Financial Markets - 203 - 2ème année de master

Ects : 3
Volume horaire : 24
Coefficient : 1.5
Compétence à acquérir :
Master the econometrics (dynamic) tools used in empirical finance

Description du contenu de l'enseignement :
Stationarity, autocorrelation, ARMA models, volatility models (GARCH, Stochastic volatility, Regime switching models ...)
To study the theory, modeling, programming, and interpretation of the major time series models

Enseignant responsable :

• SYLVAIN BENOIT

Ects : 6
Volume horaire : 24
Coefficient : Coefficient 1 (M2 Research in Finance)<br /> Coefficient 3 (M2 Financials Markets)
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.
Pré-requis obligatoires :
Basic probability theory, stochastic processes (martingales,...), stochastic calculus in continuous time (Brownian motion, Itô formula, Stochastic differential equations)

Description du contenu de l'enseignement :
Advanced derivative pricing and stochastic calculus.
This course requires that the students have validated the course "Finance in continuous time". Its gives more insights into the theory of derivative asset pricing as well as the main models and techniques used in practice.

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.

Enseignant responsable :

• PAUL GASSIAT

Ects : 3
Volume horaire : 24
Coefficient : 1.5
Compétence à acquérir :
Master econometrics (static) tools in empirical finance: factor models, risk premia, etc.

Description du contenu de l'enseignement :
Financial Data, Econometrics of Efficient frontier, CAPM to multifactor pricing models estimations
To offer an overview of mostly used econometrics tools and the way these methodologies can be used in empirical finance, both in investment banking and asset management.

Enseignant responsable :

• GUILLAUME MONARCHA

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Master financial en economics environement as well as the interactions between financial markets and the economy

Description du contenu de l'enseignement :
To describe the strong interactions between financial markets and the economy: from the economy towards markets and the reverse. Links between finance and economic policies, as fiscal policy, monetary policy and finance regulation.
Understand the financial and economics environment as well as the interactions between financial markets and the economy: from the economy towards markets and the reverse. Links between finance and economic policies, as fiscal policy, monetary policy and finance regulation.

Enseignant responsable :

• CONSTANCE BOUBLIL-GROH
• SIMON RAY

Ects : 3
Volume horaire : 30
Coefficient : 1.5
Compétence à acquérir :
Master the issues and tools in risk management
Mode de contrôle des connaissances :
Final Exam

Description du contenu de l'enseignement :
Risk Management, Sensitivities, VaR, Expected Shortfall, Stress testing, Counterparty Risk on Market Operations, Liquidity risk, Basel requirements, multivariate models, Extreme risks
Understanding the main issues and tools in risk management

Enseignant responsable :

• XAVIER BOCHER
• LAURENT DAHAN

Ects : 3
Volume horaire : 24
Coefficient : 1.5
Compétence à acquérir :
Knowledge in Python programming for empirical finance

Description du contenu de l'enseignement :
Python in finance : getting data, cleaning data, data vizualisation, econometrics, stochastic processes and finance applications. “scientific libraries” in Python: numpy, scipy, pandas, and matplotlib.
To provide students with the tools for financial data analysis in Python.

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Knowledge in C++ programming for finance

Description du contenu de l'enseignement :
C++ language and programming
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

Enseignant responsable :

• JOHAN MABILLE

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Knowledge of the history and evolution of the energy sector and its main drivers.

Description du contenu de l'enseignement :
Economics and geopolitics in the shaping of the global energy map and their impacts
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.

Enseignant responsable :

• GUILLAUME LEENHARDT

Ects : 3
Volume horaire : 18
Coefficient : 1.5
Compétence à acquérir :
Master usual transaction structures with a special focus on takeover bids and LBO transactions

Description du contenu de l'enseignement :
Mergers and Acquisitions
Give a first overview of Mergers & Acquisitions' issues and practice

Enseignant responsable :

• JEAN-LOUIS DUVERNEY-GUICHARD

Ects : 3
Volume horaire : 21
Coefficient : Coefficient 1 (M2 Research in Finance)<br /> Coefficient 1.5 (M2 Financial Markets)
Compétence à acquérir :
Master the regulatory prudential and market reforms, at the global level and across regions

Description du contenu de l'enseignement :
Financial regulation, prudential regulation around the world, regulation to "too big to fail" banks and fragmented environment
To give the students an overview of recent and future regulatory prudential and market reforms, at the global level and across regions.

Enseignant responsable :

• THIBAULT GODBILLON

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Practical knowledge to design quantitative investment strategies.

Description du contenu de l'enseignement :
Beta investments, Equity beta portfolio strategies, Bonds beta portfolio strategies, multi asset allocation approach
to deeply study beta (passive) investments across asset class, and to be able to design quantitative investment strategies to monetize views on factors (macro, curve and style)

Enseignant responsable :

• SCHLOMY BOTBOL
• BRICE PERIN

Ects : 3
Volume horaire : 24
Coefficient : 1.5

Enseignant responsable :

• NICOLAS RAYMOND
• PHILIPPE NARDONE
• ALEXANDRE LEDUC

Ects : 3
Volume horaire : 18

Enseignant responsable :

• NATHALIE COHEN

Ects : 3
Volume horaire : 24
Coefficient : 1.5
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

Description du contenu de l'enseignement :
Commodities spot prices models, Forward curves, Options pricing models (Futures options, real options)
Commodities investing (properties, indices, relations to other asset classes and hedge funds strategies)
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 iv) present risk measurement and stress testing principles for commodity portfolios.

