Professor David Tuckett and Colleagues have been awarded $250,000 by the Institute for New Economic Thinking to set up a Centre for the Study of Decision-Making Uncertainty. For more news >>>
Learning at the Centre
CSDU hosts a MPhil/PhD
programme open to a wide range of scholars interested in studying uncertainty
and its human consequences for decision-makers.
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We welcome additional corporate and individual investors and are currently seeking philanthropic support to enable us to bring in more researchers, engage in more projects and build our network of partners. To learn more about plans for the UCL Centre for the Study of Decision-Making Uncertainty, to discuss how it could be of most benefit to your business, or to explore opportunities to support UCL, please contact: Christine Simms, Executive Head of Major Gifts.
Ph.D and Post Doc Opportunities at the Centre
CSDU hosts a MPhil/PhD programme open to a wide range of scholars interested in studying uncertainty and its human consequences for decision-makers. Students with backgrounds and interests in law, finance, political science, economics, sociology, anthropology, psychology, neuroscience, computer science and psychoanalysis interested in the Centre’s programme of research could all be suitable.
The Centre has a thriving research group connected to major centres worldwide and to other faculties at UCL. It is linked to the Psychoanalysis Unit and part of the Division of Psychology and Language Sciences (PALS) in the Faculty of Brain Sciences. Research student programs are tailored to their backgrounds and the methodologies required to investigate their research questions. Supervisors will be available from throughout UCL.
Applicants are invited from suitably qualified candidates to pursue any topic within the Centre’s general remit.
Some funded positions are available (in co-operation with other UCL departments). The following are current priorities for such PH.D studentships available from September 1st 2015:
The role of sentiment in determining the business cycle
The role of sentiment was recognised in economics in the 1930s and 40s by a range of great economists such as Hayek, Keynes and Schumpeter. Recent advances in computer science technology mean that time series of sentiment can now be extracted from large scale text data bases using directed algorithmic search. We are seeking a PhD candidate to work on developing a theoretical macroeconomic model of the business cycle in which sentiment is a key determinant. The model will be calibrated, using the standard techniques of mainstream macroeconomics, against the key stylised facts both of standard macroeconomic variables, and the sentiment variables described above. Whilst analytical results obtained from the model will be desirable, much of the work will require computer simulation of agent-based models.
The research will be directed by Professor Paul Ormerod. The candidate might come from any existing discipline but must have a strong background in maths. Prior knowledge of economics is desirable but not essential.
Understanding Monetary Policy in the context of sentiment
Recent advances in computer science technology mean that time series of sentiment can now be extracted from large scale text data bases using algorithmic search techniques. There is a growing literature in economics which analyses the minutes of central bank meetings and other such texts in this way. Our approach is based upon a new theory of human decision making under uncertainty, namely conviction narrative theory. In contrast to the existing literature, which is essentially atheoretical, textual search is directed by a social psychological theory of emotion in decision-making. The PhD candidate would analyse information and time series data obtained from central bank minutes and other sources by this method using econometric techniques such as SVAR. The aim will be to obtain a better understanding of the stance and effects of monetary policy once sentiment and narratives around policy are taken into account.
The research will be directed by Professor Paul Ormerod and Rickard Nyman. A strong background in modern time series econometrics is essential. Prior knowledge of algorithmic text analysis or social psychology, whilst it would be an advantage, is not required in any way.
Fund Manager Survival
Questions exist as to the role and functioning of active asset management and its effect on the economy and savers. A Ph.D. candidate is sought for a study mixing computer, statistical and questionnaire techniques aiming to determine the main influences on medium and long-term fund manager performance and particularly the extent to which variations in the institutional arrangements in which they work create significant differences in performance outcome. The study will construct a new longitudinal database and then use it both for analysis and further study, for example through sending out questionnaires. The aim is to shed light on the factors that determine survival and to consider their impact on the strategies and performance of fund managers and the effects both on the financial system and the short-term and long-term effects on the economy.
The study will be directed by Professor David Tuckett and Dr Robert Smith with the assistance of Dr Arman Eshraghi from the University of Edinburgh Business School. A strong background in statistics and mathematics is essential. Prior knowledge of computing, finance or questionnaire methodology, whilst it would be an advantage, is not required. The studentship might suit a statistically inclined social scientist or psychologist.
New Approaches to Text and Sentiment Analysis
Modern text analysis and natural language techniques are focused on extracting meaning from unstructured texts, including challenge problems in extracting the entities and topics being talked about, their relationships, analysis of the elements of discourse in the text, and the intended or stated sentiment in and around these elements and relationships. A Ph.D. candidate is sought to extend these techniques to extract psychological meaning from text automatically. This will require research that combines and selectively exploits existing techniques in text analysis and natural language processing along with exploration of current knowledge in linguistics as it pertains to psychology, particularly around decision-making under uncertainty, particularly in financial and economic settings, but with potential applications in other areas, including public policy, conflict detection, etc. The study will combine understanding of the mathematics involved in computational techniques, the social science aspects involved, and innovative implementation of these techniques in a framework to address “big data”.
The study will be directed by Professor David Tuckett and Dr Robert Smith. A strong background in mathematics and programming is essential. Prior knowledge of linguistics, psychology, natural language understanding or text analysis is helpful, but not essential. The studentship might suit a social scientist or psychologist with experience in programming, or a programmer with interests in the social sciences.
New Approaches to Dynamic Social Network Analysis
Social network analysis (SNA) focuses primarily on static metrics and structures arising from networks of people, for instance via their connections in social media, their connections via co-authorship, etc. One of the most exciting areas of SNA is the examination of the evolution dynamics of networks over time. A Ph.D. candidate is sought to develop new SNA techniques that consider the propagation of psychological states surrounding topics through networks, and how that affects social network dynamics. The aim of the study is to better understand the contagion of ideas, with effects on areas like economics, policy impact, marketing, conflict detection, etc. The study will combine ideas from SNA with innovative text analytics, to construct and dynamic networks from evolving “big data” sources.
The study will be directed by Professor David Tuckett and Dr Robert Smith. A strong background in mathematics and programming is essential. Prior knowledge of SNA is helpful, but not essential. The studentship might suit a social scientist or psychologist with experience in programming, or a programmer with interests in the social sciences.
Application Process: Interested applicants should submit a CV with the names of two referees and a letter indicating the nature of their interest and suitability and the approach they might take to one or more of the projects to the email link here.
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