Séminaire Bachelier Paris


Objectif : Les cours Bachelier sont des cours de formation doctorale ouverts également aux chercheurs et aux praticiens désireux de suivre un cours spécialisé de haut niveau dans le domaine des mathématiques financières.

Périodicité et lieu : Les cours ont lieu à l’Institut Henri Poincaré entre 9h à 11h, selon le programme indiqué dans Programme, avant le séminaire Bachelier.


Cours de Christian Bayer

(TU Berlin)

les vendredis 01/03 et 08/03

Abstract of Mini-Course 1 :

Lecture notes ⬇

Cours de Christa Cuchiero

(TU Berlin)

les vendredis 22/03 et 29/03

Abstract of Mini-Course 2 :

Lecture notes ⬇

Cours de Gilles Pagès

(TU Berlin)

les vendredis 26/04, 03/05 et 17/05

Abstract of Mini-Course 3 :

Lecture notes ⬇

Cours de Peter Friz

(TU Berlin)

les vendredis 14/04 et 21/04

Abstract of Mini-Course 1 : From Diamonds to Signatures (14 April 2023, 9h00-11h00):

Lecture notes ⬇

Hairer's perturbative approach to the KPZ equation (with mollified noise) known as Wild's expansion has a non-Markovian pendant, that relates non-trivially to the so-called diamond expansions of Alos-Gatheral-Radoičić (20) and the Lacoin-Rhodes-Vargas cumulant formula (22). We will provide a common generalization of these works, clarify their relation through forest reordering, and given an application to rough forward variance models. (Based on F-Gatheral-Radoičić, "Forests, cumulants, martingales." Ann. Probab. 2022). The second part is devoted to signatures, a beautiful piece of mathematics, that has gained much recent attention in finance (Buehler, Cuchiero, Dupire, Lyons, Teichmann ...). More specifically, I will present a non-commutative generalization of the afore-mentioned expansions, based on a type of infinite-dimensional Ricatti equation. This allows to compute recursively the logarithm of the expected signatures, a.k.a. signatures cumulants, in general semi-martingale models. (Based on F-Hager-Tapia. "Unified signature cumulants and generalized Magnus expansions." Forum Math. Sigma 2022.) Time permitting, I will also report on a related ongoing work with A. Seigal (Harvard) and T. Lyons (Oxford) on the non-polynomial nature of such expansions.

Abstract of Mini-Course 2 : Rough Path Pricing in Local Stochastic Volatility Models (21 April 2023, 9h00-11h00):

LSV models, widely used in the industry, are specified by their (possibly non-Markovian) SV process together with a leverage function. We describe partially conditioned dynamics via explicit (Markovian) rough stochastic differential equation. The conditional pricing problem can then treated by rough PDE methods. Upon suitable randomization of the driving rough paths and subsequent averaging, we return to the original pricing problem. This can be seen as extension / refinement of Romano-Touzi (97) and a recent SPDE pricing method for rough volatility of Bayer et al. Some rough idea about rough paths will be helpful, but we will introduce in the lecture everything we need. Ongoing joint work with P. Bank, C. Bayer and L. Pelizzari (all Berlin).

Cours de Marcel Nutz

(Université de Columbia)

Les Mardis à Campus Jussieu, salle 104 barre 15-25.

Introduction to Entropic Optimal Transport

19 Octobre26 Octobre23 Novembre30 Novembre
9h00-10h00Marcel Nutz C1Marcel Nutz C3Marcel Nutz C5Marcel Nutz C7
10h15-10h55Pierre BrasKatarina EichingerRoberta FlenghMehdi Talbi
10h55-11h35Mohan YangGeoffrey DerchuSongbo WangGiacomo Greco
11h50-12h50Marcel Nutz C2Marcel Nutz C4Marcel Nutz C6Marcel Nutz C8

Cours de Zorana Grbac et Claudio Fontana

(Université de Paris - LPSM et Université de Padoue)

les vendredis 01/04, 08/04 (matin et après-midi) et 15/04

Recent developments in interest rate modelling

Lecture notes ⬇


In the last 15 years the fixed-income markets have witnessed some profound changes. The credit crisis in 2007–2008 and the Eurozone sovereign debt crisis in 2009–2012 had a strong impact on these markets: the emergence of multiple interest rate curves depending on the tenor and the presence of persistently low and negative interest rates have irreversibly changed the way the fixed-income markets function in practice, as well as the way their theoretical models were developed. Moreover, a few years ago a major reform was undertaken, and is still ongoing, with the goal of providing more robust and more reliable benchmark rates to replace the LIBOR rates as reference rates in financial transactions.

