Ce MSc. Financial Markets est un programme international qui forme des spécialistes des marchés financiers exerçant leurs compétences au service des banques et entreprises d'investissement, des sociétés de gestion d'actifs, des cabinets de conseil, des compagnies d'assurance ou des grandes entreprises. La formation offre aux étudiants des connaissances approfondies, à la fois théoriques, quantitatives et opérationnelles, sur tous les produits négociés sur ces marchés.
L’accès au Master 2ème année est ouvert aux étudiants ayant validé en première session, le Master Finance 1ère année de Paris-Dauphine sous conditions :
Ce parcours peut être prolongé par une thèse de doctorat, notamment pour les étudiants se destinant à la recherche.
ECTS : 3
Description du contenu de l'enseignement :
We propose a deep dive into the factor investing universe, from its academic foundations to practical implementation. This course will consider two complementary perspectives, focusing on both:
Compétence à acquérir :
Master the technics, tools and strategies for alpha extraction
Mode de contrôle des connaissances :
Exam and group project
Group project: will consist in the construction and backtesting of systematic investment strategies, risk premia allocations, replication and application of research papers...
ECTS : 3
Description du contenu de l'enseignement :
The aim of this course is to propose an out-of the box perspective upon the financial markets and to explore the financial universe beyond the traditional investments like equity, bonds, currency… . We will focus the course on the products and technics used at the fringe of finance including crowfunding, peer-2-peer finance, shadow banking, Bitcoin, social and environmental impact products….
Throughout this course students will learn about alternative investment supports and alternative financing solutions. The objectives of this lecture are:
Compétence à acquérir :
Knowledge on the modelling methods specific to alternative finance.
Mode de contrôle des connaissances :
Project
Bibliographie, lectures recommandées :
ECTS : 3
Description du contenu de l'enseignement :
The objective of the course is to study the theory, modeling, programming, and interpretation of the major time series models. Some applications to finance will be undertaken using Python. At the end of this class, students should be able to :
Course outline:
1/ Time series building blocks
2/ ARMA Framework
3/ Specific topics and applications
4/ Volatility models
5/ Principal Component Analysis
Compétence à acquérir :
Master the econometrics (dynamic) tools used in empirical finance
Mode de contrôle des connaissances :
Assignment (30%) + Final Exam (70%)
Bibliographie, lectures recommandées :
Brooks C (2008), Introductory econometrics for Finance, Cambridge Univ Pr.
Brockwell, P.J. and Davis, R.A. (2002), Introduction to time series and forecasting, Springer Verlag.
Campbell J., Lo A., McKinley, A. (1997), The Econometrics of Financial Markets. NJ: Princeton University Press.
Francq C, Zakoïan J.M. (2010), Garch models: Structure, statistical inference and financial applications, Wiley.
Hamilton J. D. (1994), Time Series Analysis, Princeton University Press.
ECTS : 3
Description du contenu de l'enseignement :
Introduce students to this relatively new sub-discipline of finance which incorporates insights from cognitive and social psychology into finance. In the past 20 years behavioral finance has emerged as an important stream of thinking in finance. Relaxing the traditional assumptions of finance models has proved a fruitful way of understanding financial decision-making.
Course outline:
The course will go through:
Compétence à acquérir :
Relaxing the traditional assumptions of finance models has proved a fruit ful way of understanding financial decision-making and anomalies found in empirical tests.
Mode de contrôle des connaissances :
Students will present a state-of-the art research paper among a selection of papers chosen by the instructors.
Bibliographie, lectures recommandées :
Daniel Kahneman, Paul Slovic, and Amos Tversky (eds.), Judgment under uncertainty: Heuristics and biases, Cambridge: Cambridge University Press, 1982.
Richard Thaler, ed., Advances in behavioral finance, New York: Russell Sage Foundation, 1993.
Richard Thaler, ed., Advances in behavioral finance, Volume II, New York: Russell Sage Foundation, 2005.
Shleifer, Inefficient markets : an introduction to behavioral finance, Oxford, Oxford University Press 2000.
ECTS : 3
Description du contenu de l'enseignement :
This practical oriented course focuses on learning C++ language as a practical tool. It aims to be both an introduction to C/C++ and a basic course for whoever want to get an expertise in programming. A special care to practice is taken through solving simple issues C++ as a tool ; no special programming background is expected. The 2 last courses are dedicated to advanced topics, not mandatory to learn the language, but important for people with programming background especially C programmers. A good grasp of the previous lessons will be required.
