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Research on decision-making in complex environments at the level of brain, mind and markets
Theoretical and empirical research on human and non-human animal learning
Theoretical and experimental research on the effects of complexity on reasoning and decision-making, and on the design of communication mechanisms to reduce complexity
Theoretical and experimental research on neurocomputational mechanisms of human decision-making in social and non-social contexts
Theoretical and experimental research on the behaviour of markets
We do theoretical and empirical research addressing fundamental questions in individual decision-making and markets, with the aim to identify new ways to improve both human and machine decision-making. Our work integrates knowledge and methods from decision and game theory with neurobiology, economics and finance, psychology and computer science. Most of our empirical work is based on laboratory experiments.
Our research is organised around three themes: complexity, learning, social interaction, and markets. A list of current and past projects is available on our Research Themes page.
A list of publications by lab members is available on the publications page.
We offer research training at both Honours and PhD level. To find out about doing Honours with us, visit the Honours in Finance site. If you are interested in doing a PhD with us, please go to the page of our inter-disciplinary PhD program in decision science (Decision, Risk and Financial Sciences) for more information.
You can take part in our experiments. We are always looking for participants.
Most of our experiments take place on the University of Melbourne Parkville campus. An experiment typically lasts between one and three hours. Participants are compensated for their time.
Click here to find out which experiments we are currently recruiting for and what's involved in participating.
We also develop software for both research and commercial purposes. Our lab has been closely involved in the development of FLEX-E-MARKETS, a platform for online, continuous double auction markets. We use FLEX-E-MARKETS in our research on asset pricing as well as in our teaching. We also develop market mechanisms and trading algorithms.
This page lists publications since 2012 by current members of the lab. Earlier publications are available on PubMed and Google Scholar
In this subject, students learn to develop trading algorithms and how to evaluate those algorithms
Elements of Quantum Computing
This subject provides an introduction to quantum computing for students from a range of backgrounds
This subject introduces students to novel experimental research methods to shed new light on asset pricing theory
Foundations of Fintech
This new subject discusses how emerging technologies can be used to solve fundamental problems in finance
This Honours subject offers an advanced introduction to asset pricing theory
Third-year undergraduate subject on financial literacy in which university students teach finance to high-school students
Experimental Methods in Decision Studies
This subject introduces students to methods for experimental research on decision-making
Fintech: Foundations and Applications
In this subject, students apply new technologies such as DLT and various machine learning algorithms to solve fundamental problems in finance
This subject introduces students to psychological methods and frameworks, and how these mechanisms can explain and predict financial decision-making.
We offer custom-made executive education programs to public- and private-sector organisations through MSPACE. For more information please contact us.
We do theoretical and empirical research to address fundamental questions in individual decision-making and markets, with the aim to identify new ways to improve both human and machine decision-making. Most of our current work focuses on complexity of decisions, learning, social interaction, and markets. In our research, we integrate knowledge and methods from decision and game theory with neurobiology, economics and finance, psychology and computer science. Most of our work is based on laboratory experiments. More information is available in the Research section. Our publications are available on the Publications page.
We teach, at both undergraduate and postgraduate level, and we offer executive education, on topics including behavioural economics/finance, neuroscience of decision-making, algorithmic trading, fintech and research methods. Our teaching builds heavily on our research. More information on the subjects we currently offer is available in the Teaching section.
We also develop software for both research and commercial purposes. Our lab has been closely involved in the development of FLEX-E-MARKETS, a platform for online, continuous double auctions. We use FLEX-E-MARKETS in our research on asset pricing as well as in our teaching. We also develop AlgoHost, a platform for developing and testing trading algorithms.
Meet our team of economists, neuroscientists, mathematicians and computer scientists. If you are interested in joining our team, please visit our Opportunities page. This page also contains information for students who are interested in doing a PhD, their Honours research project or an internship with us.
Our lab is based on the Parkville campus of the University of Melbourne, just north of Melbourne's CBD. It is located on the edge of the Melbourne Biomedical Precinct, Australia’s, and one of the world’s, leading biomedical precincts. It is only a short walk away from the new Melbourne Innovation Districts.
In our research, we collaborate with colleagues in the Faculty of Medicine, Dentistry and Health Sciences at the University of Melbourne, the Florey Institute for Neuroscience and Mental Health, as well as at universities around the world including the California Institute of Technology, Cambridge University, University of Minnesota and University of Utah.