Antoine Bommier: Catalogue data in Autumn Semester 2020

Name Prof. Dr. Antoine Bommier
FieldIntegrative Risk Management and Economics
Address
Integratives Risikomanag. und Ök.
ETH Zürich, SEC E 7
Scheuchzerstrasse 7
8092 Zürich
SWITZERLAND
Telephone+41 44 632 38 10
E-mailabommier@ethz.ch
DepartmentManagement, Technology, and Economics
RelationshipFull Professor

NumberTitleECTSHoursLecturers
363-1100-00LRisk Case Study Challenge Restricted registration - show details
Does not take place this semester.
3 credits2SA. Bommier, S. Feuerriegel, J. Teichmann
AbstractThis seminar provides master students at ETH with the challenging opportunity of working on a real risk case in close collaboration with a company. For Fall 2019 the Partner will be Credit Suisse and the topic of cases will focus on machine learning applications in finance.
Learning objectiveStudents work in groups on a real risk-related case of a business relevant topic provided by experts from Risk Center partners. While gaining substantial insights into the risk modeling and management of the industry, students explore the case or problem on their own, working in teams, and develop possible solutions. The cases allow students to use logical problem solving skills with emphasis on evidence and application and involve the integration of scientific knowledge. Typically, the cases can be complex, cover ambiguities, and may be addressed in more than one way. During the seminar, students visit the partners’ headquarters, interact and conduct interviews with risk professionals. The final results will be presented at the partners' headquarters.
ContentGet a basic understanding of
o Risk management and risk modelling
o Machine learning tools and applications
o How to communicate your results to risk professionals

For that you work in a group of 4 students together with a Case Manager from the company.
In addition you are coached by the Lecturers on specific aspects of machine learning as well as communication and presentation skills.
Prerequisites / NoticePlease apply for this course via the official website (www.riskcenter.ethz.ch/education/lectures/risk-case-study-challenge-.html). Apply no later than September 13, 2019.
The number of participants is limited to 16.
364-0531-00LCER-ETH Research Seminar0 credits2SH. Gersbach, A. Bommier, L. Bretschger
AbstractResearch Seminar of Center of Economic Research CER-ETH
Learning objectiveUnderstanding cutting-edge results of current research in the fields of the CER-ETH Professors.
ContentReferate zu aktuellen Forschungsergebnissen aus den Bereichen Ressourcen- und Umweltökonomie, theoretische und angewandte Wachstums- und Aussenwirtschaftstheorie sowie Energie- und Innovationsökonomie von in- und ausländischen Gastreferierenden sowie von ETH-internen Referierenden.
Prerequisites / NoticeBitte spezielle Ankündigungen beachten.

Studierende des GESS-Pflichtwahlfachs sollten sich vor Beginn mit der Seminarleitung in Verbindung setzen.
364-1025-00LAdvanced Microeconomics
Does not take place this semester.
3 credits2GA. Bommier
AbstractThe objective of the course is to provide students with advanced knowledge in some areas of micro economic theory. The course will focus on 1) Individual behavior 2) Collective behavior 3) Choice under uncertainty 4) Intertemporal choice.
Learning objectiveThe aim is to give to the students the opportunity to review the key results in rational individual behavior, collective models, choice under uncertainty, intertemporal choice, as well as to get some insights on more recent advances in those areas.
The course is therefore designed for students who have some interest for research in economics.
ContentThe following topics will be addressed;
1) Individual Behavior. Theory of the consumer (preferences, demand, duality, integrability). Theory of the firm.
2) Collective models. Cooperative and non cooperative models of household behavior.
2) Choice under uncertainty. The foundations of expected utility theory. Some insights on other approaches to choice under uncertainty.
3) Intertemporal choice. Dynamic model. Life cycle theory.
LiteratureThe course will be based on some chapters of the books "Advanced Microeconomic Theory" by Jehle and Reny (2011) and "Microeconomic Theory", by Mas-Colell, Whinston and Green (1995), as well as research articles for the most advanced parts.
364-1058-00LRisk Center Seminar Series0 credits2SB. Stojadinovic, D. Basin, A. Bommier, D. N. Bresch, L.‑E. Cederman, P. Cheridito, H. Gersbach, G. Sansavini, F. Schweitzer, D. Sornette, B. Sudret, S. Wiemer, M. Zeilinger, R. Zenklusen
AbstractThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. Students and other guests are welcome.
Learning objectiveParticipants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop novel mathematical models for open problems, to analyze them with computers, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to work scientifically on an internationally competitive level.
ContentThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. For details of the program see the webpage of the colloquium. Students and other guests are welcome.
Lecture notesThere is no script, but a short protocol of the sessions will be sent to all participants who have participated in a particular session. Transparencies of the presentations may be put on the course webpage.
LiteratureLiterature will be provided by the speakers in their respective presentations.
Prerequisites / NoticeParticipants should have relatively good mathematical skills and some experience of how scientific work is performed.