The "Twitter Hedge Fund": Harnessing the power of social media for investment direction





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Published on Jul 8, 2011

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On July 1st 2011, London based Derwent Capital Markets has launched the Derwent Absolute Return Fund which became known in the industry as the "Twitter Hedge Fund'. This highly anticipated hedge fund is Europe's first to utilize sentiment derived from real-time social media data analysis.

Most people are not aware that Derwent Capital's investment approach is actually based on an academic paper by Johan Bollen, HuinaMao, Xiao-Jun Zeng called 'Twitter mood predicts the stock market' (http://arxiv.org/abs/1010.3003).

The paper is an investigation into whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time. Indeed, the researchers says their study indicates an accuracy of 87.6% in predicting the daily up and down changes in the closing values of the DJIA.

Analyzing global "fear and greed" in 200 million daily Tweets

Investors have widely accepted that financial markets are driven by fear and greed. Paul Hawtin, Derwent Capital's Founder and Fund Manager explains in this Opalesque BACKSTAGE video how he - together with Indiana University's Professor Johan Bollen and massive computing power - evaluates and interprets the daily 200 million "Twitter Tweets" to understand shifts of "global moods" and their directional impact on the financial markets.

Hear more about:

- How the Twitter hedge funds's signals are computed
- Operational set up and infrastructure of Derwent
- Trade generation
- The "Michael Jackson" Test: Is the Twitter hedge fund an automated black box?
- Risk Management
- Will large scale analysis of social media be part of quant trading and investing from now on?
- Who is invested in the Twitter hedge fund?
- Capacity, Target return

Derwent Capital Markets Ltd is a London based, family owned investment boutique, authorized and regulated by the UK Financial Services Authority.


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