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Research project

Modelling the wisdom of the crowd

Project overview

Crowd sourcing, an innovative means of aggregating information to improve public and commercial decisions, is based on the principle that relevant information concerning the likelihood and nature of future events is dispersed among the opinions and intuitions of many people. Prediction markets, an important means of crowd sourcing, are growing rapidly. These markets for contracts, whose values depend on the outcome of future events, have been used to predict the probability and nature of many uncertain outcomes. The efficient market hypothesis predicts that in prediction markets, prices will incorporate all available information. The success and potential of these markets in predicting public events and corporate outcomes has generated substantial interest among social scientists, policymakers, and the business community. Working with a company operating a leading prediction market, the project transferred knowledge on discrete choice modelling and real-time Big Data analysis from the EPSRC funded secondee and the research team from Centre for Risk Research at the Southampton Business School to enable the company to transform its existing and future digital data (containing details of several million trades) into commercial knowledge for business value creation and profit enhancement.
The project completed with very positive feedback from the sponsor “The project has stimulated our interest in, and has highlighted future directions for, a Counter-party project which we believe has highly significant profit potential. The KTS project has provided the tools needed to help make this a reality and has really helped inform our thinking concerning this business strategy” “We developed an excellent working relationship with the secondee and with members of the project team from the Centre for Risk Research and expect this to continue in the future. We really enjoyed working together on this innovative project. The project demonstrated to us the valuable ideas and expertise which are available to businesses within universities”.


Lead researcher

Professor Ming-Chien SUNG

Professor of Risk And Decision Sciences

Research interests

  • Financial technology (Fintech) and cryptocurrency analysis
  • Risk analysis using Big Data
  • Artificial intelligence (AI)
Connect with Ming-Chien
Other researchers

Emeritus Professor Johnnie Johnson

Research interests

  • Risk taking behaviour
  • Use of information in betting markets
  • Decision-making under uncertainty
Connect with Johnnie

Dr Tiejun Ma

Associate Professor

Research interests

  • Financial Risk Modelling
  • Investors Behaviour Modelling
  • Fintech
Connect with Tiejun

Collaborating research institutes, centres and groups

Research outputs