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Algorithmic Trading and the Streaming Data Complex: A Little Bird Told Me


While the shouting over whether Twitter has any value is largely over— there’s still some question as to what that value is. The search for a single qualitative value to which Twitter can be reduced is, of course, futile. It would be like trying to identify the single value of ink/paper, email, telephones or http.

When looking for meaning and value, there are a number of routes we might take. The denizens of Forrester, Gartner and Red Monk might take one direction; the host of burlesque performers and vaudevillians hanging out shingles as ‘social media’ experts may take another. Generally the process involves modeling what a business might do with ‘social meda’ (Twitter). The Profit/Loss in these models generally operates in the realm of public relations, marketing, good will and social capital. There is some argument for Twitter as a customer service channel, but while it’s optimal as a hailing frequency, it’s inadequate as a customer solution medium. This soft approach has some chance of success during a bull market, and a better than even chance during a financial bubble. While some, like Umair Haque, argue that these soft social revenue streams ultimately must provide a context for hard revenue streams, at the moment the stock market doesn’t agree. Positive sentiment on Twitter doesn’t translate into more demand for an equity. Adoption is currently limited to businesses that either can afford the luxury, or have replaced existing marketing and public relations modes with the Twitter channel.

On the hard revenue stream side of the ledger, we might look at how algorithmic stock traders are beginning to use Twitter. In trading, the asymmetry of the dispersion of news is a trading opportunity. We’ve seen how flash traders can create algorithms that determine the market’s direction from real-time data before the rest of the trading fraternity can even open their eyes.

Wall Street & Technology Magazine’s Melanie Rodier is reporting that algos at hedge funds are starting to consume data flow from Twitter to gauge the direction of sentiment toward an event or stock. The compact size and real-time nature of the tweet makes its ingestion and analysis particularly attractive. StreamBase Systems, a vendor of a complex event processing (CEP) platform, has announced a Twitter adapter that allows its applications to both consume and publish tweets. The designated (tracked) twitter streams are spliced with market data, financial ratios, newswire information and other data streams to build a more fully dimensional picture of a particular stock (company). Waiting for news to be collected, digested and emitted by Reuters can add too much latency to the news/information release pattern.

Just as reading the early reports from a newswire requires an understanding of context, history and the politics of news construction and distribution; reading a tracked Twitter stream as a part of a data complex requires a particular interpretive skill set. If the old adage ‘buy on the rumor, sell on the news’ has some truth to it, Twitter has just added a deep data layer to the ‘buy’ side of that equation.

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