• Target level of study

    BAC +5

  • ECTS

    120 credits

  • Duration

    2 years

  • Training structure

    Faculty of Economics

  • Language(s) of instruction

    French

Presentation

The Master's degree in Money, Banking, Finance and Insurance comprises 5 courses:

  • Market Risk Analysis course
  • Banking Risk Analysis Course
  • Actuarial studies
  • Financial Engineering course
  • Economic and Financial Information Systems course
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Training benefits

  • Since 2019, the Faculty of Economics has been equipped with a trading room that implements innovative teaching practices in real-life trading situations, and the analysis of financial data and information.
  • This is the only Master's degree in the Hérault department and in the region that offers students a real opportunity to consider a career in financial engineering. It's also worth mentioning that this will be one of the few courses in financial engineering to be offered within an economics faculty in France.
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Objectives

The Market Risk Analysis course provides an understanding of the organization and operation of the most common financial products (equities, bonds, etc.) as well as speculative markets (energy, raw materials, commodities, etc.).

The Banking Risk Analysis path enables you to acquire skills in the tools used to model banking risks and the banking environment. A sound knowledge of banking operations and products.

The Actuarial Science pathway enables students to acquire skills in actuarial methods and tools and to apply them to their professional practice. The theoretical and methodological knowledge required to pursue a career as an actuary, and to prepare future researchers in this field.

The Financial Engineering pathway enables students to acquire advanced financial engineering techniques, techniques that integrate the global dimension of the problems to be dealt with and their strategic stakes, and that are open to the international environment.

The Information Systems track provides skills in computer science, information systems modeling and economic and financial data mining.

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Know-how and skills

This mention allows :

                - Give students the skills they need to work as risk analysts (analyzing different types of risk), to be able to propose personal solutions in the field of risk management (risk assessment of complex products, construction of structured products or complex portfolios, etc.), and actuarial science.

                - Give students the skills needed to carry out research for public bodies and to understand financial and banking regulations and operations, to detect, assess and model risks, and to evaluate financial products.

                - Master the tools of financial modeling as well as financial and banking econometrics and financial engineering techniques, enabling you to apply for jobs as market operators, portfolio managers, financial risk analysts, back office functions and actuary analysts.

               - Acquire sufficient knowledge to apply for the Contrats doctoraux competition and/or to enroll in a doctoral program.

               - Computer skills and the ability to model and use computer tools, software and software packages often used in the marketplace.

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Organization

Special features

Special study and examination arrangements are available for students with disabilities and/or high-level athletes.

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Program

The Master's degree is divided into 2 years: Master 1 and Master 2.

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Select a program

Actuarial science (MBFA MENTION)

Actuarial science is part of the Money, Banking, Finance and Insurance specialization.

This course provides the theoretical and methodological knowledge needed to pursue a career as an actuary, and prepares future researchers in this field.

  • What is an actuary?

Professional specializing in the application of probability calculus and statistics to insurance, finance and welfare issues.

To do this, they analyze the financial impact of the risk and estimate the associated future cash flows. The actuary uses mathematical techniques, mainly derived from probability theory and statistics, to describe and model certain future events in a predictive way, such as the length of human life, the frequency of claims or the scale of associated financial losses.

See the complete page of this course

  • Theoretical econometrics

    5 credits
  • Market Finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Language selection list

    • Your choice: 1 of 2

      • English for Finance 1

        2 credits
      • Spanish 1

  • Economics of Bancassurance

    3 credits
  • Introduction to stochastic calculus

    4 credits
  • Corporate Finance

    4 credits
  • Introduction to SAS

    2 credits
  • Actuarial models in Excel VBA

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Actuarial techniques

    3 credits
  • Your choice: 1 of 2

    • Financial English 2

      2 credits
    • Spanish 2

      2 credits
  • Optional

    • UM student commitment

  • Financial markets and financial theory

    2 credits
  • Professionalization conferences

  • Trading algorithm

    1 credits
  • Portfolio management under R

    1 credits
  • Non-Life Actuarial

    3 credits
  • Financial analysis (Banque de France)

    1 credits
  • Introduction to artificial intelligence in Python

    0.5 credits
  • Primary equity market: initial public offering

    0.5 credits
  • Stochastic calculus

    2 credits
  • English for finance

    1 credits
  • Enterprise risk management

    1 credits
  • Exploratory statistics (SAS)

    1 credits
  • Computer techniques (VBA)

    1 credits
  • Modeling emerging risks

    2.5 credits
  • Life Actuarial

    2.5 credits
  • Cybersecurity and cryptography

    1 credits
  • Econometrics applied to finance

    2 credits
  • Econometrics of financial markets

    2 credits
  • Financial Big Data

    1 credits
  • FinTechs, Block-Chain and Crypto-currencies

    1 credits
  • Numerical Methods in Actuarial Science "VBA

    2 credits
  • Banking and insurance regulations

    1 credits
  • Research seminars

Banking risk analysis (MBFA MENTION)

This program trains banking finance professionals and researchers in this field.