Course outline:
1. The basics
Compétence à acquérir :
Knowledge in C++ programming for finance
Bibliographie, lectures recommandées :
Beginners:
Stanley B.Lippman, Josee Lajoie, Barbara Moo, "C++ Primer ", Fifth Edition, 2012.
Koenig A. & B. E. Moo, "Accelerated C++", Addison-Wesley, 2000
Reference guides:
Bjarne Stroustrup, "The C++ Programming Language", Fourth Edition, 2013.
Nicolai M. Josuttis N. M., "The C++ standard library" 2nd edition, Addison-Wesley, 2012
Scott Meyers, “Effective STL”, Addison-Wesley, 2001
Online Gurus:
http://www.drdobbs.com/
ECTS : 3
Description du contenu de l'enseignement :
Commodity markets have experienced exceptional turmoil over the last 20 years. The arrival of new players in futures markets has drastically changed the behavior of commodities prices, connecting them to equity and currency markets. The objective of this course is to provide an economic understanding of the latest developments in commodity markets, grasp the financial, social and regulatory challenges behind commodity investing as well as the necessary concepts and tools to i) evaluate and hedge business exposure to commodities price fluctuations, ii) construct physical or paper trading strategies on commodities markets, iii) price and hedge complex commodity derivatives (on paper contracts or spot price) iv) present risk measurement and stress testing principles for commodity portfolios.
Course outline:
Compétence à acquérir :
Deep understanding of the latest developments in commodity markets, grasp the financial, social and regulatory challenges behind commodity investing as well as the necessary concepts and tools
Mode de contrôle des connaissances :
Final exam
Bibliographie, lectures recommandées :
Eydeland A., Wolyniec K., Energy and Power Risk Management : New Developments in Modeling, Pricing, and Hedging, WileyEurope (2003).
Geman H., Commodities and Commodity Derivatives : Modelling and Pricing for Agriculturals, Metals and Energy, Wiley Finance (2005).
Intelligent Commodity Investing, edited by H.Till and J. Eagleeye, Riskbooks (2007).
Risk Management in Commodity Markets, edited by H.Geman, Wiley ed (2008).
ECTS : 3
Description du contenu de l'enseignement :
Part 1 : O. Toutain (18h)
The objectives of this cours is the following:
Compétence à acquérir :
Master the mecanisms behind the credit risk products and their pricing models
Mode de contrôle des connaissances :
Bibliographie, lectures recommandées :
Textbooks
Options, Futures and Other Derivatives (6th Edition), Prentice Hall, 2005
By John C. Hull
Credit Risk : Modeling, Valuation and Hedging, Springer Finance, 2002
By Tomasz R. Bielecki, Marek Rutkowski
Articles
Altman, Edward, Andrea Resti, and Andrea Sironi, "Default Recovery Rates in Credit Risk Modeling: A Review of the Literature and Empirical Evidence", Economic Notes, Vol. 33, No. 2, (July 2004), pp. 183-208.
Jarrow, Robert A. and Stuart M. Turnbull. "Pricing Derivatives on Financial Securities Subject to Credit Risk", Journal of Finance, Vol. L, No. 1, Cornell University, and Queen's University (Canada) (Mar-1995), pp. 53-85.
Hull, John and Alan White, "The Impact of Default Risk on the Prices of Options and Other Derivative Securities", Journal of Banking & Finance, Vol. 19, No. 2, (May 1995), pp. 299-322.
Duffie, Darrel, Lasse Hefe Pedersen and Kenneth J. Singleton, "Modeling Sovereign Yield Spreads: A Case Study of Russian Debt", Journal of Finance, (February 2003), Vol. LVIII, No. 1, pp. 119-159.
Elliott, Robert J., Monique Jeanblanc, and Marc Yor, "On Models of Default Risk", Mathematical Finance, Vol. 10, No. 2, (April 2000), pp. 179-196.
Schönbucher, Philipp J., "Term Structure Modelling of Defaultable Bonds", The Review of Derivatives Research, Vol. 2, No. 2/3 (Fall-1998), pp. 161-192.