Developing pertinent and up-to-date models for the dynamics of the term struc- ture of interest rates presents not only mathematical challenges due to the complex- ity and high-dimensionality of the problem, but is also of utmost importance for the financial industry. Fixed-income instruments represent by far the largest portion of the global financial market: according to the statistics provided by the Bank for International Settlements, the notional amounts outstanding for over-the-counter (OTC) interest rate derivatives sum up to several hundreds trillions of US dollars, which is more than three quarters of the total trade volume in OTC derivatives. The goal of this course is to provide an overview of the state-of-the art techniques used in modern interest rate modeling, addressing the above-mentioned challenges.

Outline of the course:

  1. A general overview of interest rate markets and basic notions;
  2. the multi-curve environment: terminology, basic traded assets, stylized facts of post-crisis interest rate markets;
  3. absence of arbitrage in a general multi-curve interest rate market;
  4. an overview of multi-curve modelling approaches (short rate models, HJM models, market models, rational models);
  5. a general multi-curve HJM framework;
  6. tractable models driven by affine processes and pricing aspects;
  7. the importance of stochastic discontinuities in interest rate dynamics;
  8. lecture by Fabio Mercurio: the Libor reform and its modelling aspects;
  9. term structure models for risk-free rates: a look at the recent literature, with a view on stochastic discontinuities;
  10. an extended HJM framework for overnight and term rates;
  11. an illustrative Vasiˇcek example with stochastic discontinuities;
  12. consistency between overnight rates and term rates;
  13. hedging with stochastic discontinuities.

Lecture notes: Cours 01/04 ⬇

Abstract of the lecture by Fabio Mercurio (8 April 2022, 15.15 - 17.15):

Interbank offered rates (IBOR) were, and still are, the key reference rates in many financial products with the total market exposure worldwide of hundreds of trillions of US dollars. Because of the inverted pyramid effect, as well as the reported cases of LIBOR manipulation, a few years ago, global authorities prompted the creation of new, more robust risk-free rate (RFR) benchmarks to be used in the majority of financial transactions. In the first part of this seminar, we’ll review some of the main decisions and actions taken by regulators and market participants to transition away from LIBOR.

In the second part of the seminar, we’ll define and model forward risk-free term rates, which appear in the payoff definition of derivatives and cash instruments based on the new RFR benchmarks. We show that the classic interest-rate mod- eling framework can be naturally extended to describe the evolution of both the forward-looking (IBOR-like) and backward-looking (setting-in-arrears) term rates using the same stochastic process. We then introduce an extension of the LIBOR Market Model (LMM) to backward-looking rates. This extension, which we call generalized forward market model (FMM), completes the LMM by providing addi- tional information about the rate dynamics between fixing/payment times, and by implying dynamics of forward rates under the classic money-market measure.

Cours de Antoine Jacquier

(Imperial College London)

les vendredis 03/06, 10/06, 17/06 et 24/06

Quantum Computing for Mathematical Finance

Introduction : Quantitative Finance is a rapidly changing environment, and the financial industry is always on the lookout for new techniques and new technologies able to harness the rise of big data and the availability of computing power.
Quantum computing, though not a recent field, has gained huge popularity in the past few years with the development of small-scale quantum computers and quantum annealers. These have in turn set directions for new algorithms, hybrid between classical and quantum, and tailored for such computers. The financial industry is now looking at such developments and there is common agreement that this will be one of the leading advances in the coming decade.
The goal of this Bachelier course is to provide an introduction to this new technology and these new algorithms and show them how they can be used to solve financial problems, in particular for portfolio optimisation, in the context of Machine learning and neural network and for PDE solving.

Plan : The course will tentatively walk along the following steps:

  1. Introduction to Quantum Mechanics and the basics of quantum computations
  2. Quantum neural networks
  3. Quantum solvers for (linear) systems and PDEs
  4. Adiabatic Quantum annealing for (portfolio) optimisation

Each lecture will focus on the theoretical aspects of the problem and the related algorithms and will further show some numerical examples in Jupyter notebooks.

