Each year, Natixis calls for submissions from 30 Tier 1 quantitative finance Masters programs in Europe – France, UK, Belgium, Switzerland, Italy – to select the best theses conducted in their respective courses.

Prize for best Master’s Thesis in Quantitative Finance

2021 Laureates

This year, we received 18 theses from 11 different Masters programs, with topics reflecting recent technological innovation. More than half of the documents submitted covered the application of data science (machine learning) to market finance i.e. derivatives pricing, market risk hedging, cryptocurrencies, forecasting.

 

The Natixis Foundation’s Scientific Committee was impressed by the exceptional quality of the theses it received. Contrary to misconception, the quality of students and teaching in these key programs is not deteriorating but rather is absolutely remarkable.

Jean Cheval, President of Natixis Foundation for Research & Innovation

First prize

  • Hannah Maidment
    Thesis: "Hawkes Process-Driven Models for Limit Order Book Dynamics"
    Master : MSc in Mathematical and Computational Finance, University of Oxford

    "In my thesis, I consider the use of Hawkes processes to model the arrival of orders in a limit order book and show that they effectively capture the clustering behaviour observed in limit order book dynamics. In a world where electronic, order-driven markets are becoming ubiquitous, the advantages of developing a meaningful model for the dynamics of a limit order book are extremely broad. These range from gaining clearer insight into the role of supply and demand in price dynamics to informing the design of electronic trading algorithms and optimal execution strategies.

 

Second prize ex æquo 

  • Rémy Vuillet
    Thesis: "Rough Volatility: Simulation and Calibration", realized at BP London
    Master : MSc in Mathematical and Computational Finance, University of Oxford

    "My thesis focuses on rough volatility models, which provide more realistic volatility dynamics for stock prices. First, I look at the simulation of the Rough Heston model and I show the tension between arbitrarily rough volatility and unbiased option prices. Secondly, I improve the benchmark for the calibration of these models with a neural network. Finally, I propose a straightforward method to estimate the regularity of time series using the signature transform from rough path theory."

 

  • Thomas Hengstberger
    Thesis: "Increasing Venture Capital Investment Success Rates Through Machine Learning"
    Master : MSc in Mathematics and Finance, Imperial College

    "The thesis explores the use of machine learning models to identify successful startup investments for the purposes of Venture Capital (VC) investing. The process of how VC investments generate returns is formalised and then translated into a binary target variable, which hinges on a future investment entry point and a subsequent investment exit point.  To imitate how predictive models might be used in a commercial setting, three machine learning models (Logistic Regression, Random Forests and Extreme Gradient Boosting) are trained using historical data from Crunchbase, while their performance is evaluated based on the predictive accuracy on unseen data. The resulting models are able to correctly identify successful startup investments in 46-52% of cases within a 4-year outcome period, which compares favourably to the typical VC 30% success rate."

2020 Laureates

 

 

 

From left to right: Jean Cheval, President of the Natixis Foundation for Research & Innovation; Gilles Pagès, Director of the Probabilities and Finance Master's Degree at the Université Pierre et Marie Curie Paris 6 and École Polytechnique; Olivier Pironneau (on screen), Académie des Sciences and member of the scientific committee of the Natixis Foundation; Mathieu Rosenbaum, professor at the École Polytechnique and winner of the 2020 Louis Bachelier Prize; Nicole El Karoui, founder of the Probabilities and Finance Master's Degree at Pierre et Marie Curie University Paris 6 and École Polytechnique; Pierre Gasnier (on the screen at the top right), winner of the 2020 Best Master's Thesis Prize, Université Pierre et Marie Curie Paris 6 and École Polytechnique; Charles-Albert Lehalle (on the screen at the bottom right), Capital Fund Management and member of the scientific committee of the Natixis Foundation; Lukas-Benedikt Fiechtner, winner of the 2020 Best Master's Thesis Prize, University of Oxford; Michel Crouhy, President of the scientific committee of the Natixis Foundation.

 

  • Pierre Gasnier
    Thesis: "Mean Field Game Theory for Gas Storage Valuation", realized at BP London
    Master: M2 “Probabilities and Finance”, Pierre and Marie Curie - Paris VI University and École Polytechnique

    "The subject of my work was to solve an optimal trading problem where the price dynamic depends of the actions, buying or selling, of the market agents. Mean field game theory simplifies the problem considering there is an infinite number of agents, but they have individually an infinitesimal impact. In my thesis, I show that the state of equilibrium of this game is not only the solution of a partial differential equation but also is the limit of a series of games where the market agents adapt naively their strategies to the previous games, giving us therefore two different numerical methods to solve the problem."

 

  • Lukas-Benedikt Fiechtner
    Thesis: "Risk Management with Generative Adversarial Networks"
    Master : MSc in Mathematical and Computational Finance, University of Oxford

    "In my work I apply Generative Adversarial Networks, a novel machine learning technique, to generate artificial stock price trajectories whose statistical properties closely match those of real financial time series. Leveraging this generative power one can greatly enlarge the dataset available to estimate risk measure such as Value-at-Risk. An out-of-sample backtest shows that this methodology is competitive with traditional Value-at-Risk estimation methods such as historical simulation. The work also paves the way for future applications of GANs in financial mathematics. For instance, one could backtest trading strategies using artificially generated data."