Heath, David, Robert Jarrow, "Bond pricing and the Term Structure of Interest Rates: A Discrete Time Approximation", Journal of Financial and Quantitative Analysis, Vol. 25, No. 4, Cornell University, University of Illinois at Chicago, (December-1990), pp 419-440.
Jarrow, Robert A., and Stuart M. Turnbull. "Pricing Derivatives on Financial Securities Subject to Credit Risk", Journal of Finance, Vol. L, No. 1, Cornell University, and Queen's University (Canada) (Mar-1995), pp. 53-85.
ECTS : 6
Description du contenu de l'enseignement :
The aim of this lecture is to present the theory of derivative asset pricing as well as the main models and techniques used in practice. The lecture starts with discrete time models which can be viewed as a proxy for continuous settings. We then develop on the theory of continuous time models. We start with a general Itô-type framework and then specialize to different situations: Markovian models, constant volatility models, local and stochastic volatility models. For each of them, we discuss their calibration, and the valuation and the hedging of different types of options (plain Vanilla and barrier options, American options, options on realized variance,...).
Course outline:
I. Discrete time modelling
I.1. Financial assets I.2. The absence of arbitrage I.3. Pricing and hedging of European options I.4. Pricing and hedging of American options
II. Continuous time modelling
II.1. Financial assets as Itô processes II.2. The Black-Scholes model II.3. Markovian models in complete markets II.4. Local volatility models II.5. Stochastic volatility models
Compétence à acquérir :
The lecture starts with discrete time models which can be viewed as a proxy for continuous settings, and for which we present in detail the theory of arbitrage pricing. We then develop on the theory of continuous time models. We start with a general Itô-type framework and then specialize to different situations: Markovian models, local and stochastic volatility models. For each of them, we discuss the valuation and the hedging of different types of options : plain Vanilla and barrier options, American options, options on realized variance, etc. Finally, we present several specific volatility models (Heston, CEV, SABR,...) and discuss their specificities.
Mode de contrôle des connaissances :
Final exam
Bibliographie, lectures recommandées :
Bouchard B. et Chassagneux J.F., Fundamentals and advanced Techniques in derivatives hedging, Springer, 2016.
Lamberton D. et B. Lapeyre, Introduction au calcul stochastique appliqué à la finance, Ellipses, Paris, 1999.
ECTS : 3
Description du contenu de l'enseignement :
To share with students the combined, yet distinct, importance of economics and geopolitics in the shaping of the global energy map, and how these can in turn trigger long term effects globally on both society and economy as a whole.
The course will also elaborate on the recent "financiarisation" of the energy sector and its related impact.
Course outline:
The course starts with a review of the key historical periods of the energy industry and the progressive shaping of today's energy sector, especially for the period starting from the decolonisation to today's resource nationalism period.
It will focus on the evolution of the global supply/demand equation, its specificities for the major energy resources as well as its relative impact (together with that of economic theory) on resource valuation.
It will then elaborate on the major changes in the recent shaping of the energy industry, with the emergence of new Major energy firms, the quest for ever more difficult production areas and technologies and the role of pioneer oil companies.
Throughout the course, the ever-growing involvement of the financial industry in the energy sector will be highlighted.
The course will then invite energy sector specialists to share with students their experience and views on some of the key aspects and issues:
Compétence à acquérir :
Knowledge of the history and evolution of the energy sector and its main drivers.
ECTS : 3
Description du contenu de l'enseignement :
This course is a presentation of financial markets, trading mechanisms and their evolution dedicated to advancing the understanding and practice of electronic markets. A particular attention will be dedicated to optimal trading and execution technics but also on the use of algo trading startegies by market participants (who do what).
Compétence à acquérir :
This course is a presentation of financial markets, trading mechanisms and their evolution dedicated to advancing the understanding and practice of electronic markets. A particular attention will be dedicated to optimal trading and execution technics but also on the use of algo trading startegies by market participants (who do what).
Bibliographie, lectures recommandées :
ECTS : 3
Description du contenu de l'enseignement :
The purpose of this course is to provide students with an overview of both the technical aspects of energy markets (generation, demand, constraints, market organization) as well as the most commonly used price models for pricing energy derivatives.
Attention is given to specific energy derivatives (Swing options and powerplants) and computational methods needed are detailed.
