DegreeInternational
Webinar – General presentation & application procedures for Masters taught in English
The aim of the Advanced Studies and Research in Finance (ASRF) program is to train graduates with a strong background in financial analysis in an international context, as well as specialists in quantitative financial management and market finance. The program prepares students for the CFA (Chartered Financial Analyst) exam.
It provides professional opportunities in consulting and research (fundamental or applied), both in the academic sphere (universities, business schools) and in financial organizations (banks, insurance companies, financial institutions, etc.).
The specificity of the program is to combine intensive French language courses (240 hours) with a comprehensive academic program in Finance taught exclusively in English.
The program is designed to train both French and foreign students who are interested in an international career in finance. This is the reason why all the courses are taught in English based on international course formats ( project-based).
The lecturers use international financial databases (Bloomberg) and their teaching is based on international standards and regulations in terms of risk management (banking risks in particular), financial markets and accounting.
The program provides in-depth knowledge in the traditional fields of finance: market finance, corporate finance, risk management, financial markets, banking management….
At the end of the program, students are familiar with financial analysis, quantitative financial management and corporate financial decision-making. Some students decide to take national and international certifications (AMF, CFA).
A significant advantage: 3 professional certifications are included in the Master’s degree: AMF, Bloomberg, CFA Professional Certification
The students of the Master 2 Finance with sufficient command of French can take the AMF (French Financial Markets Authority) certification. This opportunity is offered to students thanks to the support of the IGR-IAE Foundation.
With our trading room featuring Bloomberg terminals, it is possible for you to take the internationally recognized Bloomberg Market Concepts (BMC) certification through online training (approximately 10 hours). The cost of this certification is covered by IGR-IAE.
The Bloomberg Market Concepts (BMC) certification is an 8-hour self-paced e-learning course that provides a hands-on visual introduction to financial markets. BMC consists of several modules:
– Economic Indicators : Monitoring and Forecasting GDP…
– Currencies / commodities: History and mechanics of the currency markets; exchange rate risk…
– Fixed Income: Understanding the bond market, interest rate setting
– Equities: Calculate the performance of a stock market index; Analyze the volatility…Multiple choice questions allow you to validate the knowledge acquired and then the modules and thus to obtain at the end of this training, the Bloomberg certification, an interesting asset to enhance the value of your CV. The Advantages of the certification : Bloomberg terminals are used by all market operators and analysts. Very few schools allow their students to take the Bloomberg certification via a trading room.
To date, only a few Grandes Ecoles and Master’s degree programs offer this possibility to students. This certification can clearly be an important element of differentiation when it comes to professional integration.
The CFA®, Chartered Financial Analyst is undoubtedly the most renowned international professional certification in Finance, both in banking and business. Passing the 1st of the 3 levels at the end of your M2 Finance is a significant asset that will make you stand out and give you a crucial advantage when it comes to recruitment. Only 2 other Masters in Finance and the 5 best Grandes Ecoles in France include CFA level 1 preparation.
Successful completion of the exam involves serious work (about 200 hours) for which the Master Finance prepares you in the best conditions ( 2 full weeks of preparation) to maximize your chances of passing the exam in June or December,
As a complement to these two weeks, IGR-IAE offers an online training platform (Barchen) as well as the book Réussir le CFA Level 1 written by Christine Verpeaux (Ensae, CFA, PRM) who will deliver several modules during these two sessions of study.
Exam in June or December
Registration for the CFA exam is to be done directly with the CFA Institute (cost varies depending on the date of registration: about 1000 euros).
IGR-IAE has signed a double degree and international mobility agreement with the ENCG Agadir, University IBN Zohr, in Morocco.
This agreement is part of the development of relations between the Brittany region and the Souss-Massa region. In addition to providing exchange opportunities for students, this partnership aims to facilitate inter-university cooperation and develop teaching and researchjoint activities between the two institutions.
The “Studies and Research in Finance” course of Master 2 introduces students to in-depth knowledge in the traditional fields of finance.
The technical dimensions allow the implementation of the concepts addressed. The personal work required ( further study, reading research articles, writing a research paper) clearly distinguishes the research speciality. It helps the student to gain autonomy, analytical, synthetic and critical thinking skills. These qualities, important in any kind of professional activity, are essential for researchers. Through its close links with financial research, the specialization participates in the dissemination of the most innovative tools, concepts and techniques in financial science. It also contributes to the ongoing development of the discipline by helping students address new challenges, understand solutions and, ideally, foster innovation.