READ THE THESIS OF OUR 2020 LAUREATES

Previous laureates by year

2019

Michal Kozyra
Subject: « Deep learning approach to hedging »
Master: MSc in Mathematical and Computational Finance, University of Oxford

Watch his video    READ HIS THESIS 

Wei Xiong
Subject: « Machine learning in financial market risk: VaR Exception classification model », realized at J.P. Morgan
Master: M2MO Random Modelling, Université Paris Diderot

Watch his video    READ HIS THESIS


2018 Redwan Bouizi
Thesis : "Financial time series forecasting using wavelet transform and reservoir computing paradigm", realized at Quant Finance
Master : MSc in Mathematics and Finance – Imperial College – Londres

Soufiane Hayou
Thesis : "Cleaning the correlation matrix", realized at Bloomberg, New York
Master : Master 2 "Probabilités et Finance" - Université Pierre et Marie Curie Paris 6 and École Polytechnique

2017
Aitor Muguraza Gonzalez
Thesis : "Rough volatility: Characterization of VIX in rBergomi and extension to numerical schemes", realized at Zeliade Systems
Master : MSc in Mathematics and Finance – Imperial College – Londres

Jean-Christophe Dietrich
Thesis : "Initial margin funding cost for rate products", realized at Goldman Sachs
Master : Master M2MO Random Modelling - Université Paris Diderot

Hayssam Sabra
Thesis : « Currency management methods for international portfolios »
Master : Master of Science in Wealth Management - University of Geneva

2016
Guillaume Ausset
Thesis : « Ensembles d'Arbres – Théorie et application au scoring », realized at Crédit Agricole
Master : Master "Mathématiques de l'Assurance, de l'Économie et de la Finance" (MASEF)

Sébastien Geeraert
Thesis : « Calcul de sensibilités par AAD » (Adjoint Algorithmic Differentiation), realized at MUREX
Master 2 "Probabilités et Finance" - Université Pierre et Marie Curie Paris 6 and École Polytechnique

Abdou Kélani
Thesis : « Couverture Optimale des Garanties de type Variable Annuities en présence de Risques Financiers Extrêmes », realized at Laboratoire SAF de l'ISFA
Master : ISFA – Université Lyon 1

2015
Claire Monin
Thesis : « Optimisation multiobjectif de l’allocation stratégique par un algorithme génétique », realized at BNP Paribas Cardif
Master : Institut de Science Financière et d’Assurances (ISFA) - Université de Lyon 1

Julien Doumergue
Thesis : "Optimal Hedging Strategies using Stochastic Space Barriers and its Application to Financial Products", realized at BNP Paribas UK
Master : Master 2 "Probabilités et Finance" - Université Pierre et Marie Curie Paris 6 and École Polytechnique

Shuren Tan
Thesis : "Reconstructing the Joint Probability Distribution from Basket Prices"
Master : MSc in Mathematics and Finance – Imperial College – Londres

2014

 


Johannes Heinrich
Thesis : "Reinforcement Learning for Algorithmic trading"
Master : MSc in Mathematics and Finance – Imperial College – Londres

Joël Bun
Thesis : "Out-of-Sample Risk Optimization Using Random Matrix Theory", realized at Capital Fund Management
Master : Master 2 "Modélisation Aléatoire" - Université Paris Diderot

Salmane Lahdachi
Thesis : « Environnement Multi-Courbes et Marges de Basis Stochastiques », realized at Crédit Agricole – CIB
Master : Master 2 "Probabilités et Finance" - Université Pierre et Marie Curie Paris 6 and École Polytechnique

2013
Jiatu Cai
Thesis : « Risque de Contrepartie et de Liquidité », realized at Crédit Agricole - CIB
Master : Master 2 "Modélisation Aléatoire" – Université Paris 7 – Paris Diderot

Jens Olov Michael Ronnqvist
Thesis : "Default Contagion in Financial Networks"
Master : MSc in Mathematics and Finance – Imperial College – Londres

Olivier Daviet
Thesis : "Commodity Futures Contagion and Diversification Potential : An Empirical Study in the U.S. Market"
Master : Master of Science in Finance - University of Geneva

2012
Tung-Lam Dao
Thesis : "Momentum Strategies : From Novel Estimation Techniques to Financial Applications", realized at LYXOR
Master : Master "Modélisation Aléatoire" – Université Paris 7 – Paris Diderot

Marouan Iben Taarit
Thesis : "Market Liquidity and Adverse Permanent Effects in Hedging Equity & Interest Rates Derivatives", realized at GRO (Crédit Agricole)
Master : Master "Mathématiques et Applications" – Parcours Finance – Université Paris-Est Marne-la-Vallée – École des Ponts Paris Tech

Adrien Grangé Cabane
Thesis : « Étude des Modèles de Corrélation en Finance », realized at Société Générale
Master : Master 2 "Probabilités et Finance" - Université Pierre et Marie Curie Paris 6 and École Polytechnique

2011
Anthony Darné
Thesis : « Remporter les appels d’offres de retraite supplémentaire grâce au Liability Driven Investment », realized at BNP Paribas Assurances
Master : Master Université Claude Bernard Lyon 1 – ISFA

Mauricio Labadie
Thesis : "Optimal Algorithmic Trading and Market Microstructure", realized at Chevreux – Crédit Agricole
Master : Université Paris Dauphine – Master 104

2010
Rija Razanatsimba
Thesis : « Validation de Modèles de Valorisation sur les Marchés Électriques », realized at EDF Trading
Master : Master Université Paris-Est Marne-la-Vallée

Martin Jimenez Sanchez
Thesis : "Variable Annuities – the GMxB guarantees and the GMWB’s Optimal Surrender Behavior", realized at Milliman
Master : Master Université Claude Bernard Lyon 1 – ISFA

2009
Anas Benabid
Thesis : « Modèle à volatilité stochastique de Wishart »
Master : Master 2 "Probabilités et Finance" - Université Pierre et Marie Curie Paris 6 and École Polytechnique

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