Cours de Ivar Ekeland et Antoine Mandel

(Université Paris Dauphine et Université Paris 1 Pantheon Sorbonne)

les vendredis 10/01, 24/01, 07/02 et 14/02

Economics of climate change and Green Finance

Lecture notes ⬇

Cours de Sarah Kaakai, Nicole El Karoui et Stéphane Loisel

(LMM, Université du Mans, LPSM, Sorbonne Université, ISFA, Université Lyon 1)

les vendredis 28/02, 06/03, 13/03 et 20/03


Part 1: Point processes in random environment and application to the study of longevity risk, Sarah Kaakai (LMM, Université du Mans).

Point processes have received much attention in the recent years. Indeed, their flexibility allows for the modeling of a wide range of phenomena, in various fields including for instance biology, finance, insurance, population dynamics or neurosciences.

In this course, I will first present a general overview on representations of point processes with stochastic intensity, with a particular focus on pathwise representations as solution of stochastic differential equations with random coefficients, driven by Poisson random measures. This viewpoint is particularly well-suited to the study of interacting events occurring in a random environment, and of non-Markovian systems. I will show how strong comparison results can be derived from pathwise representations, as well as straightforward tightness results.

In a second part, I will apply these results in order to introduce a new class of heterogeneous population dynamics in random environment. Individuals (or companies) can enter or exit the population, as well as change characteristics, at stochastic rates depending on the whole population and on the random environment. I will show on this model how averaging results can be obtained for point processes in random environment, here when changes of characteristics occur at a faster timescale than entries and exits from/to the population. In particular, I will give a brief overview on the stable convergence, which is a powerful tool naturally extending the convergence in distribution in the presence of a random environment.

Finally, I will illustrate how such averaging results allow us to generate more realistic mortality models than standard demographic tools based on linear models, reflecting the heterogeneity of the underlying population and taking into account the macro environment.

Part 2: Longevity risk and quickest detection problem: from theory to practice, Nicole El Karoui (LPSM, Sorbonne Université) and Stéphane Loisel (ISFA, Université Lyon 1).

After recalling briefly key features of longevity risk,, we explain how to detect as quickly as possible the date where that the actuarial assumptions related to longevity risk are no longer valid.

The problem is put as a quickest detection problem. We introduce the so-called cusum process and show its optimality for a generalized Lorden criterion. We then explain how to design Key Risk Indicators thanks to the cusum process. We analyze its advantages and drawbacks for longevity risk monitoring, as well as for some other insurance risks. The method is illustrated on simulated and real-world case studies.

Lecture notes: Cours 28/02 ⬇, Cours 06/03 ⬇, Cours 13/03 ⬇

Cours de Adrien Richou et Sergey Nadtochiy

(Université de Bordeaux et Illinois Institute of Technology)


Cours de Mathieu Rosenbaum

(Ecole Polytechnique)

les vendredis 08/02 et 15/02

Rough volatility

Lecture notes: Part 1, Part 2, Part 3, Part 4.

Cours de David Salant

Joint lecture with FIME

(Toulouse School of Economics)

les vendredis 29/03, 05/04, 12/04 et 19/04

Auctions in the Energy Sector: An Introduction and Survey


  1. Introduction to auction theory
  2. Default service procurement
  3. Capacity Markets
  4. Transmission rights
  5. Renewable procurement

Cours de G. Peyré et M. Cuturi

les vendredis 07/06 (G. Peyré) et 21/06 (M. Cuturi)

Optimal Transport & Machine Learning

Cours de Stéphane Crépey

(Université d'Evry, CNRS, Université Paris-Saclay)

les vendredis 26/01, 02/02, 09/02 et 16/02

Analyse XVA

Lecture notes: Part 1, Part 2.

ABSTRACT: Since the crisis, derivative dealers charge to their clients various add-ons, dubbed X-valuation adjustments (XVAs), meant to account for counterparty risk and its capital and funding implications.

XVAs deeply affect the derivative pricing task by making it global, nonlinear, and entity dependent. However, before the technical implications, the fundamental points are to understand what deserves to be priced and what does not, and to establish, not only the pricing, but also the corresponding collateralization, dividend, and accounting policy of a bank.