Course outline:
Compétence à acquérir :
Good technical knowledge of pricing models and computational methods for energy derivatives products
Mode de contrôle des connaissances :
Final exam
Bibliographie, lectures recommandées :
Clewlow L. & Strickland S., Energy Derivatives: Pricing & Risk Management, Lacima Group Pub., 2000.
Eydeland A. & Woliniec K, Energy and Power Risk Management: New Developments in Modelling, Pricing and Hedging, Wiley, 2007.
Géman H., Commodities and commodity derivatives: modelling and pricing for agriculturals, metals and energy, Wiley, 2005.
ECTS : 3
Description du contenu de l'enseignement :
Course objectives
Conducting business in the financial sector means conducting business with highest standards of ethics and in accordance with the laws and regulations of the countries where the business is done.
The course’s objectives are
· to understand the importance of ethics and professional standards when conducting business in the financial sector;
· to get a basic knowledge of the regulation and laws;
· to understand the main compliance concepts applied in Corporate & Investment Banks
Part 1. Ethical and Professional Standards
This part offers a pragmatic approach of ethics in finance, pointing out some of the recent issues that emerged since the financial crisis.
The course takes as a starting point some of the recent codes of conduct issued by the finance industry as well as CFA Institute® Code of Ethics and Standards of Professional Conduct; it then turns to concrete issues such as rate-rigging, toxic assets or liabilities, product structuring, investor protection, as well as some of the recent regulation. Topics are covered through presentations in class, student presentations, exercises and case studies. Student presentations are delivered individually, in class, under a pre-set format, and are part of the participation grade. As a prerequisite, students must be familiar with CFA Institute® Code of Ethics and have prepared an example of a standard violation and corrective action for the first class.
Part 2. Global Compliance
Main objectives are giving students a global overview on the main Compliance concepts applied in a Corporate & Investment Bank and emphasizing the latest trends in regulatory environment. Theoretical courses and practical examples will be exposed to students on the main Compliance and Financial Security themes met in a Corporate & Investment Bank.
· Compliance: privileged information, information barriers, conflicts of interests, market abuse and insider trading, suitability, reputation risk, etc...
· Financial Security: KYC, KYB, and implementation of the European 3rd Directive ; embargos, countries on watch lists, combating money laundering, fraud prevention.
Course outline
Introduction Course: Regulation today - for a better understanding of Ethics and Compliance (3h)
· Evolution of regulation and where we are now
· Linkage between the directives
· Comparison EU/rest of the world
Part 1. Ethical and Professional Standards
Session 1-Course Introduction: (1h)
Why do ethics matter? How to prepare a presentation, a case study, an exercise?
Exercise on Standard violations: (Using CFA Institute® Code of Ethics and Standards of Professional Conduct) Debrief on the example prepared by each student for and before Class 1.
Session 2- What do Codes of ethics and Codes of conducts tell us? (2h)
Compare 2 different codes: what is the focus? How well do they protect clients? other stakeholders? Identify what codes teach us about business ethics, operational risks, reputation risk.
Session 3- FX rate-rigging & other benchmarks (2h)
The FX rate-rigging scandal – FX markets Codes of conduct. Importance of trust in benchmarks.
Session 4- Libor rate-rigging & other benchmarks (2h)
The Libor manipulation scandal–Libor administration before/after the scandal.
Regulation on benchmarks and indice
Compétence à acquérir :
Demonstrate ethical awareness when conducting business in the financial sector, as well as the ability to understand the main compliance concepts applied in Corporate & Investment Banks.
Mode de contrôle des connaissances :
Participation and Final exam
Bibliographie, lectures recommandées :
Lewis M. , The Big Short, 2011. Flash Boys, 2014
O’ Malley C. : The story of the Eurobond Markets (ch. 10-11), 2015
CFA Institute® Code of Ethics and Standards of Professional Conduct
CFA Institute® Standards of Practice Handbook, 2014 edition
ECTS : 3
Description du contenu de l'enseignement :
Structured Products offer tailor made investment solutions which can combine equities, currencies, commodities, credit or interest rates to meet specific investor’s needs in term of expected returns, frequency of cash flows and investment horizons and respect constraints such as risk level and specific legal and fiscal aspects.
The most known Structured Products (Linked Notes) are based on exotic optional component to achieve their investment objectives.