It offers modern programming combined with statistical methods applied to large financial databases, with the aim of managing banking risks.

This course takes constant account of developments in the banking sector, and in particular of changes in the banking risk analyst professions. Over the last few years, the banking professions have undergone profound changes. These changes and the globalization of operations have generated new risks. International operations account for a growing share of credit institutions' balance sheet and off-balance sheet activities, while market operations are becoming more diversified and complex. These developments have generated new types of risk and altered the factors of financial fragility likely to affect the quality of banking players' situations. As a corollary, the banking supervisory authorities have imposed prudential rules to prevent banks from going bankrupt. These rules are part of preventive action programs designed to promote the stability of domestic banking systems.

This new range of training courses is designed to meet Basel III regulatory constraints on the measurement of banking risks such as liquidity risk, asset liability management (ALM)...

 The aim is to equip students with three types of skills: expertise in quantitative methods (econometrics, analysis of large databases, etc.), risk analysis (particularly in banking) and banking regulations, and mastery of IT tools (SAS, R, VBA, Python....). Courses in quantitative subjects take place in the MUSE trading room.

 These skills equip students with powerful tools for measuring the risks faced by financial institutions, enabling them to join risk control departments....

Strong links have been forged for many years with regional and national professionals, such as the regional director of the Ecole Supérieure, the regional delegate of the Fédération Française des Banques... Numerous professionals are involved in Master 2 courses, or in the course's professionalization lectures. These professionals share their professional experience and explain the careers they can expect to enter on graduating. Internships are often secured as a result.

Conferences on Big Data, Artificial Intelligence (Python programming), ..... are organized by Data Scientist specialists.

As a result, students benefit from excellent professional training based on solid theoretical knowledge and professional application by recognized experts in the field, through tutored projects or professionalization conferences. This enables the vast majority of graduates to find a job within six months of completing their Master 2. The integration rate is over 77%. 

See the complete page of this course

  • Your choice: 1 of 2

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market Finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Optional

    • UM student commitment

  • Your choice: 1 of 2

    • Financial English 2

      2 credits
    • Spanish 2

      2 credits
  • Introduction to stochastic calculus

    4 credits
  • Corporate Finance

    4 credits
  • Introduction to SAS

    2 credits
  • Banking techniques

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Financial mathematics in Excel VBA

    3 credits
  • Professionalization conferences

  • Financial markets and financial theory

    2 credits
  • Numerical methods in VBA banking

    2 credits
  • Trading algorithm

    1 credits
  • Portfolio management under R

    1 credits
  • Financial analysis (Banque de France)

    1 credits
  • Primary equity market: initial public offering

    0.5 credits
  • Stochastic calculus

    2 credits
  • Operational and compliance risks

    2 credits
  • English for finance

    1 credits
  • Introduction to artificial intelligence in Python

  • Exploratory statistics (SAS)

    1 credits
  • Computer techniques (VBA)

    1 credits
  • Financial Big Data

    1 credits
  • Credit risk

    2 credits
  • Cybersecurity and cryptography

    1 credits
  • Econometrics applied to finance

    2 credits
  • Econometrics of financial markets

    2 credits
  • Asset liability management (ALM)

    2 credits
  • Interest rate risk

    2 credits
  • FinTechs, Block-Chain and Crypto-currencies

    1 credits
  • Numerical Methods in Actuarial Science "VBA

    2 credits
  • Programming in R

  • Banking and insurance regulations

    1 credits
  • Research seminars

Market risk analysis (MBFA MENTION)

This course is designed to train market finance professionals and researchers specializing in this field. It offers specialized training in the theoretical and quantitative aspects of products traded on financial markets. In particular, it covers the determination of risk management using a combination of statistical methods.

