A six-year study of the Financial Times has found that the more frequently a company is mentioned in the newspaper in the morning, the greater the volume of shares traded in that company during the same day.
Merve Alanyali, of the Centre for Complexity at the University of Warwick, and Suzy Moat and Tobias Preis, of Warwick Business School, looked at 1,821 issues of the Financial Times from January 2, 2007 to December 31, 2012.
They demonstrated a strong correlation between the daily mentions of companies in the Financial Times in the morning and how much they were traded on the stock market during the day.
Dr Preis, Associate Professor of Behavioural Science and Finance, and Dr Moat, Assistant Professor of Behavioural Science, have previously found that following query volume for financial search terms on Google could predict stock market movement, while also revealing that increases in the number of views of financially related Wikipedia pages was a prelude to stock market falls.
Now by tracking mentions of the names of the 30 companies on the Dow Jones Industrial Average in the Financial Times, the two academics and their collaborator Merve Alanyali have shown a link between what hits the news and stock market trading.
Dr Moat said: "It seems intuitive that trading decisions are affected by news available to a trader – and equally, that big movements in the market can cause big waves in the news. In this study, we were seeking to provide a quantitative description of the relationship between movements in financial markets and developments in financial news."
Alanyali added: "We looked at a corpus of six years of daily print issues of the Financial Times, tracking the mentions of companies that form the Dow Jones Industrial Average.
"Interestingly, we found that a greater number of mentions of a company in the news on a given morning corresponded to a greater volume of trading for that company during the same day, as well as a greater change in price for a company's stocks."
Dr Preis said: "The results are consistent with the hypothesis that movements in the news and movements in the markets may exert a mutual influence upon each other. However we could find no evidence of a relationship between the number of mentions of a company in the morning's news and the direction of price movement for a company's shares."
In the paper Quantifying the Relationship Between Financial News and the Stock Market, the team writes: "Future analyses building on this work will seek to provide further insight into the direction and causality of the relationship between financial news and market movements."
Quantifying the Relationship Between Financial News and the Stock Market is published in Nature Publishing Group's Scientific Reports on Friday, at http://www.nature.com/srep/2013/131220/srep03578/full/srep03578.html
This URL will become live when the embargo lifts at 10am UK time on Friday December 20. Copies of the paper can also be requested from Tobias.Preis@wbs.ac.uk.
To interview Dr Tobias Preis contact:
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To interview Dr Suzy Moat contact:
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Notes to editors:
Warwick Business School, located in central England, is the largest department of the University of Warwick and the UK's fastest rising business school according the Financial Times. WBS is triple-accredited by the leading global business education associations and was the first in the UK to attain this accreditation. Offering the full portfolio of business education courses, from undergraduate through to MBAs, and with a strong Doctoral Programme, WBS is the complete business school. Students at WBS currently number around 6,500, and come from 125 countries. Just under half of faculty are non-UK, or have worked abroad. WBS Dean, Professor Mark P Taylor, is among the most highly-cited scholars in the world and was previously Managing Director at BlackRock, the world's largest asset manager.
Suzy Moat is an Assistant Professor of Behavioural Science at Warwick Business School. Her work exploits data from sources such as Google, Wikipedia and Flickr, to investigate whether data from the Internet can help us measure and even predict human behaviour. In recent studies, in collaboration with Tobias Preis, H. Eugene Stanley and colleagues, Dr Moat has provided evidence that patterns in searches for financial information on Wikipedia and Google may have offered clues to subsequent stock market moves, and that Internet users from countries with a higher per capita GDP are more likely to search for information about years in the future than years in the past. Dr Moat was awarded a Ph.D. from the University of Edinburgh and won a series of prizes during her studies. Since 2011, Dr Moat has secured £3.3 million of funding from UK, EU and US research agencies. Her work has been featured by television, radio and press worldwide, including recent pieces on CNN and the BBC. Dr
Moat has acted as an advisor to government and public bodies on the predictive capabilities of big data. She currently co-directs a small research team working on these questions. As a computational social scientist, Dr Moat's research investigates how the vast amounts of data generated by our everyday use of technology can help us understand and even predict how humans behave.
Tobias Preis is an Associate Professor of Behavioural Science and Finance at Warwick Business School. His recent research has aimed to carry out large scale experiments on complex social and economic systems by exploiting the volumes of data being generated by our interactions with technology. In 2010, Dr Preis headed a research team which provided evidence that search engine query data and stock market fluctuations are correlated. In 2012, Dr Preis and his colleagues Suzy Moat, H. Eugene Stanley and Steven R. Bishop used Google Trends data to demonstrate that Internet users from countries with a higher per capita GDP are more likely to search for information about the future than information about the past.
Dr Preis received his Ph.D. in Theoretical Physics from the Johannes Gutenberg University of Mainz in 2010 and draws on an interdisciplinary background in physics, economics, and computer science. He has authored more than 30 scientific publications, published a book about the physics of financial markets and acts as a reviewer for more than 15 leading international journals. Dr Preis serves as an Academic Editor of the multidisciplinary journal PLoS ONE. Dr Preis advises government agencies as well as private companies on potential exploitation of online digital traces. More information can be found on his personal website http://www.tobiaspreis.de. Dr Preis's current research activities are driven by a deep interest in understanding the complex behaviour of financial systems by exploiting big data resources, with the hope that such understanding could contribute to the development of reliable and stable financial systems. His expertise covers a wide range of subjects including computational social science, big data analytics, predictive analytics, data mining, complex systems, network science, and management science.
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