Professor Tobias Preis
Professor of Behavioural Science & Finance
Research Interests
Mammoth amounts of data are now being generated through society's extensive interactions with technological systems, automatically documenting collective human behaviour in a previously unimaginable fashion.
Preis' interdisciplinary research investigates whether data from sources such as Google, Wikipedia, Twitter, Flickr and Instagram can be used to:
Together with Suzy Moat and Mark Carrigan, he chaired Europe's first Computational Social Science Conference at the University of Warwick.
See also his Google Scholar Profile for a list of citations and statistics.
Teaching in 2018-2019
Finance
- IB9CS0: Big Data Analytics
MSc Business
- IB9CSB: Big Data Analytics
Postgraduate Research Business and Management
- IB9ES0: Advanced Communication Skills for Data Science Research
- IB9ER0: Designing and Managing Data Science Research
Behavioural Science Group
Email: Tobias.Preis@wbs.ac.uk / Tel: 024 765 28422 / Room: 3.120
Biography
Tobias Preis is Professor of Behavioural Science and Finance at the University of Warwick and a Fellow of The Alan Turing Institute, the UK's national institute for data science and artificial intelligence. Together with his colleague Dr. Suzy Moat, he directs the Data Science Lab at Warwick Business School.
His recent research has aimed to analyse and predict real world behaviour with the volumes of data being generated by our interactions with technology, using data from Google, Wikipedia, Twitter, Flickr, Instagram and other sources. Preis' research is frequently featured in the news, by outlets including the BBC, the New York Times, the Financial Times, Science, Nature, Time Magazine, New Scientist and the Guardian.
He has given a range of public talks including presentations at TEDx events in the UK and in Switzerland and he frequently advises governmental and commercial stakeholders around the globe. More details can be found on his website https://www.tobiaspreis.com.
Selected media coverage of his work includes:
"Computer analysis of what is scenic may help town planners"
"Measuring the mobs"
"Crowds 'could be counted' with phone and Twitter data"
"Do Politics-Themed Google Searches Predict Stock Activity?"
"Google search proves to be new word in stock market prediction"
"Google searches predict market moves"
"Counting Google searches predicts market movements"
"Google Search Terms Can Predict Stock Market, Study Finds"
"Which countries are the most forward thinking? See it visualised"
"Online searches for future linked to economic success"
"Study: Are Google Searches Affecting the Stock Market?"
"Can Google Predict the Stock Market?"
Publications
Journal Articles
- Seresinhe, C. I., Moat, H. S. and Preis, T. (2018) "Quantifying scenic areas using crowdsourced data", Environment and Planning B : Urban Analytics and City Science, 45, 3, 567-582
- Curme, C., Zhuo, Y. D., Moat, H. S. and Preis, T. (2017) "Quantifying the diversity of news around stock market moves", The Journal of Network Theory in Finance, 3, 1, 1-20
- Seresinhe, C. I., Preis, T. and Moat, H. S. (2017) "Using deep learning to quantify the beauty of outdoor places", Royal Society Open Science, 4, 7, 170170
- Alanyali, M., Preis, T. and Moat, H. S. (2016) "Tracking protests using geotagged Flickr photographs", PLoS One, 11, 3, 1-8, e0150466
- Letchford, A., Preis, T. and Moat, H. S. (2016) "Quantifying the search behaviour of different demographics using Google Correlate", PLoS One, 11, 2, 1-11, e0149025
- Moat, H. S., Olivola, C. Y., Chater, N. and Preis, T. (2016) "Searching choices : quantifying decision-making processes using search engine data", Topics in Cognitive Science, 8, 685-696
- Seresinhe, C. I., Preis, T. and Moat, H. S. (2016) "Quantifying the link between art and property prices in urban neighbourhoods", Royal Society Open Science, 3, 4, 1-7, 160146
- Kristoufek, L., Moat, H. S. and Preis, T. (2016) "Estimating suicide occurrence statistics using Google Trends", EPJ Data Science, 5, 1, 32
- Botta, F., Moat, H. S. and Preis, T. (2015) "Quantifying crowd size with mobile phone and Twitter data", Royal Society Open Science , Volume 2, Number 5, 150162-150162
- Alis, C. M., Lim, M. T., Moat, H. S., Barchiesi, D., Preis, T. and Bishop, S. R. (2015) "Quantifying regional differences in the length of Twitter messages", PLoS One, Volume 10, Number 4, Article number e0122278
- Letchford, A., Moat, H. S. and Preis, T. (2015) "The advantage of short paper titles", Royal Society Open Science , 2, 8, 1-6, 150266
- Barchiesi, D., Preis, T., Bishop, S. R. and Moat, H. S. (2015) "Modelling human mobility patterns using photographic data shared online", Royal Society Open Science , 2, 8, 1-8, 150046
- Barchiesi, D., Moat, H. S., Alis, C. M., Bishop, S. R. and Preis, T. (2015) "Quantifying international travel flows using Flickr", PLoS One, 10, 7, 1-8, e0128470
- Seresinhe, C. I., Preis, T. and Moat, H. S. (2015) "Quantifying the impact of scenic environments on health", Scientific Reports, 5, 16899