The last financial crisis leads to important changes in rules and regulations with regard to investor protection (MiFID II). A first effect was the simplification of Structured Products destined to retail market. Today Sophisticated products concern only the most discerning customers (institutional and client of private banks)
The course will recall some key elements in fixed income and derivatives to concentrate first on exotic payoffs and then structured products. We will have a review of products from each main asset class. We will learn how to build them, how to hedge them, how to manage the life cycle and how to insure liquidity and create a secondary market. At the end of the course we will look to regulatory aspects, the cost of capital and liquidity and distribution rules.
The course includes the uses of online pricer and simulations.
Course outline:
Compétence à acquérir :
Knowledge in structured products: how to build them (funded, or unfunded), how to hedge them and how to manage the life cycle.
Mode de contrôle des connaissances :
Bibliographie, lectures recommandées :
ECTS : 3
Description du contenu de l'enseignement :
The last ten years have seen an extraordinary growth in the use of quantitative methods in financial markets. Professionals now use sophisticated statistical techniques in portfolio management, proprietary trading, derivative pricing, risk management and securities regulation. This course has two main objectives. The first one is to offer an overview of mostly used econometrics tools, and some of their developements in the machine learning area: moment estimation, linear factor models, dynamic linear models, latent factor models, numerical simulations, model selection, clustering. The second one is to highlight the strong link between academic research and their practical implementation in various fields – portfolio construction, asset pricing, fund analysis, performance evaluation, quantitative investment strategies, factor investing, backtesting – through the analysis of research papers and applications into Python.
Course outline:
Lecture 1 - An Overview of Financial Data
Compétence à acquérir :
Master econometrics (static) tools in empirical finance: factor models, risk premia, etc.
Mode de contrôle des connaissances :
Final Exam
Bibliographie, lectures recommandées :
ECTS : 3
Description du contenu de l'enseignement :
The objective of this course is to describe the strong interactions between financial markets and the economy:
Compétence à acquérir :
Master financial en economics environement as well as the interactions between financial markets and the economy
Mode de contrôle des connaissances :
Bibliographie, lectures recommandées :
Frederic S. Mishkin « Economics of Money, Banking, and Financial Markets »
Carmen M. Reinhart & Kenneth S. Rogoff « This Time Is Different: Eight Centuries of Financial Folly »
ECTS : 3
Description du contenu de l'enseignement :
The course is intended to be both theoretical and practical; its purpose is to introduce issues and problems that arise regarding pricing and hedging of exotic rate products. Specific examples of pricing and hedging will be dealt with. Concepts of DELTA and GAMMA/VEGA HEDGING will also be studied during the course. Recent advances in interest rate modelling will be introduced.
Course outline :
Compétence à acquérir :
Master the theory and practice of Fi Income products pricing and hedging.
Mode de contrôle des connaissances :
Final exam
Bibliographie, lectures recommandées :
Brigo D. and F. Mercurio, Interest Rate Models-Theory and Practice With Smile, Inflation and Credit, Springer-Verlag Berlin and Heidelberg GmbH & Co. K; Édition : 2nd Revised edition 2005, 1037 pages.
ECTS : 6
ECTS : 3
Description du contenu de l'enseignement :
The objective of the course is to provide students with an introduction to supervised machine learning and its applications to finance.
At the end of the course, students will be able to implement a whole machine learning pipeline in Python. From key features (data cleaning, cross-validation..) to machine learning models implementation (linear regression, tree-based techniques, neural networks...).
Live-coding and practicing also are main features of the course.
Students will be asked for multiple hours labs and a machine learning competition evaluation.
Course outline:
Session 1: Machine learning in finance.
Session 2: Linear and Logistic regressions.
Session 3 : Machine learning in practice.
Labclass 1: Financial news impact on Dow Jones index.
Session 4: Tree-based methods.
Session 5: Feedforward neural networks.
Labclass 2: Machine learning competition.
Compétence à acquérir :
Be able to implement a whole machine learning pipeline in Python. From key features (data cleaning, cross-validation..) to machine learning models implementation (linear regression, tree-based techniques, neural networks...).
Mode de contrôle des connaissances :
Machine learning competition (50%), final evaluation (50%).
Bibliographie, lectures recommandées :
Trevor Hastie, Robert Tibshirani, Jérôme Friedman (2009), The elements of statistical learning, (Springer).
