MASTER IN FINANCIAL ENGINEERING

Intake
October 2024

Location
Africa Business School campus, UM6P, Rabat

Target
Moroccan or international candidates holding a Bachelor/License Degree, preferably in applied mathematics, statistics or computer science.

Duration
2 years

Language
English & French 

Format
In person

WHY A MASTER IN FINANCIAL ENGINEERING ?

THIS PROGRAM IS DESIGNED FOR

PROGRAM STRUCTURE

SELECTED FACULTY

LEARN MORE ABOUT THE PROGRAM

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Welcome to the Master in Financial Engineering (MFE) at Africa Business School

Financial Innovations and Global Challenges: Join the Master in Financial Engineering, an exceptional program at the heart of African and global financial markets. 

The Master in Financial Engineering (MFE) is an innovative and interdisciplinary program designed to train experts capable of mastering complex financial products and supporting the development of African markets. This program will equip you with the technical skills necessary to address today’s financial challenges while placing a particular emphasis on the banking and insurance sectors, African financial markets, and the transition towards sustainable practices. 

WHY CHOOSE OUR MASTER’S PROGRAM?

  • A focus on Africa and beyond

    • The MFE builds on the emergence of Morocco and Africa in the financial sector. In addition to equipping, you with cutting-edge financial engineering skills, this program prepares you to play a key role in the development of African markets.

  • A program rooted in industry needs

    • Our curriculum evolves continuously to adapt to market demands, with updated modules in sustainable finance, data science, banking regulation, and risk management. The program is designed to prepare our graduates for the complex challenges of modern finance.

  • A network of renowned experts and practitioners

    • Courses are taught by internationally recognized professors and practitioners from prestigious institutions such as Natixis Bank and leading universities (Université Pierre et Marie Curie, Université Paris Dauphine, New York University, McMaster University, …). Our students also benefit from collaborations with the various Centers of Excellence at UM6P. 

THIS PROGRAM IS DESIGNED FOR:

Moroccan and international candidates  who hold a Bachelor’s or equivalent License Degree in mathematics, statistics, computer science, economics, or finance. 

Given the nature of our Master’s degree, basic knowledge of mathematics, probability, statistics, computer science (algorithms, programming) and databases is recommended. 

PROGRAM STRUCTURE

Semester 1

Introduction to Probability
Introduction to Probability
Statistical Methods for Data Science
Sustainable Finance
Foundations of Finance and Financial Markets
Python Programming for Financial Engineering
Academic and Research Skills Development


The “Probability Primer” course provides students with a comprehensive understanding of probability theory.
It is specifically tailored to the demands of financial engineering.
Through this course, students will deepen their knowledge of essential probabilistic concepts
to analyze and model financial markets, evaluate derivatives, and manage risk effectively.
Topics include probability spaces, random variables, and their distributions, focusing on applications in finance.
Students will also explore probability measures and algebraic structures relevant to financial modeling.


Additionally, the course delves into simulation techniques specific to financial variables,
providing students with practical skills in generating simulated data for derivative valuation,
stress testing, and scenario analysis. Special emphasis is placed on Monte Carlo simulations
and their application in risk management and portfolio optimization.
Furthermore, students will learn principles of convergence and limit theorems adapted to financial variables.

Course Objectives

This module aims to provide an in-depth understanding of fundamental concepts in probability theory,
including probability spaces and random events. Students will learn to apply probability theory
to real-world problems, particularly in financial engineering.
They will master statistical inference techniques, both frequentist and Bayesian,
and gain knowledge of various probability distributions, both discrete and continuous,
as well as their properties and applications in financial contexts.
Moreover, students will develop skills in using simulation techniques to generate random data
and evaluate probabilistic models.
They will understand the principles of convergence for sequences of random variables and their implications.
Finally, they will be able to interpret and use probabilistic results in financial contexts such as
derivative pricing, risk management, and portfolio optimization.



This module offers an in-depth exploration of statistical methods tailored for data science applications.
The course focuses on the practical use of statistical techniques to analyze datasets,
emphasizing understanding the underlying concepts rather than rigorous mathematical proofs.
Students will master the application of these methods using the R programming language.
The module covers a range of statistical models and methods commonly used in modern data analysis,
preparing students to tackle real-world data science challenges.

Course Objectives

By the end of this course, students will be able to:


– Develop an understanding of the key statistical models and methods used in modern data science.
– Effectively apply statistical techniques in various practical contexts.
– Gain knowledge of the theoretical foundations of statistical methods for data analysis.
– Master data analysis using R software.
– Focus on intuitive understanding and practical application of statistical techniques rather than theorem development and proofs.
– Develop the ability to use statistical and financial software to perform econometric analyses.



This course provides a comprehensive overview of sustainable finance,
covering topics such as an introduction to sustainable finance, policy and regulatory frameworks,
industry initiatives and best practices, the integration of Environmental, Social, and Governance (ESG) criteria,
sustainable investment vehicles, climate finance and carbon markets,
sustainable risk management and reporting, emerging trends and innovations,
as well as practical applications and case studies.

Course Objectives

As the world faces urgent environmental and social challenges, the financial sector plays a critical role in addressing these issues.
The objective of this course is to develop an understanding of the role of the financial sector in sustainability
and to introduce the key principles and tools of sustainable finance.
Delivered from a practical perspective, the course emphasizes the application of concepts through case studies.



This course provides an introductory overview of financial markets,
financial instruments, and trading practices. It covers the roles and objectives of various financial market participants,
types of markets, as well as trading conventions and terminology.
Emphasis is placed on understanding the differences between primary and secondary markets
and the characteristics of various financial instruments.