If banks cannot replicate jump-to-default related cash ows, deals trigger wealth transfers from bank shareholders to creditors and shareholders need to set capital at risk. On this basis, we devise a theory of XVAs, whereby so-called contraliabilities and cost of capital are sourced from bank clients at trade inceptions, on top of the fair valuation of counterparty risk, in order to compensate shareholders for wealth transfer and risk on their capital.

The resulting all-inclusive XVA add-on, to be sourced from clients incrementally at every new deal, reads (CVA + FVA + MVA + KVA), where C sits for credit, F for funding, M for (initial) margin, and where the KVA is a cost of capital risk premium. This formula corresponds to the cost of the possibility for the bank to go into run-off, while staying in line with shareholder interest, from any point in time onward if wished.

Moreover, economic capital (EC) can be used as a funding source by banks, at a risk-free cost instead of the additional credit spread of the bank in the case of unsecured borrowing. This intertwining of EC and FVA leads to an anticipated BSDE (backward stochastic differential equation of the McKean type) for the FVA, with coefficient entailing a conditional risk measure of the one-year-ahead increment of the martingale part of the FVA itself.

Our XVA equations are solved by projection on a reduced filtration myopic to the default of the bank, the latter being assumed to be an invariance time as per Crépey and Song (2017). This assumption, which covers mainstream immersion setups (but not only), expresses the consistency of valuation across different trading desks with different focuses within the bank: the XVA desks versus the different business desks.

Finally, we present a nested Monte Carlo approach implemented on graphics processing units (GPU) to XVA computations. The overall XVA suite involves five compound layers of nested dependence. Higher layers are launched first and trigger nested simulations on-the-fly whenever required in order to compute a metric from a lower layer. With GPUs, error controlled nested Monte Carlo XVA computations are within reach. This is illustrated on XVA computations involving equities, interest rate, and credit derivatives, for both bilateral and central clearing XVA metrics.

Course material: Related papers on https://math.maths.univ-evry.fr/crepey/.

Cours de Benjamin Jourdain


les vendredis 23/03 et 30/03

Diffusions en interaction de champ moyen suivant le rang

ABSTRACT: Les particules diffusives interagissant suivant le rang permettent de modéliser les capitalisations boursières dans la théorie du portefeuille stochastique de Fernholtz. Nous nous intéresserons au cas particulier où l'interaction est en outre de type champ moyen : les coefficients de diffusion et de dérive de chaque coordonnée (ou particule) dépendent de la fonction de répartition empirique de l'ensemble des particules calculée en cette coordonnée. Nous étudierons tout d'abord la limite de champ moyen où le nombre de coordonnées tend vers l'infini. La fonction de répartition empirique tend alors vers la fonction de répartition de la loi marginale de l'équation différentielle stochastique limite qui est non linéaire au sens de McKean. Nous nous intéresserons ensuite au comportement en temps long de cette diffusion non linéaire en exploitant que la statistique d'ordre des particules est une diffusion à coefficients constants normalement réfléchie à la frontière du simplexe.

Nous interprèterons cette limite en temps long en théorie du portefeuille. Enfin, nous montrerons que la limite petit bruit du système de particules est donnée par la dynamique des particules collantes et nous étudierons la limite de cette dynamique lorsque le nombre de particules tend vers l'infini.

Cours de Huyên Pham

(Université Paris-Diderot)

les vendredis 06/04 et 13/04

Control of McKean-Vlasov equations

ABSTRACT: This lecture is concerned with the optimal control of McKean-Vlasov equations, which has been knowing a surge of interest since the emergence of the mean-field game theory. Such problem is originally motivated from large population stochastic control in mean-field interaction, and finds various applications in economy, finance, or social sciences for modelling motion of socially interacting individuals and herd behavior. It is also relevant for dealing with intermittence questions arising typically in risk management.

In the first part, I focus on the important class of linear-quadratic McKean-Vlasov (LQMcKV) control problem, which provides a major source for examples and applications. We show a direct and elementary method for solving explicitly LQMcKV based on a mean version of the well-known martingale optimality principle in optimal control, and the completion of squares technique. Variations and extensions to the case of infinite horizon, random coefficients and common noise are also addressed. Finally, we illustrate our results with an application to a model of interaction between centralised and distributed generation.