Speakers
University teachers and professional practitioners (financial directors, risk managers, auditors, treasurers, consultants and representatives of professional associations).
The aim of the course is to give to students solid foundations in portfolio management.
Skills to be acquired
The students will be able to analyze the needs of investor and customers, to compute efficient portfolio using various techniques and contexts, to detect and analyze various investment methods and to assess the performance of portfolios.
Bodie, Kane, Marcus Investments McGraw-Hill
Basic knowledge in optimization and statistics
Written exam
The aim of the course is to explore in-depth the properties of options and those of the option markets. One will insist especially on the management of options and on the implied volatility and related concepts. These subjects are rarely covered that way.
The students will be able to understand the challenge faced by the option sellers and many aspects of the option markets…
Options
Option markets
Implied Volatility and related concepts.
Lecture notes and articles.
Moraux, Finance de Marché, Pearson, 2010 (chapter 7, 8, 9).
Portait, Poncet Finance de Marché, Pearson.
None.
Exam.
Knowledge of the main derivatives, understanding of the way they work and the evaluation techniques.
Program:
Derivatives markets
Derivative contracts: Forwards, futures and FRA
Swaps
Options
John Hull, Options, futures and other derivative assets, Pearson
Knowledge of basic financial products: stocks, bonds
Continuous assessment, assignments, in-class participation
The aim of the course is to understand
– the main models of portfolio optimization: Markowitz, Black, Black and Litterman
– portfolio insurance strategies
Skills to be acquired
The students will be able to implement portfolio optimization and portfolio insurance strategies
Chapter 1. Portfolio management
Reminder on Markowitz and Tobin methodologies
Black model approach
Main drawbacks
Applications on Excel and Bloomberg
Chapter 2. Advanced methods of portfolio management: Portfolio Insurance Strategies
The case of real options
Duplication methodologies and OBPI
Applications on Excel
Understand the methods and tools used by banks to manage their risks in the context of prudential regulations.
Skills to be acquired: Know how to measure the market and credit risk exposure of banks. Use statistical tools (parametric approaches and simulations) related to banking risk. Understand the prudential environment.
Models and measure of risks: Value at Risk (VaR), presentation, applications to market risks, estimation, back testing, critics and developments (Conditional VaR)
Methods of simulation: historical simulation, (+bootstrap, kernel), Monte Carlo simulations (Inverse Transform Method)
Stress testing: scenarios analysis and catastrophic scenarios
Foundation of credit risk analysis: exposition, probability of default, loss given default, correaltion between defaults,
Professional models of credit risk: CreditMetrics, Credit Portfolio View, Credit Risk…
Basel II approaches for credit risk
Risk Management and Financial Institutions John C. Hull.
Dowd “Beyond Value at Risk”, Wiley.
Jorion “Value at Risk”, 3rd Edition McGraw Hill.
Saunders “Credit Risk Measurement”, Wiley.
Riskmetrics “Technical Document”
Creditmetrics “Technical Document”
Gloriamundi.org
Bis.org
Knowledge of bank operations and risk management.
The objective of this course is to familiarize the students with performance measurement methods used in the banking sector.
By developing the concept of efficiency, we shall favor the approaches according to DEA axiomatic.
At the end of the course, the students will have to be able to develop, under excel, basic and extended DEA models-
Computing CCR and BCC models under Inputs and outputs orientations.
Using DEA Models to allocate fixed costs.
Introduction to costs terms.
Distance function and DEA Analysis.
CCR input and output oriented.
Economies of scales and BCC models.
Outputs and Ressources allocation using DEA Models
Fixed costs allocation models using DEA.
– Data Envelopment Analysis, A comprehensive Text with Models, Applications,References and DEA- Solver Software, W.W. Cooper, L.M. Seiford, K. Tone, Springer, 2008.
– Gestion des risques et institutions financiers, J. Hull, Pearson, 2008.
– Data Envelopment Analysis, Theory, Methodology and Applications, A. Charnes, W. Cooper, A. Lewin, M. Seiford, Kluwer, 2000.
Operational Resaerch
Project
This course presents the foundation of corporate finance with an emphasis on capital structure decisions. The main objective of the course is to provide the conceptual background for understanding and analyzing the capital structure of firms in the market environnement.
This course will cover important topics and recent developments in capital structure theory. The goal of this class is to familiarize you both with original papers in the field and current researches in this areas.
