Stock prices influenced by Twitter and Facebook

Share price volatility is affected by public opinion on social media sites such as Twitter and Facebook, according to a survey of 360 UK financial professionals. The research, carried out by Colt Technology Services, found that 63 per cent of respondents, including brokers and heads of trading desks, believe the valuation of individual stocks can be directly linked to public sentiment contained in social media channels.

While only seven per cent of respondents regard social media sentiment as a leading indicator, 45 per cent see it as a trailing indicator. Firms such as hedge funds and proprietary trading houses can now scan social media data at random and then categorise messages into one of a range of public mood states. The firms then use algorithmic or high frequency trading strategies to place trade orders, enabling them to potentially steal a march on competitors who trade using more traditional forms of data.

Hugh Cumberland, solution manager, payment & settlement services at Colt, says: “In a market where liquidity is highly valued and investors cautious, new sources of competitive advantage will always be welcome. What’s important is working out how best to leverage the data mined from millions of social media messages to help trading firms cut through inertia and deliver much needed volume.”

The research also highlighted some concerns about sentiment-based trading. Nearly a third of respondents believe that the ability to respond fast enough to social media sentiment is a barrier to adoption. The sheer volume of data from social media was also one of the major challenges to creating successful trading strategies, with 43 per cent claiming that they would struggle to respond fast enough to the daily influx of information.

Cumberland adds: “Data mined from millions of tweets and Facebook posts will only add to the increasingly large volumes of information flowing through a firm’s IT systems. With additional capacity and bandwidth required to store, access and manipulate the millions of messages, social media analysis will need to be underpinned by an appropriate IT infrastructure to ensure a consistent, fast and reliable flow of data into the heart of the trading environment.”

Respondents also saw the accuracy of information as a barrier to mainstream adoption at the moment. Cumberland says: “Getting data to the heart of the trading systems as fast as possible is nothing new. Addressing anxiety over data integrity requires confidence that the tools can accurately separate credible data from the general social noise along with maliciously generated content. While only 13 per cent of respondents saw regulatory pressures as a barrier to adoption, the scrutiny that now surrounds the industry means that confidence levels have to improve significantly before social media powered trading becomes the status quo.”

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