New research from RSM Rotterdam School of Management, Erasmus University has found that information taken from Twitter posts could be used to predict the stock market – and help traders to make better investment decisions.
Ting Li, Professor of Digital Business and Dr Jan van Dalen analysed over a million twitter messages that mentioned stocks listed on the S&P 100 share index.
The researchers then developed an algorithm that looked at the sentiment of the tweets and extracted distinct ‘buy’, ‘hold’ and ‘sell’ signals embedded in them – before comparing them to actual price fluctuations on the stocks over the following days.
They found that stocks that are tweeted bullish sentiments such as ‘buy!’ experience, on average, higher abnormal returns. The results also showed that the relationship between bullish language and increased stock performance was even stronger for influential Twitter users who are frequently retweeted and often mentioned – and that the number of tweets about a particular stock could predict trading volumes, volatility and follow-up return on a stock.
The results often showed that the more that Twitter users disagreed about a particular stock, the higher the trading volumes.
To test if these findings could be the basis for a profitable trading strategy, the researchers ran a 21 week simulation using the information from the study and found that, even taking transaction costs into account, the simulated returns beat the market.