Algorithmic trading systems are, as everyone knows, dispassionate. They are rules based, mechanical trading robots. You would think then that there is no place for emotion to enter into the picture, and no real reason for its doing so. That thinking, however, may not be correct.
As long as there are humans participating in trades, and as long as human speech, whether written or spoken, influences public opinion, then those opinions can, do, and will impact stock price. If a set of rules could be built around that idea, and the data from various social media aggregated to create solid metrics, then there is an opportunity to bridge the gap between human emotion driving opinion and its influence on a company’s stock price, and the mechanical nature of an algo trading system.
Algorithmic Trading System & Algorithm Technologies
Viralheat is a new company that is doing that very thing. They have recently been awarded patents for two of their algorithm technologies that allow them to process vast amounts of social media data, sift through the static, and cut to the specific language that is shaping opinion. At the moment, their main focus is on the consumer, and their purpose is to identify specific marketing opportunities for individual consumers. For instance, if someone announces on Facebook that they are having a baby, marketers can then begin marketing baby products to them. They may or may not be entering search terms on various search engines, but it won’t matter, because their social media signals have been read and understood.
This same basic approach can be used for product brands, and by extension, the companies that own those brands. By looking for specific language that indicates public sentiment about a brand or company, the data can be collected and trends spotted. Those trends could then be fed into an algorithmic trading system to take advantage of ebbs and flows in public perception as it relates to specific brands, companies, and even whole industries.
To my knowledge, there is not yet a single algorithmic trading system taking such an approach, but it is certainly worthy of some consideration. It could open the door to a fascinating new field of study within the algorithmic trading universe.