Research on decision-making at the level of brain, mind and markets
RESEARCH THEMES
-
Learning
Theoretical and empirical research on human and non-human animal learning
-
Reasoning
Theoretical and experimental research on the effects of complexity on reasoning and decision-making, and on the design of communication mechanisms to reduce complexity
-
Social interaction
Theoretical and experimental research on neurocomputational mechanisms of human decision-making in social and non-social contexts
-
Markets
Theoretical and experimental research on the behaviour of markets
We investigate human and machine decision-making in the presence of complexity, at the level of brain, mind and markets
RESEARCH PROJECTS
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.
PUBLICATIONS
A list of publications by lab members is available on the publications page.
RESEARCH TRAINING
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.
TAKE PART
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.
SOFTWARE ENGINEERING
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
Research Themes
We teach decision-making at undergraduate, Masters and PhD level and also offer custom-made executive education programs
UNDERGRADUATE
-
Algorithmic Trading
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
-
Experimental Finance
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
-
Investments
This Honours subject offers an advanced introduction to asset pricing theory
-
Street Finance
Third-year undergraduate subject on financial literacy in which university students teach finance to high-school students
POSTGRADUATE
-
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
-
Behavioural Finance
This subject introduces students to psychological methods and frameworks, and how these mechanisms can explain and predict financial decision-making.
EXECUTIVE EDUCATION
We offer custom-made executive education programs to public- and private-sector organisations through MSPACE. For more information please contact us.
We are a diverse team of decision scientists investigating fundamental questions about the nature of decision-making
OUR PEOPLE
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 WORK
We do theoretical and empirical research on individual decision-making and on markets. 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 empirical research is based on laboratory experiments. More information is available in the Research section. Our publications are available on the Publications page.
We also 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.
OUR PLACE
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 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.