Jobs
PhD student positions @ UCLouvain
Teaching assistant @ Louvain School of Management - LLN (Sep. 2024)
Thesis description
Open in various fields of finance. Teaching duties in accounting & finance.
Profile of the candidate:
Master "Cum Laude" in Business Engineering, Management Sciences or related fields with track in finance.
More information and contact: Frederic.vrins@uclouvain.be
Early warning systems/credit risk (closed)
Thesis description
Credit risk is, by far, the largest risk ran by banks. It is therefore compulsory for them to properly monitor the latter. Although this is partly achieved via financial provisions and regulatory capital requirements, it is the primary interest of banks to limit defaults and to keep their loans performing. This is precisely the purpose of Early Warning Systems (EWS). EWS aim to assess clients’ financial health in expert-based deep-dives, and to detect as early as possible those who could run into difficulties in the next few months. Such systems enable banks to better anticipate potential distresses, and to take appropriate actions to mitigate the risk that those clients end up into financial troubles such arrears in payments. In practice, EWS essentially consist of a set of decision rules and algorithms exploiting large datasets. The latter can feature macro (global economic indicators) and micro (customer-specific) variables.
There is a vast amount of research on credit scoring and the valuation of non-performing loans. By contrast, the scientific literature on EWS remains scarce. This can be understood from the fact that this type of studies is, to a large extend, data-driven, and that accessing those sensible data and publishing related results is very difficult due to obvious confidential and competition reasons.
This PhD thesis (2x2 years, starting September 2023) is organized in collaboration with a major European bank, that will provide a large sample of anonymized data and a standard setup of existing EWS. The purpose of the thesis is to enhance and combine existing EWS systems and to assess the impact of the actions that are taken when a signal is triggered. The PhD student will thus work on the UCLouvain campus but also, occasionally in the company’s premises, in close partnership with the Louvain Finance research center of UCLouvain and the associated team in the bank. This thesis is a unique opportunity to combine advanced scientific research with the development of cutting edge methodologies with sound industrial applications.
Profile of the candidate:
The successful candidate is expected to have a solid background in data science and machine learning (both theory and implementation in R or Python). Very good communication skills (both oral and written) in English is mandatory. Knowledge of finance is an asset.
Keywords: banking, finance, credit risk, early warning systems, big data, data science, algorithms
More information and contact: Frederic.vrins@uclouvain.be
Postdoc position @ UCLouvain
Mathematical finance/credit risk (closed)
The UCLouvain opens a Postdoc position in credit risk/mathematical finance. The overall goal of the research project is to investigate counterparty risk, and credit valuation adjustment (CVA) in particular. The research project will involve new approaches to better model and learn risk dependencies such as wrong-way and recovery risks. The idea is to combine machine learning tools together with stochastic models recently developed within our team.
This Postdoc position will be held in the LIDAM institute, the Louvain Institute of Data Analysis and Modeling in economics and statistics of the UCLouvain, in Belgium. The contract is one year full time grant, extendable for another year and could start as from February/March 2022. The candidate will be co-supervised by Prof. C. Hafner and Prof. F. Vrins. This project is a joint collaboration with Prof. D. Brigo (Imperial College London, UK).
Profile : the successful candidate must
have completed (or be about to complete) a PhD in Actuarial Sciences, Financial Engineering, Quantitative Finance, Applied mathematics or related fields ;
be familiar with financial concepts like risk-neutral valuation, Black-Scholes model and credit risk modeling. Knowledge of CVA/wrong-way risk is an asset ;
be familiar with standard machine learning algorithms such as neural networks ;
have strong skills in continuous-time stochastic processes, numerical simulations and coding (R, Python or Matlab) ;
have a good knowledge of written and spoken English. Knowledge of French is not required.
Research environment & terms of employment
The project is a joint venture between ISBA and LFIN, two renowned research centers of high international reputation. Equipped with modern computing facilities, a statistics library, a vivid visitor program and ample funding for scientific activities. Regularly organized short courses, workshops, and seminar series (all in English) are given by international short and long-term visitors. ISBA and LFIN are located in the heart of the modern, vivid and international UCL university campus at Louvain-la-Neuve, in close proximity of Brussels and its international airport, and in short travel distance to other European capitals. You will receive a tax-free monthly grant for two times two years. The position is a pure research position, that is, with (almost) no teaching or administrative obligations.
How to apply ?
Send your application directly to frederic.vrins@uclouvain.be. Your application should consist of a zip archive including the following :
A motivation letter, including the names and contact information of two reference persons (including your PhD supervisor)
A detailed curriculum vitae
A detailed publication list
A copy of your relevant diploma(s)
A copy of your best paper (chosen according to the technical skills required here)
Related references :
Mbaye, C. & Vrins, F. (2022). Affine term structure models: a time-change approach with perfect fit to market curves. Mathematical Finance (forthcoming). http://hdl.handle.net/2078.1/254447
Jeanblanc, M. & Vrins, F. (2018) Conic martingales from Stochastic integrals. Mathematical Finance 28(2):516-535. http://hdl.handle.net/2078.1/176590
Damiano B. & Vrins, F. (2018) Disentangling wrong-way risk: pricing credit valuation adjustment via change of measures. European Journal of Operational Research 269:1154-1164 (2018). http://hdl.handle.net/2078.1/196286