The second part is devoted to the presentation of the dynamic programming approach (in other words, the time consistency approach) for the control of general McKean-Vlasov dynamics. In particular, we introduce the recent mathematical tools that have been developed in this context: differentiability in the Wasserstein space of probability measures, Itô formula along a flow of probability measures and Master Bellman equation. Extensions to stochastic differential games of McKean-Vlasov type are also discussed.

Cours de Samson Lasaulce

Bachelier / Fime


les vendredis 18/05, 25/05, 01/06 et 15/06 (10h-11h)

Théorie des jeux : Outils de base et application aux réseaux sans fil et réseau d’électricité

PDF : Présentation du cours et de l'orateur

PDF : Supports de présentation

Cours de Charles-Albert Lehalle

(CFM & Imperial College London)

les vendredis 18/11, 25/11 et 2/12

Financial Intermediation at Any Scale for Quantitative Modelling

ABSTRACT: During this series of lectures, we will go from the role of the financial system described as a large network of intermediaries to a fine description of high frequency market makers. The role of regulation in the recent transformations of participants’ practices will be exposed too. The viewpoint taken is the one of a practitioner or a researcher who has to put in place models. Existing models will be reviewed, and new challenges and the stakes of possible improvements will be discussed. Important stylized facts and important mechanisms that models should reproduce will be exposed.



ABOUT THE AUTHOR: Charles-Albert Lehalle is Senior Research Advisor at Capital Fund Management (CFM, Paris) and a member of the CFM-Imperial Institute of Quantitative Finance. He was formerly Global Head of Quantitative Research at Crédit Agricole Cheuvreux, and Global Head of Quantitative Research on Market Microstructure in the Equity Brokerage and Derivative Department of Crédit Agricole Corporate Investment Bank.
With a Ph.D. And an HDR in applied mathematics Charles-Albert Lehalle lectures at the Pierre et Marie Curie "Probability and Finance" and the MASEF/ENSAE Masters in Paris.
Since the financial crisis, Charles-Albert has studied market microstructure evolution and regulatory changes in Europe and the US, and has provided research and expertise on these topics to investors, intermediaries and policy-makers such as the European Commission, the French Senate and the UK Foresight Committee. He has been a member of the Consultative Workgroup on Financial Innovation of the European Market Authority (ESMA) and is part of the Scientific Committee of the French regulator (AMF). Besides, he chairs Euronext’s Index Advisory Group, working on topics like Smart Beta and Factor Investing.
He has published many academic papers about the use of stochastic control and stochastic algorithms to optimize trading flows with respect to flexible constraints. He has also authored papers on post-trade analysis, market impact estimation and modelling the dynamics of limit order books. He co-authored the book "Market Microstructure in Practice".
and co-edited the book "Market Microstructure: Confronting Many Viewpoints", being co-organizer of the eponymous conference taking place every even year in December in Paris. Charles-Albert is one of the managing editors of the “Market Microstructure and Liquidity” academic journal.

Cours de Mihail Zervos

(London School of Economics)

les vendredis 7/4, 21/4, 28/4 et 5/5

Continuous time contract theory models

ABSTRACT: We consider a number of models involving two parties, a principal and an agent. In practice, the principal can be the owner of a firm and the agent can be a manager that is hired to run the firm's operations. The two parties may share the same information or not. The first of these two cases gives rise to a risk sharing problem in which the principal optimally determines the precise actions that the agent has to follow. The second one gives rise to a problem that may involve moral hazard in the sense that the agent can take actions that are not in the best interest of the principal. We develop a complete analysis of the models we consider, with emphasis on the important ideas underlying their analysis. The four lectures are structured to be relatively independent.

Cours de Johannes Muhle-Karbe

(University of Michigan)

les vendredis 12/5 et 19/5

Equilibrium models with frictions



Propagation of uncertainty

Cours de Pierre Del Moral


les vendredis 15/01, 22/01, 29/01 et 12/02

An introduction to Feynman-Kac integration and genealogical tree based particle models

Slides: Lecture 1, Lecture 2, Lecture 3, Lecture 4.
Labs (.sce): Lab 1, Lab 2.