This course is a continuation of what has been done up to the 2020-2021 academic year, with developments that enable the integration of changes in the risk analyst professions. In particular, it will incorporate Basel III regulatory constraints on market risk measurement (calculation of Value at Risk (VaR) and Expected Shortfall (ES), and their validation (backtesting). The aim is to equip students with high-performance tools for measuring and hedging the risks faced by financial institutions (banks and insurance companies). Once they have acquired their skills in market risk analysis, students will be able to join risk control departments. 

See the complete page of this course

  • Your choice: 1 of 2

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market Finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Introduction to stochastic calculus

    4 credits
  • Asset valuation

    3 credits
  • Corporate Finance

    4 credits
  • Introduction to SAS

    2 credits
  • Portfolio allocation

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Optional

    • UM student commitment

  • Your choice: 1 of 2

    • Financial English 2

      2 credits
    • Spanish 2

      2 credits
  • Numerical methods

    3 credits
  • Financial markets and financial theory

    2 credits
  • VBA programming

    1 credits
  • Stochastic calculus

    2 credits
  • Portfolio management

    4 credits
  • English for finance

    1 credits
  • Trading algorithms

    2 credits
  • Data mining and big data

    3 credits
  • Exploratory statistics (SAS)

    1 credits
  • Computer techniques (VBA)

    1 credits
  • Market risks

    4 credits
  • Econometrics of finance

    2 credits
  • Programming on R, Python

    1 credits
  • Professional speakers

  • Research seminars

Economic and financial information systems (MBFA MENTION)

This course offers in-depth training in economics and econometrics.

It also enables students to acquire skills in information systems modeling and economic and financial data mining.

See the complete page of this course

  • Your choice: 1 of 2

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market Finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • IS (information system) design

    3 credits
  • Database handling

    2 credits
  • Programming techniques

    2 credits
  • Data mining and big data

    3 credits
  • Survey

    2 credits
  • Computer law (Polytech)

    2 credits
  • Data warehouse

    3 credits
  • IS (information system) modeling

    3 credits
  • Exploratory statistics (SAS)

    1 credits
  • Computer techniques (VBA)

    1 credits
  • Data visualization design

    2 credits
  • Econometrics

    3 credits
  • Security

    3 credits
  • Optional

    • UM student commitment

  • Your choice: 1 of 2

    • Financial English 2

      2 credits
    • Spanish 2

      2 credits
  • Introduction to stochastic calculus

    4 credits
  • Corporate Finance

    4 credits
  • Introduction to SAS

    2 credits
  • VBA programming

    3 credits
  • Econometrics of qualitative variables

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Choice of internship or dissertation

    30 credits
    • Your choice: 1 of 2

      • M2 SIF internship

        30 credits
      • Research dissertation as part of a research program

        30 credits
  • Research seminars

Financial Engineering (MBFA MENTION)

This course trains professionals in financial engineering and researchers specializing in this field.

See the complete page of this course

  • Your choice: 1 of 2

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market Finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Your choice: 1 of 2

    • Financial English 2

      2 credits
    • Spanish 2

      2 credits
  • Introduction to stochastic calculus

    4 credits
  • Corporate Finance

    4 credits
  • Introduction to SAS

    2 credits
  • Project financing in Excel VBA

    3 credits
  • Time series econometrics

    5 credits
  • Corporate taxation

    3 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Optional

    • UM student commitment

  • Merger-Scission-LBO-Bankruptcy-Restructuring

    2 credits
  • Quantitative risk management

    2 credits
  • Financial markets and financial theory

    2 credits
  • Investment science

    3 credits
  • Portfolio management under R

    1 credits
  • Innovative financing operations

    1 credits
  • Financial analysis (Banque de France)

    1 credits
  • Advanced financial management "case study

    2 credits
  • Stochastic calculus

    2 credits
  • Tax optimization "Case studies

    2 credits
  • Audit and control "case study

    1 credits
  • English for finance

    1 credits
  • Exploratory statistics (SAS)

    1 credits
  • Computer techniques (VBA)

    1 credits
  • International accounting (GAAP or IFRS)

    2 credits
  • Project management and set-up

    1 credits
  • Panel econometrics

    2 credits
  • FinTechs, Block-Chain and Crypto-currencies

    1 credits
  • Banking and insurance regulations

    1 credits
  • Strategy and corporate governance

    1 credits
  • Research seminars

Admission

Access conditions

CANDIDATES :

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Target audience

And then

Professional integration

Students in this specialization prepare for a wide range of careers in banking, finance, insurance, financial engineering, data processing
(data analyst) and information systems design.

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