Enseignant responsable :

• BENOIT GUILLEMINOT

Ects : 3
Volume horaire : 30
Coefficient : 1.5
Compétence à acquérir :
Master the mecanisms behind the credit risk products and their pricing models

Description du contenu de l'enseignement :
Duration And Convexity of Bond Yields, Price Dynamics of Mortgages and Cash Flows, Default Risk, Interest Rate Volatility, Financial Risk Management of Bond Portfolios, Securitization, Corporate Debt And The Securitization Markets, Asset-Backed Commercial Paper, Collateralized Loan Obligations, Structuring Synthetic Collateralized Loan Obligations, Securitization of Revolving Credit, Financial Derivatives And Their Use As Hedging Tools.
To provide a theoretical and practical analysis of credit risk markets and products

Enseignant responsable :

• Fabian ASTIC
• OLIVIER TOUTAIN

Ects : 3
Volume horaire : 24
Coefficient : 1.5
Compétence à acquérir :
Good technical knowledge of pricing models and computational methods for energy derivatives products

Description du contenu de l'enseignement :
Energy markets, pricing Spot and Forward models for electricity and gas prices, Vanilla energy derivatives, Structured derivatives and physical assets, Advanced computational methods for stochastic control in energy markets
To provide students with an overview of both the technical aspects of energy markets as well as the most commonly used price models for pricing energy derivatives.

Enseignant responsable :

• CLEMENCE ALASSEUR
• MARC RINGEISEN

Ects : 3
Volume horaire : 24
Coefficient : 1.5
Compétence à acquérir :
Master the theory and practice of Fi Income products pricing and hedging.

Description du contenu de l'enseignement :
Pricing and hedging of exotic rate products: Interest rate futures and bonds, Interest rate swaps, Zero coupon rate construction, Caps -Floors, Swaptions (pricing and smile), Volatility Surface/Cube, Bermudan swaptions, Callable bond and swap, Callable reverse floater, Callable snowball ... Models : HJM, Libor Market Model, Cheyette Model ...
To introduce issues and problems that arise regarding pricing and hedging of exotic rate products.

Enseignant responsable :

• HAFID AGOUZOUL

Ects : 3
Volume horaire : 24
Coefficient : 1.5
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...).

Description du contenu de l'enseignement :
From key features (data cleaning, cross-validation..) to machine learning models implementation (linear regression, tree-based techniques, neural networks..).
To provide students with an introduction to supervised machine learning and its applications to finance.

Enseignant responsable :

• THIBAUD VIENNE

Ects : 3
Volume horaire : 24
Coefficient : 1.5
Compétence à acquérir :
Master the technics, tools and strategies for alpha extraction

Description du contenu de l'enseignement :
Alpha in quantitative strategies. Alpha extraction tools. Risk premia. Volatility strategies.
To understand what Alpha is about (by opposition to beta) and what are the various form it can take when analysing and eventually replicating it through advanced methods in quantitative Investment strategies.

Enseignant responsable :

• GUILLAUME MONARCHA
• THIERRY BECHU
• THIERRY KUAGBENU

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Knowledge on the modelling methods specific to alternative finance.

Description du contenu de l'enseignement :
Products and technics used at the fringe of finance including crowfunding, peer-2-peer finance, shadow banking, Bitcoin, social and environmental impact products
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, etc. The course focuses 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.

Enseignant responsable :

• MARIUS FRUNZA
• OLIVIER TOUTAIN

Ects : 3
Volume horaire : 21
Coefficient : Coefficient 1 (M2 Research in Finance)<br /> Coefficient 1.5 (M2 Financial Markets)
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.

Description du contenu de l'enseignement :
Bevavioral finance, cognitive and social psychology in finance
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.

Enseignant responsable :

• ALBERTO MANCONI

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Advance the understanding and practice of electronic markets.

Description du contenu de l'enseignement :
Electronic financial markets, Trading cost analysis, optimal execution, high ferquency data, trading with limit orders, otpimal trding
To present 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.

Enseignant responsable :

• GAELLE LE FOL
• JIANG PU

Ects : 3
Volume horaire : 18
Coefficient : 1.5
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.

Description du contenu de l'enseignement :
Exotic options, structured products
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 (funded, or unfunded), how to hedge them and how to manage the life cycle.

Enseignant responsable :

• REDOUANE ZAD

Ects : 3
Volume horaire : 21
Coefficient : 1.5
Compétence à acquérir :
Master the modelling and numerical analysis of financial derivatives

Description du contenu de l'enseignement :
Modeling and numerical analysis of financial derivatives. Numerical methods needed for quantitative work in finance: binomial and trinomial methods, finite difference methods, Monte-Carlo simulation, random number generators, option pricing and hedging
Understanding the financial meaning of the related mathematics: model parameters, implied volatility, Greeks.

Learning how to derive a pricing equation based on the probabilistic formulation of a model, possibly with stochastic volatility and/or jumps,

Learning how to implement a theta-scheme of finite differences or a tree pricing method,

Learning simulation Monte Carlo pricing and Greeking methods: basic principles and variance reduction techniques, first in a set-up of random variables or vectors, then in a dynamic set-up of stochastic processes.

Enseignant responsable :

• TETE KAIZA AMOUH

Ects : 3
Volume horaire : 21
Coefficient : 1.5

Enseignant responsable :

• KENZA AKALLAL

Ects : 6