Tuffery S. (2011), Data mining and statistics for decision making, (Wiley).
Hinton Geoffrey (2014), Neural networks for machine learning, Toronto University.
Ng Andrew (2014), Machine Learning, Stanford University.
ECTS : 3
Description du contenu de l'enseignement :
Course outline:
Class #1: Introduction to M&A
Class #2: Basic valuation and structure
Class #3: Buy-side versus sell-side M&A
Class #4: Excel Models, business planning, auditing of a spreadsheet
Class #5: Takeover Bids and LBO transactions
Class #6: Negotiations
Compétence à acquérir :
Master usual transaction structures with a special focus on takeover bids and LBO transactions.
Mode de contrôle des connaissances :
- 45min multiple-choice questionnaire
- No documents allowed
- 1 case study
Bibliographie, lectures recommandées :
ECTS : 3
Description du contenu de l'enseignement :
The course bears on the modeling and numerical analysis of financial derivatives. The objectives are:
Compétence à acquérir :
Master the modelling and numerical analysis of financial derivatives
Mode de contrôle des connaissances :
Bibliographie, lectures recommandées :
Crépey S., Computational Finance Lecture Notes, 2009 edition, 188 pages, available on http://www.maths.univ-evry.fr/crepey
Lamberton D. and Lapeyre P., Introduction to Stochastic Calculus Applied to Finance. Chapman & Hall, 2nd revised edition, 2007.
Shreve S., Stochastic Calculus for Finance II, Springer Finance, 2008.
Hull J., Options, Futures, and Other Derivative Securities, Prentice-Hall, 7th edition, 2009.
ECTS : 3
Description du contenu de l'enseignement :
This intermediate-level Python programming course is designed to deepen your understanding of Python and enhance your programming skills for a career in quantitative finance. After introducing the foundational concepts of the Python programming language, this course delves into more advanced topics and techniques. You will learn about object-oriented programming (OOP) principles and advanced data structures, as well as essential computer science concepts to profile and write more efficient code. The course will also enable you to write more elegant code, maintain code written by others, and take advantage of the growing popularity of LLMs to code faster. Through practical hands-on exercises, you will develop the ability to design and implement complex Python applications while also gaining proficiency in utilizing external libraries and modules. By the end of this course, you will be equipped with the skills necessary to tackle more challenging programming tasks and create robust and maintainable Python programs.
Program
* Week 1 Introduction to Python, grammar, syntaxis, history, binary arithmetic, good-practices, basic data-structures.
* Week 2 NumPy, Matplotlib, Pandas.
* Week 3 Parallel programming - Polars and Dask
* Week 4 Object Oriented Programming
* Week 5 Algorithm Analysis and Numerical Optimization (SciPy)
* Week 6 Webscraping and APIs
* Week 7 Calling C code from Python
* Week 8 LLMs and Code profiling.
Compétence à acquérir :
Knowledge in Python programming for career in quantitative finance
Mode de contrôle des connaissances :
Final Exam 70 % - Class Projects 20 % - Attendance (10%).
Recommended prior knowledge
Basic concepts of programming, statistics, linear algebra and convex optimization.
Bibliographie, lectures recommandées :
Mandatory literature: Mandatory installation:
Python 3.9 and other pydata libraries from Anaconda: https://www.anaconda.com/distribution/
An IDE like VSCode to run python code https://code.visualstudio.com/
Pre-requisite:
Recommended material if the student has no experience coding: 1 hour Python beginner tutorial - See the vide
ECTS : 3
Description du contenu de l'enseignement :
Banks, and the financial sector more broadly, operate in a highly regulated environment. Financial regulations have evolved over time, in response to key events, such as the 2008 Global Financial Crisis, emerging risks (e.g., data, cyber security, FinTech, etc) and more recently the COVID19 pandemic, or the failure of SVB and Credit Suisse.
Regulations have broadened to encompass all parts of the financial system: banks and non-banks—insurers, market infrastructures, credit rating agencies, hedge funds, etc. Global policymakers (including BCBS, FSB, IOSCO) have developed international standards to support the G20 mandate—ensuring the stability and resiliency of the global financial system. At the local and regional level (in the EU for instance), prudential and market regulators are tasked with transposing these global standards in their own framework, which may cause some variations in the way regulations are implemented across jurisdictions.