Part 1 – Introduction to corporate finance
First principles of corporate finance
Part 2 – Financial Structure and Firm Value
✓ Chapter 1 – The financing mix question: practical point of view
✓Chapter 2 – The MM’s theorem
✓ Chapter 3 – The costs of financial distress
✓ Chapter 4 – The signaling theory and informational asymmetries
✓Chapter 5 – The agency theory
Chapter 6 – The tradeoff model
Part 3 – Financial Choices and security design
✓ Chapter 1 – Equity financing
✓ Chapter 2 – Debt Financing
✓ Chapter 3 – Hybrid Financing
Damodaran, Corporate Finance: Theory and practice, 2nd edition, 2010
Almeida, Heitor, and Thomas Philippon, 2007, The Risk-Adjusted Cost of Financial Distress, Journal of Finance 62, 2557-2586
Anderson, RW, and S Sundaresan, 1996, Design and Valuation of Debt Contracts, Review of Financial Studies 9:1, 37-68
Graham, John R., 2000, How Big Are the Tax Benefits of Debt?, Journal of Finance 55, 1901-1941.
Jensen, Michael C., and William H. Meckling, 1976, Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure, Journal of Financial Economics 3, no. 4 (October), pp. 305-360
Leary, Mark T., and Michael R. Roberts, 2009, The Pecking Order, Debt Capacity, and Information Asymmetry, Journal of Financial Economics 95, 332-355.
Modigliani, Franco, and Merton H. Miller, 1958, The Cost of Capital, Corporation
Finance and the Theory of Investment, American Economic Review 48:261-297
Myers, Steward C., and Nicholas S. Majluf, 1984, Corporate Financing and Investment Decisions when Firms Have Information that Investors do not Have, Journal of Financial Economics 13, no. 2 (June), pp. 187-224
Shyam-Sunder, Lakshmi, and Stewart C Myers, 1999, Testing Static Trade-Off Against Pecking Order Models of Capital Structure, Journal of Financial Economics 51:2, 219-244.
Strebulaev, Ilya A., 2007, Do Tests of Capital Structure Theory Mean What They Say?, Journal of Finance 62:4, 1747-1787
Written exam (2h)
The aim of the course is to:
– Discover VBA with excel and to code on VBA
– Master the basics of programming
The students will be able to code on VBA ( macros and functions)
– 3h: Presentation and theoretical overview of VBA
-6h : Series of 20 exercises on macros
-6h : Series of 20 exercises on functions
Course elements
Basic knowledge in programming and mastery in excel
Project
The aim of the course is to introduce students to use the Bloomberg dataset.
Skills to be acquired
The students will be able to:
– To look for any information on all companies and assets available on the Bloomberg dataset
– To export the data on a selected sample of companies, indexes…from Bloomberg to excel for further analyses
– Chapter 1 : Bloomberg terminal
– Chapter 2 : Bloomberg via Excel
– Chapter 3 : Applications
Using the help tab available on Bloomberg to deepen the knowledge.
General knowledge in corporate finance and financial markets as a whole to be able to understand the concepts available in the Bloomberg dataset.
Project.
The aim of the course is to:
– Introduce students to manage cross-sectional as well as panel data
– Initiate them to use the ordinary least squares estimations (simple and multiple linear models)
– This course is followed by a set of exercises on applied econometrics with several applications using Excel and the R software.
The students will be able to:
– Manage and read the content of a dataset using R and excel
– Specify economic and financial phenomena and to interpret them
– Chapter 1 : Introduction to econonometric modelling
– Chapter 2 : Simple linear regression model
– Chapter 3 : Multiple linear regression model: an application on Excel and R
– Reference 1 : Principles of Econometrics, by: Hill, R. Carter; Griffiths, William E.; Lim, Guay C. Edition: 4th ed. New York : Wiley. 2011.
– Reference 2 : Introductory Econometrics: a modern approach , by: Wooldridge, Jeffrey M..
– Reference 3 : Econometric analysis, by William Greene
Basics in mathematics, linear algebra, descriptive statistics and probability theories.
Project
Program:
Risk management has become progressively more important for all corporations in the last few decades. Financial institutions such as banks and insurance companies are concerned with providing a good trade-off between return and systemic (non-diversifiable) risk for their investors. They are also concerned with total risks (systemic plus non-systemic) because of the bankruptcy costs arguments. However, there is another reason why most financial institutions carefully monitor total risks. This is that regulators require them to ensure that the probability of a bank or an insurance company experiencing severe financial difficulties is low.
