Social Data + Financial Markets

Leigh Drogen, Igor Gonta and Jon Najarian discuss the growing role of social data in financial markets.

In today’s world, news is breaking faster on social media than anywhere else. These outlets have become marketers, brand managers, and crisis responders’ first point of reference for major shifts in their industries – and those in the finance space are listening in too. When the NASDAQ takes a sudden dip, financial professionals need to know about it fast, monitor the conversation around the behavior, then make timely adjustments to maximize the opportunity or in some cases, cut losses. Big Boulder’s social data and financial markets panel discussion proved there is much excitement and anticipation around social data and its application to the finance world. Industry experts Leigh Drogen of Estimize, Igor Gonta of Market Prophit, and Jon Narajian, of optionMONSTER.com provided lively conversation around the current and future prospects for the industry.

In some regards, the finance industry’s integration of social data into methods of trading is still in its infancy. Drogen, who has pioneered many of the platforms for social finance, noted that the industry is moving into a period of structured platforms. Previously, financial professionals often struggled with vast amounts of disorganized data. Companies like Thomson Reuters and FactSet are taking social philosophies and bringing them to finance. Structured financial data means professionals can take a deeper look at the conversation and identify who’s predicting the market change and those who are reacting to it. By placing the predictors against the reactors, analysts are removing the noise from the crowd, resulting in a signal.. and a competitive edge. When identified in a timely manner (and in today’s world, that’s down to the second) it can create conditions for arbitrage opportunities and therefore, profits.

As the industry continues to grow and more data is collected and integrated, the financial markets should become more efficient, smoothing the reactionary curve as financial trading professionals arbitrage social data in all aspects of their business.

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