This lecture aims to provide students with an understanding of the global regulatory architecture, ensure they understand where regulations come from, and how to stay up-to-date with a complex and constantly evolving topic. The course will also provide students with an overview of the current rules and regulations applying to banks and financial market operators in general. Via the drafting of a two-page note on a specific topic from the course, students will practice their written English communication and capacity to summarise complex matters. Finally, via the participation of experts from various background, the course will provide students with an insight into working for global organisations.
Course outline:
1) An introduction to financial regulations
2) Prudential regulations (Basel standards, CRD/CRR, DFA)
3) Crisis management (FSB standards, BRRD/CMDI, DFA)
4) Overview of Market regulations (International standards, MIFID/EMIR)
5) Sustainable Finance (Key risks, FSB/BCBS standards, EU taxonomy/GBS/ SFDR)
6) Digital Finance (Key risks, FSB/BCBS standards, DORA/MiCAR)
7) Outro (Wrap-up, critical considerations on financial regulations)
Compétence à acquérir :
Master the regulatory prudential and market reforms, at the global level and across regions
Mode de contrôle des connaissances :
Each students will be asked to prepare a two page note aimed at summarising a key issue of the programme.
ECTS : 3
Description du contenu de l'enseignement :
Part 1 (L. DAHAN – 18h) : Risk management in practice
The Part 1 objective is to understand the issue of risk management. The principal ways of understanding and learning about risk are considered. Greeks computation is used to explain the daily P/L in a normal trading environment. The VaR is used to take into account market tail events while stress testing highlights performance under extreme market conditions. In a similar measure the course attempts to present the counterparty risk for market operations. This course shows also how all these measures come within the framework of the Basel Accords (3 pillars, regulatory capital requirements...)
Part 2 (X. BOCHER – 12h) : Mathematical framework of market risk measures and its limits
The Part 2 objective is to go deeper into Risk Measures introduced in Part 1, from a mathematical prospective (main measures, properties, limits, implementation). Then the course leads to the identification of main empirical sources of market risks and introduces more sophisticated models that allow to take into consideration those sources of risks. Within this framework, topics will be firstly introduced through empirical observation of data ("Stylized Facts") to lead to modeling answers and their application for risk management purpose.
Course outline:
Part 1 : Risk management in practice
Compétence à acquérir :
Master the issues and tools in risk management
Mode de contrôle des connaissances :
Final Exam
Bibliographie, lectures recommandées :
Cherubini U., E. Luciano and W. Vecchiato, 2004, Copula Methods in Finance, Wiley, 310 pages.
Roncalli T., 2009, La Gestion des Risques Financiers, Economica (2ème édition), Collection Gestion, 455 pages.
ECTS : 3
Description du contenu de l'enseignement :
Course objectives
“85% of our success accounts from soft skills and emotional intelligence, yet we only pay attention to them 10% of the time."
The result of this study conducted by Stanford university, amongst many others, highlights the importance of increasing our focus on soft skills on the road to professional and personal success.
Whether for the purpose of a successful first round HR interview, the fluidity of colleague and client relationships at a first entry job, or the integrity with which one treats themselves and other people - the soft skill module offers you a space of contemplation on emotional intelligence and interpersonal relationships, and its importance in your long term career.
This module is not a practical preparation for interviews, but rather a space of reflection on how to know yourself and accept yourself in your strengths and areas of development, so that you may apprehend your interview rounds, your career path, as well as your personal life with integrity, strength and authenticity.
"Your level of success will seldom exceed your level of personal development, because success is something you tract by the person you become” - Jim Rohn
Course outline
Part I –Interactive workshops on Authentic Leadership, 1 session of 3h and 6 sessions of 1h30 each.
· Emotional intelligence: Group interactive work on emotion & awareness, stress & confidence, emotional intelligence, inter&intra-personal relationships, challenges & opportunites at work
· Clarity = Power: Who am I ?, Identifying your Talents and Resources
· Emotions Management: Brain plasticity, Face your fears
· Communication: Projection and Intuition, Story Telling
· Authentic Leadership & Critical Thinking: Ability to Learn & Transmit, Decision-Making Power
· Team Work: Flexibility and Collective Intelligence, Win-Win Negotiation
· Mindfulness & Positive Attitude: Active Listening, Personal and collective growth
Part II - Discovery and practice of the process of NonViolent Communication according to Marshall Rosenberg over 6 sessions of 1h30 each.
