On September 12th, the news of Twitter's SR1 filing with the SEC gave this journalist a cue to announce another startup company.
Smart ideas are spun from a simple concept even from the complex infrastructure of financial investing. Predictive forecasting in the stock market based on social media triggers is the beauty of Market Prophit, a platform focused on analyzing stock-related conversations in social media and providing real-time, crowd-sourced sentiment signals and buzz to both retail and institutional clients.
Market Prophit uses sophisticated natural language processing and quantitative analytic to extract meaningful bullish/bearish signals from social media noise. Its algorithms automatically interpret and quantify large quantities of unstructured conversations to deliver actionable insights in an intuitive and easy-to-use interface with lots of visualizations.
I spoke with Igor Gonta today, the CEO and founder of Market Prophit. Mr. Gonta is a 13-year Wall Street veteran having worked at Goldman Sachs, Credit Suisse, and Barclays. He holds a BS and an MS in electrical engineering from MIT. Our conversation debuts his company’s mission – to empower the individual everyday investor with the same financial big data analytics tools and market-moving information currently available to professional investors.
Q: If you are going to produce a thirty second TV commercial to air during the program, CNBC’s “Squawk Box.” What would it say about your service?
A: I would say, that with so many market-moving financial related conversations happening in social media today and the volume of noise growing as well, it's impossible for an individual investor to keep up with it all; be able to filter out the noise, get a sense of market mood and sentiment and actionable signals, and especially, do all of this in real-time. Market Prophit makes sense of the conversations and allows the individual investor to access that market moving information through an easy-to-understand platform. Our website empowers the every-day investor to use our sentiment and buzz signals as yet another arrow in their "information quiver" when they are researching all of the information when evaluating what stocks to buy and sell.
Q: Can you explain how the platform works?
A: Our platform (which is currently in a free beta) takes in Tweets from the Twitter fire hose and extracts those that are financial/stock related (i.e. ones that include a cash-tag or a ticker with a "$" in it). We are planning to add other social media data sources in the future as we expand our company. We then use sophisticated natural language processing and quantitative analytic to generate sentiment signals (bullish/bearish) and buzz for individual tickers. Sentiment signals vary between -1 (most bearish) and +1 (most bullish) on a continuous scale. Buzz scores greater than 1 indicate higher than usual conversation about a particular ticker. All signals on our website are updated every minute. Most financial instruments in the conversations are stocks but there are commodities, currencies, fixed income and some futures as well. We then present these signals in a variety of visual outputs that make the data easy to interpret and quickly understand for the user. We also have powerful features such as a dashboard where a user can track a custom set of tickers in their portfolio. Email alerts are another powerful feature that we have built into the platform to allow users to get notified when custom sentiment, buzz, and/or price related targets they set are triggered so they can get alerted on tickers that matter most to them. We have also back-tested our signals and have shown that they can at times be predictive of stock price movements and generate positive returns. You can find those results on our research page on our website. However, as with any investment strategy, our signals should not be solely relied upon to make decisions but rather can be used as a complementary source of information when doing research on what stock to buy and sell. And of course, as noted on our website, we are not a financial adviser and our output is for informational purposes only (please see our disclaimer).
Q: Can you give a recent example of how your website's signals were predictive of a stock's price movement.
A: Yes, there have definitely been many examples recently of our site's signals alerting bullish/bearish sentiment before a stock prices subsequent move (up/down). The most notable ones are the infamous "Icahn Apple tweet" as well as the market’s reaction to his CNBC interview where he said that he had bought more shares after Apple's price decline on the day of their product release. As you can see from the first chart below (the top chart is our sentiment signal and the bottom chart is the price of Apple), Market Prophit's sentiment signal turned positive (bullish) prior to the tweet. In this example, sentiment was bullish on Apple in the social media blogosphere before he tweeted but more importantly, Market Prophit's proprietary sentiment engine picked up on the tweet quickly and created a fast bullish signal prior to the full reaction of the stock price move up.
Similarly, in the case of the CNBC interview, our signal went positive (bullish) before Icahn actually spoke about buying Apple shares that day and therefore preceded the subsequent upward move in the stock price. Here, it is interesting to note that even though Icahn didn't actually tweet that he had bought the shares but said it in a TV interview, Market Prophit analytical engine picked up on conversations in social media regarding that interview and generated a bullish sentiment signals based on those conversations.
You can follow Market Prophit LLC by going to the company’s twitter account @MarketProphit, or become a friend on their facebook page. Learn more about the company by going to the company profile by jumping to their Linkedin account or to their website.