Facebook, Twitter and other forms of social media are changing our lives. And given that history tells us that it often takes decades for the full effects of new technology to become apparent, these changes probably include ways we cannot yet foresee. However, it is possible that social media have at least one downside – they can distort our financial decisions.
Twitter warning for share traders
Our first clue that this is the case comes from a recent study by Vineet Bhagwat at the University of Oregon and Timothy Burch at the University of Miami. They have found that companies in the United States that are active on Twitter see their share prices behave differently after earnings news. Twitter-active firms see their shares rise more in the days after good earnings news. But they also see prices recover more strongly in the days after bad results. Both good news and bad, then, raises their share price after a few days.
The most obvious explanation for this is that being on Twitter helps a company to attract investors’ attention; it can draw their attention to good results, which causes prices to rise. And it can also draw attention to its reasons (or excuses) for poor results.
This, though, poses a danger for share traders. It means they could be trading on stale information. By the time some news has been tweeted, retweeted and discussed, it should be already discounted by markets; it should be in the price.
One easy way for retail investors to lose money is by trading too much; doing so incurs dealing costs without any offsetting benefit. Social media can increase our temptation to do so.
There’s another way in which this can happen – through correlation neglect. Imagine you were to read a story in a newspaper you didn’t believe. You would not give the story more credence if it also appeared in your friend’s copy of the paper. His copy and your copy are obviously correlated so one does not verify the other. However, it’s easy to make this mistake in other contexts. If you see a rumour repeated on the internet, its many repetitions are not necessarily corroboration of each other; they might instead have a common source, with tweeters simply repeating each other.
Some experiments by Florian Zimmerman and Benjamin Enke at the University of Bonn have shown how this failure to discount signals because they have a common source is both common and costly. They got subjects to guess the number of balls in an urn they couldn’t see, based upon some computer-generated clues. Some were told that the clues were uncorrelated while others were told they were correlated. But the latter group didn’t discount the signals accordingly. This meant they were overconfident about the reliability of the clues, and so guessed too high when the clues were high, and too low when they were low.
What’s more, when subjects were invited to trade an experimental asset whose pay-off depended upon the number of balls in the urn, traders getting the correlated clues drove prices too high if the clues were high and too low if they were low. This tells us that correlation neglect can lead to costly investment errors, as we put too much faith in unreliable signals.
Facebook and confirmation bias?
There’s a third problem with social media, described by Cass Sunstein of Harvard Law School and co-author of the influential book Nudge. We tend to follow and be friends with people like ourselves. This can generate a type of groupthink, whereby we become too confident about our beliefs because we see them echoed by people we like. Professor Sunstein worries that this can cause excessive extremism and dogmatism in politics. But it’s quite likely that this can spill over into other aspects of life; if the internet encourages us to become overconfident about our political beliefs, it might also lead us to become overconfident about our views on the economy and investment matters.
The point here is a simple one. For centuries, technology has shaped people’s beliefs, often in ways of which they are unaware. And because our beliefs can be distorted by numerous cognitive biases, we should be on guard against ways in which technology can exacerbate those biases.