· Listening to yourself
- Observe one's thoughts & judgements and translate them into needs.
- Distinguishing facts/obs. from our interpretations/ judgments
· Listening to each other
- Offering non-directive listening, with empathic reflection in Feeling & Need
- Accepting a difficult message: against oneself, against the other, with oneself, with the other
· Dialogue practice
- Alternating self-expression and listening to others
- Elaborate a solution that considers the needs of each person
Mode de contrôle des connaissances :
No Exam
Bibliographie, lectures recommandées :
ECTS : 3
Description du contenu de l'enseignement :
The past years have seen a marked shift in society’s attitudes toward sustainability. This shift is spurring political pressure, a regulatory push and technological advancements to create the foundations of a more sustainable world, leading to a change in investor behaviour and setting in motion a major yet gradual capital reallocation. Society’s long transition toward the practice of sustainable investing is likely to drive market adjustments for years and even decades.
In this course, we have a curated a series which will enable you to learn the basics and get started in the sustainable investing landscape, while providing you an opportunity to discover insights, data and tools across asset classes that are evolving the markets.
Course outline:
Part 1: What is Sustainable Investing and why does it matter? --- 3h
1.1. Big picture - why sustainable development matters?
1.2. Evolving regulatory landscape
1.3. Recent market trends and strategy
1.4. Measuring sustainability
1.5. Limitations and challenge
Part 2: Sustainability’s challenge to corporates --- 3h
2.1. Externalities
2.2. Governance and behaviour
2.3. Strategy and intangibles - changing business models
2.4. Integrated reporting - metrics and data
Part 3: Approaches of data analysis --- 6h
3.1. ESG metrics methodology
3.2. Data availability, data quality and usage
3.3. Identification of material information
3.4. New tools and technology
Part 4: Financing Sustainability --- 6h
4.1. Investing for long-term value creation
4.2. Equity - Engagement and Stewardship, ESG integration in valuation
4.3. Bonds - investing without voting power
4.4. Alternatives - approach to sustainable investing in real assets
4.5. Banking - new forms of lending
4.6. Insurance - managing long-term risk
4.7. Market view - risk/return assessment
Part 5: How to get there? --- 3h
5.1. Current state of the market and financial institutions commitments
5.2. Next steps
5.3. Conclusion
Compétence à acquérir :
In this course, we have a curated a series which will enable you to learn the basics and get started in the sustainable investing landscape, while providing you an opportunity to discover insights, data and tools across asset classes that are evolving the markets.
Bibliographie, lectures recommandées :
Schoenmaker D. and W. Schramade, Principles of Sustainable Finance, Oxford University Press, 432 pages, 2018.
ECTS : 3
Description du contenu de l'enseignement :
The objective of the course is to give in-depth knowledge about Volatility Trading Strategies.
The goal is to provide participants with the various uses of volatility, its dynamics, the instruments to trade it, the risks embedded in and how to avoid classic pitfalls about volatility.
We will cover main instruments to trade Volatility (from vanilla options to more complex products as Conditional Variance swaps or Vix Options) and how to manage them in the various volatility strategies (Vega/Gamma Trades, Relative Value Trading, Risk Overlay, Cross-Asset volatility arbitrage strategies, Convertible Bonds Arbitrage, Variance Trades, Dispersion…).
Course outline:
Compétence à acquérir :
Practical knowledge to design quantitative investment strategies.
Bibliographie, lectures recommandées :
Bennett C. (2012), Volatility Trading, Santander Research Notes
Cochrane, J.H.(2005), Asset Pricing, Revised Edition, Princeton University Press.
Demeterfi, Derman, Kamal & Zou, (1999), More Than You Ever Wanted to Know About Volatility Swaps, GS Research Notes
Hull, J. (2006), Options, futures and other derivatives, 6th ed., Pearson Prentice Hall
Ilmanen, A. (2011), Expected returns, Wiley Finance.
MacDonald R. L. (2006) Derivatives Markets, 2nd ed., Addison Wesley
Riva, F. (2008) Applications financières sous Excel en Visual Basic, 3ème éd., Economica.
Taleb, N. (1997) Dynamic Hedging: Managing Vanilla and Exotic Options, Wiley