We all know Twitter, America’s favorite 140 character micro-blogging site. Twitter has quickly grown over the past 5 years to one of the most popular sites in the world, receiving over 1 billion tweets per week. With the exponential growth of Twitter, more people began looking for a way to harness all of these opinions in to something meaningful. Developers got to work developing software systems that look at factors such as emotion, tone, and content to determine opinion. Twitter originated as a rather simple idea, has now turned into a robust platform for business, news and social gathering.
Being able to understand the opinions of a community is crucial for traders and investment bankers. Valid data gives them insights in to whether they should be against or with the current public opinion. Not to mention, it also gives independent investors a way to gather market intelligence from unknown sources, potentially giving day traders a competitive advantage in a cluttered investment landscape.
Using Twitter to predict the stock market is a relatively new concept. There are very little publicly available tools, and many tools come with skeptics. The skeptics claim that Twitter has too much noise. There are so many tweets every second that say something; however the truth is that the majority of these tweets don’t carry much opinion. Instead tools like Opinion Finder, aggregate data from people that are tweeting words about their emotion by using words “I feel like,” “I like,” “I want to.” Even with this, they found was that their Twitter algorithm paralleled market changes and allowed them to predict changes with an 87.6% accuracy.
Twitter is a hot topic for many investment firms. Currently it hasn’t been adopted on a massive scale, making it a rare tool to gain a competitive advantage. However in the future if these stock predictors provide fruit, the competitive advantages will lie in how well they aggregate opinions and not simply using the tools. “According to Derwent Capital Markets, a London-based hedge fund set to open for public investment on April 1, has pooled together $40 million to obtain exclusive rights to the Twitter predictor, according to the Indiana Daily Student. Bringing on Bollen and Mao as personal consults, they plan to create a trading model based on the findings.”
1. Capture daily tweets.
2. Analyze tweets with mood-measurement tools.
3. Determine mood content of tweets (i.e., “positive” vs. “negative” or “calm” vs. “anxious”).
4. If mood is positive or “calm” readings jump, buy stocks, because Dow is likely to rise three to four days later.
5. If mood is negative or “calm” readings plummet, sell stocks, because Dow is likely to fall three to four days later.
(IU study showed 86.7% accuracy rate in predicting the direction of the Dow three to four days later.) According to USA Today
Day trading can be an exciting mix of trial and error. It can’t hurt to try a new an emerging trend in the investment world. Even though people may be saying that “It’s a ripple, not a wave. It’s just another data source that has been popularized.” The skeptics are just less competition.
What do you think Twitter can be a scope for the same in future? Do share your thoughts.
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