- Botta, F., Moat, H. S., Stanley, H. E. and Preis, T. (2015) "Quantifying stock return distributions in financial markets", PLoS One, 10, 9, 1-10, e0135600
- Letchford, A., Preis, T. and Moat, H. S. (2015) "The advantage of simple paper abstracts", Journal of Informetrics, 10, 1, 1-8
- Noguchi, T., Stewart, N., Olivola, C. Y., Moat, H. S. and Preis, T. (2014) "Characterizing the time-perspective of nations with search engine query data", PLoS One, Volume 9, Number 4, Article number e95209
- Curme, C., Preis, T., Stanley, H. E. and Moat, H. S. (2014) "Quantifying the semantics of search behavior before stock market moves", Proceedings of the National Academy of Sciences of the United States of America, Volume 111, Number 32, 11600-11605
- Preis, T. and Moat, H. S. (2014) "Adaptive nowcasting of influenza outbreaks using Google searches", Royal Society Open Science , Volume 1, Number 2, Article number 140095
- Moat, H. S., Preis, T., Olivola, C. Y., Liu, C. and Chater, N. (2014) "Using big data to predict collective behavior in the real world", Behavioral and Brain Sciences, Volume 37, Number 01, 92-93
- Preis, T., Moat, H. S. and Stanley, H. E. (2013) "Quantifying trading behavior in financial markets using Google Trends", Scientific Reports, 3, 1684
- Moat, H. S., Curme, C., Avakian, A., Kenett, D. Y., Stanley, H. E. and Preis, T. (2013) "Quantifying Wikipedia usage patterns before stock market moves", Scientific Reports, 3, 1801
- Alanyali, M., Moat, H. S. and Preis, T. (2013) "Quantifying the relationship between financial news and the stock market", Scientific Reports, Volume 3, Article number 3578
- Preis, T., Moat, H. S., Bishop, S. R., Treleaven, P. and Stanley, H. E. (2013) "Quantifying the digital traces of Hurricane Sandy on Flickr", Scientific Reports, Volume 3, Article: 3141
- Feng, L., Li, B., Podobnik, B., Preis, T. and Stanley, H. E. (2012) "Linking agent-based models and stochastic models of financial markets", Proceedings of the National Academy of Sciences, Vol.109, No.22, 8388-8393
- Preis, T., Moat, H. S., Stanley, H. E. and Bishop, S. R. (2012) "Quantifying the advantage of looking forward", Scientific Reports, Vol.2, Article no. 350
- Preis, T., Kenett, D. Y., Stanley, H. E., Helbing, D. and Ben-Jacob, E. (2012) "Quantifying the behavior of stock correlations under market stress", Scientific Reports, Vol.2, Article no. 752
- Kenett, D. Y., Preis, T., Gur-Gershgoren, G. and Ben-Jacob, E. (2012) "Dependency network and node influence : application to the study of financial markets", International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, Volume 22, Number 07, Article number 1250181
- Block, B. J. and Preis, T. (2012) "Computer simulations of the ising model on graphics processing units", The European Physical Journal Special Topics, Volume 210, Number 1, 133-145
- Preis, T., Schneider, J. J. and Stanley, H. E. (2011) "Switching processes in financial markets", Proceedings of the National Academy of Sciences of the United States of America, Vol.108, No.19, 7674-7678
- Tobias Preis (2011) "Econophysics ��� complex correlations and trend switchings in financial time series", The European Physical Journal Special Topics, Volume 194, Number 1, 5-86
- Tobias Preis (2011) "GPU-computing in econophysics and statistical physics", The European Physical Journal Special Topics, Volume 194, Number 1, 87-119
- Preis, T., Reith, D. and Stanley, H. E. (2010) "Complex dynamics of our economic life on different scales : insights from search engine query data", Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol.368, No.1933, 5707-5719
- Block, B., Virnau, P. and Preis, T. (2010) "Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model", Computer Physics Communications, Volume 181, Number 9, 1549-1556
- Preis, T. and Stanley, H. E. (2010) "Switching phenomena in a system with no switches", Journal of statistical physics, Volume 138, Number 1-3, 431-446
- Preis, T., Virnau, P., Paul, W. and Schneider, J. J. (2009) "Accelerated fluctuation analysis by graphic cards and complex pattern formation in financial markets", New Journal of Physics, Vol.11, No.9, Article no. 093024
- Preis, T., Virnau, P., Paul, W. and Schneider, J. J. (2009) "GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model", Journal of Computational Physics, Volume 228, Number 12, 4468-4477
- Preis, T., Paul, W. and Schneider, J. J. (2008) "Fluctuation patterns in high-frequency financial asset returns", EPL (Europhysics Letters), Volume 82, Number 6, 1-7, Article number 68005
Book Items
- Tobias Preis (2011) "Price-time priority and pro rata matching in an order book model of financial markets ", Springer, Milan ; New York
- Preis, T. and Stanley, H. E. (2010) "Trend switching processes in financial markets ", Springer Japan,
Book
- Tobias Preis (2011) "O��konophysik : Die Physik des Finanzmarktes", Springer Fachmedien Wiesbaden GmbH, Wiesbaden, Wiesbaden : Gabler Verlag. 9783834963956
