Wallstreet and Web2.0

Since Collective Intellect is in the business of finding novel information from consumer generated media sources I often get asked about other opportunities that exist in mining information from the web for trading. Activity is really just starting to heat up in this area with multiple companies getting started and several acquisitions going on. It also seems to me with the popularity of more powerful web interfaces via AJAX and Flash that there are even some opportunities to create research platforms that are easier to use, more robust, and with more information than the current king of the road, Bloomberg. I'll reserve bitching about Bloomberg for a future post however.

I've jotted down an unordered list of what I've come across so far and will spend some time in future posts describing each one in more detail.

• Rumor Detection - Find the people that are speculating on some aspect of the company that would likely have material impact to the stock, such as: big deals, management change, mergers, drug trial results, etc.
• Sentiment Measurement - Detect sentiment towards a company, it's management and directors, and products and run statistical models to compare this against stock price and volatility
• Event Activity Correlation - Track a company event, such as an earnings announcement, that has material impact to the company and measure the amount of chatter before and after the announcement in order to gain insight into what the crowd thinks will happen to the company stock relative to the event.
• Citizen Analysts - Find the people in Consumer Generated Media (CGM) who speak regularly about a company and offer unique insights into that company or its products.
• Trend Death - For consumer packaged goods that end up on auction sites, mine those sites for popular product pricing. When prices reach an asymptote and start to trend down, it is possibly time to short the stock.
• Fill Rate Prediction - Anyone who takes online reservation for resources whether it be airlines, hotels, cars, that have variable rate pricing models, scrape pricing information. Lower prices = lower fill rates and thus lower top line revenues for the company.
• Passive Site Visits to Stock Price - Use Comscore or Compete.com information to track the number of visitors to a consumer packaged goods site. This shows invigorated consumer interest which may translate into stock price movement. I believe there was a study showing AAPL site visits as a predictor of stock price movement.
• Active Site Visits to Revenue - For companies that sell products online, track the number of unique visitors and clicks within the site. If you can figure out the customer conversion to average order size you can estimate revenue contribution from the online property.