The Department of Economics is delighted to announce that Alessio Sancetta and Francesco Feri won a Leverhulme grant to study the dissemination of information in high frequency trading. The main goal of the project is to study information dissemination through the interaction of machines and humans in financial markets.
Machines in the form of algorithms are nowadays an integral part of any financial market. In the last decades, there has been emerging interest in algorithms to make predictions and decisions in financial markets. The project intends to add a new dimension to it by studying the interaction between machines and humans.
The project addresses questions such as:
- How do human participants react to the presence of algorithms in the market?
- How is information dissemination within electronic markets affected by the presence of algorithms? Are human and algorithmic traders able to detect the information disseminated in the market? How can they learn from each other?
- How does the presence of algorithms affect the dynamics of electronic financial markets? How unstable and manipulatable a market becomes as the proportion of algorithms increases?
- How well can an algorithm learn from historical data? Can such a trained algorithm adapt to learn from new data from experiments? How well can an algorithm learn to account for its actions when such actions impact the environment?
To answer these questions, a considerable innovation of the project is the use of economic experiments where participants can be either humans or algorithms trained on high frequency datasets.
