchain platform, and what’s ahead for 2018, and into 2019.Subscribe to Weekly Wrap emails