Risk management is the process of identification, analysis and acceptance or mitigation of uncertainty in investment decisions. In other words, the role of risk management is to understand the risks of an investment that the company is currently taking and the risks it plans to take in the future. It must decide whether the risks are acceptable and if they are not acceptable, what action should be taken given its investment objectives and risk tolerance.
There are two broad risk management strategies open to a financial institution. One approach is to identify risks one by one and handle each one separately. This is referred to as risk decomposition. The other is to reduce risks by being well diversifying. This is referred to as risk aggregation. The objective of this course is therefore twofold. The first one is to give a view of how risk measurement techniques are quantified in almost every single market. Each technique is deeply associated with its specific market and cannot be applied directly to other markets. The second objective (main objective of the course) is to present an integrated way to deal with different markets and different risks and to combine all of the factors in a single number which is a good indicator of the overall risk level: Value at risk.
The students will
have an overview of existing risk measure techniques (Bonds : duration, convexity, term-structure model; Stocks : volatility, correlations, beta; Derivatives : Greek parameters; Credit : rating, default models; Forex: target zones, spreads; Value at risk (VaR)).
to be able to calculate the risk of a portfolio containing different securities (VaR methods of measurement: Historical simulations, Variance-covariance, Monte Carlo simulations, Analytical methods).
1. An overview of risk measurement techniques
2. Value at risk
1. Hull, John. C. (2012). Risk management and financial institutions. Pearson.
2. Dowd, Kevin. (2002). An introduction to market risk measurement. Wiley Finance.
3. McNeil, Alexander. J. Frey, Rudiger and Embrechts, Paul. (2015). Quantitative risk management: Concepts, techniques and tools. Princeton University press.
Notions about banks, insurance companies, mutual funds and hedge funds, financial instruments and how to use these instruments.
Calculus: derivatives, differentiating functions and integrals, etc.
Probability theory: calculation of probability of an event, random variables and their distributions, mean, variance, limit theorems, etc.
Linear algebra: basic calculations with matrices: summation & subtraction, multiplication of matrices, finding determinants and inverse matrix, etc.
Empirical project.
Linear regression is the most basic tool of an econometrician and is widely used throughout finance and economics. It attempts to model the relationship between two or more variables by fitting a linear equation to observed data. Using the suitable methods and techniques, the objectives of regression analysis are to analyze movements in an economic variable by reference to movements in one or more other economic variables. Linear regression’s success is owed to two key features: the availability of simple closed form estimators and the ease and directness of interpretation.
There are two types of linear regression, simple linear regression and multiple linear regressions. In simple linear regression a single independent variable is used to predict the value of a dependent variable. In multiple linear regressions, two or more independent variables are used to predict the value of a dependent variable.
There are broadly three types of data that can be employed in quantitative analysis of financial problems: time series data, cross-sectional data, and panel data. A cross-sectional regression is a type of regression in which the explained and explanatory variables are associated with one period or point in time. This type of cross-sectional analysis is in contrast to a time-series regression in which the variables are considered to be associated with a sequence of points in time. Panel data have the dimensions of both time series and cross-sections. The panel data, also called longitudinal data or cross-sectional time series data, are data where multiple cases (people, firms, countries, etc.) were observed at two or more time periods. Following these distinguished types of data, the course is divided into three units.
In the empirical work, this course uses R software to analyze the relationship between variables. R is an open-source software programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
The students will be able to
model time series, cross sectional data when assumptions are not valid.
apply appropriate tests to analyze properties of cross sectional and time series data, to identify stationarity, trend, seasonality, etc.
use R software.
Regression analysis with cross-sectional data and time series data
I. Econometrics and Statistics Textbooks on Finance
1. Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.
2. Wooldridge, J. M. (2012). Introductory Econometrics A Modern Approach
3. Greene, W. H. (2003). Econometric analysis. Pearson Education India.
4. Hamilton, J. D. (1994). Time series analysis. Princeton: Princeton university press
II. R Software
1. Carmona, R. (2014). Statistical Analysis of Financial Data in R. Springer Texts in Statistics.
2. Chambers, J. (2008). Software for data analysis: programming with R. Springer.
3. Daróczi, G., Puhle, M., Berlinger, E., Csóka, P., Havran, D., Michaletzky, Vidovics-Dancs, A. (2013). Introduction to R for Quantitative Finance. Packt Publishing Ltd.
4. Goulet, V. (2014). Introduction à la programmation en R.
Calculus: derivatives, differentiating functions, finding extreme values of functions, and integrals.
