Prediction markets are virtual market platforms that make it easier to predict the outcome of specific events. To this end, they aggregate the knowledge of their participants by making use of techniques from betting or stock markets. They are usually implemented electronically via dedicated websites or other tools and platforms.
Even though this type of method has been widely studied, there are still some barriers and challenges that have not yet been fully solved:
- The processes behind the idea of these methods are often quite complex and not intuitively tangible. How can these be adapted so that this tool becomes more usable for the general public?
- How can participants be differently incentivised and what impact do different incentives have on the behaviour of participants within these markets?
Structure of the thesis:
First, the work begins with an introduction to the theory and gaining understanding about the topic. Then, different ways of investigating a particular topic emerge:
- Theoretical familiarisation with the topic and gaining a deep understanding of the various facets of prediction markets.
- Generate hypotheses and consider the possible target group for an experimental study.
- Carrying out the experiment with subsequent investigation.