Thèse, Liège, Belgium.| Entreprise/Organisme : | University of Liège - HEC Liège (Belgium) | | Niveau d'études : | Master | | Sujet : | Regression Models for Extremes in Finance:
Regression Models for Extremes are statistical techniques that have seen enormous developments in
the past years. Today, they allow us to study the dependence structure among extreme events that
are of interest for regulators, policy makers and the financial sector at large (e.g. cyber-attacks,
multimillion frauds, financial crises and contagion, etc.). However, numerous methodological
challenges are still unsolved, making it hard for practitioners to rely on these tools. Therefore, the first
goal of this PhD thesis will be to tackle some of these issues, in particular model selection, dimension
reduction, non-stationarity and causality questions. Extensions of techniques like the LASSO, neural networks, copula, GLM will be considered to solve these problems. The second objective consists in
applying these findings to the study of systemic and cyber risks. The Great Financial Crisis as well as
the advent of the Internet of Things highlighted the increasing interconnections between economic
agents. Thus, the proper design of related risk measures and the identification of their determinants
have become crucial tasks to monitor the financial system and prevent its collapse. In conducting
empirical studies on these problematics, we aim at answering to these preoccupations. Banks, hedge
funds and insurance companies are the kinds of institutions studied.
The PhD project is part of a series of ongoing research projects in collaboration with researchers from
ESSEC (France), HEC Montréal (Canada) and University of Goettingen (Germany). It offers multiple
opportunities for collaborations and research stays in these institutions. Data for the project are made
available through national security agencies and professional databases like HFR or CRSP. The project
will be further refined and can be adapted once the PhD student has started. Other fields of
applications like insurance, energy economics, climate change or economic inequalities can be
considered. | | Date de début : | 1st October 2019 but can be postponed (1 February 2020 at the latest) | | Durée du contrat : | up to 6 years (3 times 2-year contracts) | | Rémunération : | around 2000 EUR | | Secteur d'activité : | Research and higher education | | Description : | YOUR PROFILE
- You have a Master’s degree (120 ECTS or equivalent) in applied statistics/mathematics, business
engineering, econometrics or a related quantitative subject (e.g. finance, quantitative
economics, applied science, physics).
- You have an interest for financial and economic applications, related to risk, market finance
and banking.
- You have a keen interest in statistics, and ideally knowledge in methods/models like GLM,
LASSO or Extreme Value Theory.
- You have a good knowledge of R, MATLAB and/or Python, and the willingness to extend it.
- You are fluent in English. Knowledge of French and/or German is a plus.
- You are persistent, work independently and have good communication skills.
- Prior experience in the financial industry (risk department, hedge funds) is a plus.
WHAT DO WE OFFER?
- A full-time position, up to 6 years (two-year renewable contracts after
receiving positive evaluations). The salary is approximately 2.000 € per month after taxes.
- A starting date on 1 October 2019, open to discussion.
- A stimulating and flexible research environment, as a member of the research unit Asset and
Risk Management (ARM).
- An access to a global research network in statistics, econometrics and finance, as well as to
industrial and governmental collaborations.
- A doctoral training program in collaboration with Solvay Brussels Schools of
Management (ULB) and linked to Maastricht University.
WHAT DO WE EXPECT FROM YOU?
- Conducting a research project related to the description made above, with the aim to write a
PhD thesis in the field of statistics/ quantitative methods applied to Finance, under the
supervision of Prof. Julien Hambuckers.
- Successfully attending the doctoral training program.
- Being in charge of practical sessions for advanced finance classes (Financial Data Modelling,
International Finance, Applied Financial instruments), equivalent to around 3h of teaching per
week.
APPLICATION PACKAGE
- Cover letter showing your motivation and eligibility for the position.
- CV showing your past experiences, your relevant expertise for the position and two references.
- An example of your written academic work (e.g. master thesis).
- A copy of your undergraduate and postgraduate degrees.
HEC® Liège is the management school of the University of Liège. HEC® Liège is one of the leading
Belgian university business schools for graduate and postgraduate programs with more than 115 fulltime faculty members and researchers and more than 2500 students. The international vision of HEC® Liège translates into multiple research activities in management and economics, numerous
partnerships with worldwide companies and universities, and growing internationalization of its
programs and faculty.
HEC® Liège hold both AACSB and EQUIS institutional accreditations. HEC® Liège also holds the
EPAS award for each of its three main programs: the Master in Management, the Master in Business
Engineering, and the Doctoral Program. The specialization “Banking and Asset Management” of the
Master in Management is into the CFA Institute University Recognition Program. HEC® Liège is also a member of the Conférence des Grandes Ecoles.
HEC® Liège is located in Liège, Belgium’s third largest city, and the largest agglomeration of the Frenchspeaking Walloon region. At the heart of Europe, Liège is the third inland port of Europe and the
seventh freight airport in Europe. Recognized for its quality of life and its rich historical heritage, Liège
is ideally situated within the Meuse-Rhin Euregio, 30 km from Maastricht (the Netherlands) and 60 km
from Aachen (Germany). It is less than 1.5 hours away from Cologne, 1.5 hours from Paris and 3 hours from London by high-speed train. | | En savoir plus : | http://www.hec.ulg.ac.be/fr/hec-liege/hec-liege-recrute
teaching_assistant_finance2019.pdf | | Contact : | jhambuckers@uliege.be |
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