Probability theory: calculation of probability of an event, random variables and their distributions, limit theorems, calculation of confidence intervals, hypothesis testing (Lagrange multiplier tests, Chisquare tests, etc.), analysis of variance, covariance and correlation, etc.
Linear algebra: basic calculations with matrices: summation & subtraction, multiplication of matrices, finding determinants and inverse matrix, and solve systems of linear equations, eigenvalues and eigenvectors of a matrix.
Empirical project.
The aim of the course is to :
– Introduce students to scientific research
– Learn about different research institutions in France and different datasets that can be used in the research field.
The students will be able to:
– Read and understand a research paper
– Present and discuss a a research paper for instance in a conference
– Discuss a research article and write a report for a scientific journal
– Chapter 1: Introduction to empirical research
– Chapter 2: Research in bank and corporate governance
– Chapter 3: Papers presentations
Research articles in the finance field
General knowledge in corporate finance, financial markets and banking finance.
Project
Several level groups of French as a foreign language are organized at the beginning of the session, allowing each group to have specific objectives depending of the level of French, from total beginners to students with already a B2 level, needing more business-related contents. Students will benefit from specific tutoring both for oral, grammatical and written skills.
Visits, cultural and daily life activities or discoveries are included in the course.
Create programs in VBA to automate tasks and create custom solutions.
Websites:
Books :
– Flavio MORGADO, Programming Excel with VBA : A Practical Real-World Guide. Apress; 1st ed.
– Frédéric LE GUEN, Macros et langage VBA : Apprendre à programmer sous Excel. ENI
Have a good knowledge of Excel with in particular calculation formulas (if, search, index, etc.).
The aim of the course is to give an overview of real option theory and applications.
Skills to be acquired
The students will be able to understand real option model, to solve investment problem using real option theory, to comment scientific papers on real option theory. …
-Real option Valuation : basic
Real option valuation : advanced
Option to wait
Operational Flexibility
Comments of papers on real option theory
Various scientific papers
Basic knowledge on option pricing.
The aim of the course is to provide students with the knowledge necessary to understand, analyse and make corporate financial decisions. Tools and techniques will be taught through theoretical presentation and practical applications.
Critical analysis will be encouraged by in-class discussion about the limits of the techniques employed and the way to overcome them.
The students will be able to understand, make and analyze three types of corporate finance decisions: capital budgeting, financing decisions and shareholders’ payout policies.
APPLIED CORPORATE FINANCE, Damodaran, Wiley, 2015
The aim of the course is to give an overview of real option theory and applications.
The students will be able to understand real option model, to solve investment problem using real option theory, to comment scientific papers on real option theory. …
Various scientific papers
Basic knowledge on option pricing.
Project : comments of papers.
The aim of the course is to present financial statement analysis from the point of view of the primary users of financial statements: equity and credit analysts.
The students will be able to:
Understand how financial statements provide information regarding an enterprise;
Prepare, audit or interpret financial information;
Understand how the differences in accounting methods (IFRS, US GAAP) affect reported results of operations, including cash flows and ratios.
The accrual method of accounting and its implications for financial reporting: income statement and balance sheet
Cash flow statement and cash flow analysis
Ratio analysis: advantages and limits
Analysis of inventories
Long-lived assets: capitalization versus expensing decision
Allocation of capitalized costs to operations (depreciation, impairment and restructuring)
Income-tax disclosures
Long-term liabilities: analysis of varying forms of debt, off-balance-sheet financing techniques (leases)
The analysis and use of Financial Statements, G. I. White, A. C. Sondhi, D. Fried; Wiley, second edition
Financial Analyst Journal, CFA Institute
CFA Magazine, CFA Institute
Understand the essential elements of financial statements analysis
Final exam: Multiple Choice Questions
The aim of the course is to give students a general understanding of the numerical methods that have early been introduced in Finance to deal with situations where it is impossible to derive analytical results. Among the broad set of available numerical methods, the course will insist on the Monte Carlo simulation technique (and variants) as well as a number of tree approaches such as the binomial tree and the trinomial tree. My aim is also to highlight and illustrate (through examples) both the opportunities and the challenge these approaches represent. For instance, the simulation approach essentially relies on our capacity to “discretize” the continuous process (hypothesized for modelling the dynamics of the underlying asset price). The tree approach must be carefully adapted to account for path-dependency. As a by-product, I will present in this course a number of exotic options for which no analytical pricing formula exists.
