Research project in finance and insurance - 2nd semester

Objective

Students of the M2 "Statistics, Finance and Actuarial Science" and students of the Actuarial Science and Finance & Risk Management tracks of ENSAE have the opportunity to participate in prospective work, in groups of 3 or 4 and under the guidance of a supervisor, professional of the financial industry or researcher in finance / insurance. The supervisor will meet with the students once or twice a month to coordinate and guide their work, in person or by videoconference. He/she will also provide the students with the data necessary to carry out the project.

These in-depth projects focus on a well-identified subject of quantitative finance, risk management, or insurance, and present a genuine interest for the company/laboratory. For example, it can be an exploratory research around a new model, the analysis of a specific database or the study and development of a new portfolio management strategy. Projects will include typically a bibliographic research step, a data analysis step and a computer implementation step. Although the results of the project can be interesting and useful for the company, it is by no means a consultancy assignment.
The objective is to be forward-looking, to test innovative ideas.

The publication of an article as the result of such work could be considered in certain cases.

The studens must submit an interim report at the end of January, a final report in May and pass an oral defense. This is a full course, which will validate 3 ECTS in the first semester and 3 ECTS in the second semester.

Examples of topics proposed in 2020-2021 :

1. Shareholder engagement (CREST)
2. Integration des vues des investisseurs dans le processus de gestion de portefeuille (BFT Investment Managers)
3. Historical simulation for Equity index Futures and Options (Zeliade Systems)
4. Modélisation multidimensionnelle des prix sur les marchés intraday de l’électricité (EDF Lab)
5. Trading VIX futures (Marker Cipher)
6. Optimal execution of trading strategies (Varenne Capital Partners)
7. Deep reinforcement learning for trading (Andurand capital)
8. Assurance Cyber : estimation de lois jointes et prédiction multi-dimensionnelle (Sorbonne Unviersité)
9. Amélioration de la méthodologie de pricing relative au péril « feu de forêt »(Axa)
10. Modélisation par les processus de Hawkes des sinistres individuels en prenant en compte les délais de déclaration (Milliman / Axa)
11. Finance verte et stress tests climatiques (Mazars)
12. Simulation des stress tests pour un portefeuille des actifs corrélés de grande dimension (Natixis)

Planning

The indicative timetable for the projects is as follows:
- Beginning of October: dissemination of subjects to students, constitution of groups
- End of January: submission of the mid-term report
- Beginning of May: submission of the final report
- Before the end of May: defense

This course aims in particular to give students the following skills:
- Bibliographic research
- Analysis of financial data
- Formulation and implementation of a mathematical model from a business problem
- Methodology and requirements of industrial / university research