At the end of the course, the students will be able to implement a number of techniques (from the MC simulation approach and the lattice approach) to price exotic options… For pedagogical reasons, one will use Excel© to explicit and highlight all the details. But nothing prevents the students to come and use other devices useful for numerical methods (R, matlab, mathematica).
Computational Finance and Numerical Methods: what for?
The Monte Carlo simulation technique (and some variants)
The ”Tree/Lattice” approaches (and variants)
Lecture notes… as well as many articles.
Duan, Hardle, Gentle (ed.) Handbook of Computational Finance, Springer, 2012.
Glasserman Monte Carlo Methods in Financial Engineering, Springer, 2003.
Jaeckel Monte Carlo Methods in Finance, Springer, 2002.
Others:
Benninga Financial Modeling, MIT Press.
Kloeden Platten : Numerical Solution of Stochastic Differential Equations, Springer.
Standard knowledge in probability.
Project.
The aim of the course is to learn about panel data and the use of qualitative information (binary independent variables) in econometric models.
The students will be able to:
– Manage panel data and run estimations
– Manage panel data using different softwares (R and Stata)
– Use binary independent variables and interpret them
– Chapter 1 : Data analysis using R and Stata
– Chapter 2 : Use of binary independent variables in a regression
– Reference 1 : Principles of Econometrics, by: Hill, R. Carter; Griffiths, William E.; Lim, Guay C. Edition: 4th ed. New York : Wiley. 2011.
– Reference 2 : Introductory Econometrics: a modern approach , by: Wooldridge, Jeffrey M..
– Reference 3 : Econometric analysis, by William Greene
Basics in mathematics, linear algebra, descriptive statistics, probability theories and econometrics on cross-sectional data.
Project
The aim of the course is to present the core material, tools and concepts of Mathematical Finance. These devices are very useful in Finance to model the financial market, to describe the dynamics of asset prices, to price financial assets and in some cases to understand how people decide. After a general overview of useful probabilistic concepts, one will insist on some elements picked from stochastic processes and stochastic calculus. One will study and apply the Brownian motions, the Levy processes, the Ito’s lemma and the Girsanov theorem among many other things. This course is taught in parallel with the “Computational Finance” course. As a result students can have some deep understanding and intuitions of what stochastic processes can provide.
The students will develop a financial intuition of what concepts of advanced probability can provide in Finance. They will understand in depth some formulae very popular in Finance. They will be able to make simple stochastic calculus on their own.
The filtered probability space, Random Variables & Probabilities (intuition on the change of probabilities and the RadonNikodym derivative)
Stochastic Processes (how to describe them)
A (non exhaustive) list of stochastic processes
A focus on the standard brownian motion and Ito’s processes
First elements of Stochastic Calculus (Ito’s lemma).
Exercises with Finance in view.
The Girsanov Theorem and applications in Finance
Lecture notes. A full bibliography is provided in the lecture notes.
Standard knowledge in probability.
Exam.
Several level groups of French as a foreign language are organized at the beginning of the session, allowing each group to have specific objectives depending of the level of French, from total beginners to students with already a B2 level, needing more business-related contents. Students will benefit from specific tutoring both for oral, grammatical and written skills.
Visits, cultural and daily life activities or discoveries are included in the course.
The traditional professional opportunities include the various consulting, analytics, and research careers (fundamental or applied). Most students find jobs in financial organizations (banks, financial institutions, asset management companies, insurance companies, etc.), in the academic sphere (universities, business schools) and corporate finance departments.
The Master of Finance – Advanced Studies and Research in Finance is an English-taught Master 2 program, leading to a Master’s degree fully accredited by the French state.
In order to apply, students should hold a 4-year Bachelor’s, or a Master 1 or Master 2 or a 4 or 5-year business school diploma.
Holders of a 3-year Bachelor’s Degree are not eligible to apply.
Tuition fee for the academic year 2024-2025 is 6,990 €.
If you are citizen of EU country the price is 6,283€.
If you have a French level as high as C1 or higher, show us you official certificate and we will quote for your speific situation.
Included in this tuition fee:
Not included in this tuition fee:
French students and international French-speaking students are welcome to contact us for more information on the fee applicable to their situation.
Classes begin:
September 1, 2024
End of academic year:
October 31, 2025 (including internship period)
Program Director:
Nadia Saghi
International Students Coordinators
Cécilia THOMAS
igr.international-degree@univ-rennes.fr
+33 2 23 23 47 92