Course Objectives

The goal of this course is to provide students with a comprehensive understanding of financial markets,
instruments, and trading practices. It aims to introduce students to the roles and objectives of various financial market participants
while familiarizing them with different financial instruments and their characteristics.
Additionally, the course aims to develop students’ quantitative skills in analyzing derivatives and assessing risk factors.
Finally, it illustrates the application of financial securities through real-world case studies.



This course offers an in-depth introduction to Python programming in the context of quantitative finance.
It covers the fundamental syntax of Python and data types, along with basic concepts in quantitative finance.
The course explores financial data manipulation using the Pandas library, visualization techniques with Matplotlib,
and the implementation of financial models in Python. Advanced topics include portfolio management,
risk analysis, derivative pricing models, and algorithmic trading strategies.
Practical projects and case studies provide opportunities to apply the concepts learned to real-world financial problems.

Course Objectives

This course is designed to teach Python programming skills essential for financial engineers. Participants will learn to:


– Use Python to analyze financial data, implement financial models, and create portfolio analysis tools.
– Automate tasks related to quantitative finance.


Upon completing this course, students will be able to:


– Understand the basics of Python and its application in a financial context.
– Develop skills in financial data manipulation and analysis.
– Master the implementation of financial models in Python.
– Create tools for portfolio analysis and risk management.
– Automate common tasks related to quantitative finance.



This module equips students with the skills and tools necessary for success in both their academic and professional journeys,
preparing them to produce high-quality work and communicate their ideas effectively in academic and professional contexts.
It aims to enhance students’ academic skills by:


– Developing proficiency in academic methodology, including study planning and time management.
– Strengthening critical reading and analysis of academic texts.
– Improving research capabilities, particularly in effective information retrieval and source evaluation.
– Refining writing skills for academic papers, reports, and presentations.
– Cultivating effective presentation techniques, including content structuring and public speaking.
– Providing opportunities for practice and feedback to refine skills and track progress.

Course Objectives

By the end of this course, students will be able to demonstrate mastery of academic methodology,
including effective study planning and time management. They will exhibit advanced skills in critical reading
and analysis of academic texts, applying effective research techniques to retrieve and evaluate information from various sources.
Students will be capable of producing high-quality academic writing, including essays, reports, and presentations,
and will use presentation techniques to communicate their ideas clearly and persuasively.
Finally, they will engage in self-assessment and feedback processes to continuously improve their academic skills.

Semester 2

Stochastic Processes and Calculus
Stochastic Processes and Calculus
Pricing and Hedging of Derivatives
Corporate Accounting and Finance
Optimization and Computational Methods in Finance
Actuarial Science
Digital Skills Development


This course offers an in-depth exploration of stochastic processes and stochastic calculus, essential tools in various fields such as finance, engineering, and physics.
The module covers fundamental concepts such as Gaussian processes, Brownian motion, martingales, stochastic integration, and stochastic differential equations.
Additionally, it addresses advanced topics like arbitrage pricing and the application of stochastic calculus to the pricing of financial derivatives.

Course Objectives

By the end of this course, students will understand the fundamental properties and characteristics of Gaussian processes and Gaussian variables.
They will explore the properties and applications of Brownian motion, including its continuity and strong Markov property.
Students will gain mastery in filtrations, martingales, and stopping times, which are essential tools in stochastic analysis.
They will study continuous semimartingales and their quadratic variation, laying the groundwork for advanced stochastic calculus.


Additionally, students will develop the ability to construct stochastic integrals and apply Itô’s formula to solve stochastic differential equations.
They will master Girsanov’s theorem and its applications in measure change and risk-neutral pricing.
Finally, students will examine practical applications such as arbitrage pricing and the evaluation of American options using stopping times and stochastic calculus techniques.



This module provides an in-depth exploration of derivative pricing and hedging strategies. It begins with an introduction to the importance of derivatives and an overview of pricing and hedging principles,
then delves into various financial modeling concepts essential for understanding derivative pricing. Topics include the construction and application of binomial tree models, the use of the Black-Scholes model for option pricing and hedging, and a comparison between the two models.


The module also analyzes the implications of the no-arbitrage assumption, the characteristics of complete and incomplete markets, and the computation and application of risk-neutral probabilities in derivative pricing.
It covers derivative pricing methods, the construction of replicating portfolios, and the implementation of effective hedging strategies.
The course concludes with an introduction to stochastic differential equations and their relevance in finance.

Course Objectives

The objective of this module is to provide students with an understanding of the theories and techniques related to the continuous-time pricing and hedging of derivative securities.
The syllabus aims to equip students with the knowledge and skills necessary to understand and apply pricing and hedging techniques in real-world financial scenarios.


By the end of this module, students should be able to understand the fundamental principles of derivative pricing and hedging,
apply financial models to accurately price derivative securities, and analyze the role of arbitrage in derivative pricing,
as well as the implications of complete and incomplete markets.
They will also learn to calculate risk-neutral probabilities and use them in derivative pricing,
construct replicating portfolios for hedging derivatives, and grasp the basics of stochastic differential equations and their applications.



This comprehensive module integrates the fundamental principles of accounting and corporate finance to provide students with a broad understanding of financial management within organizations.
In the Corporate Finance component, students explore corporate theory, capital structure theories, and agency frictions, examining their implications for financial decision-making.
Topics include the time value of money, investment budgeting techniques, valuation methods such as discounted cash flow (DCF) and relative valuation, and considerations related to capital structure decisions.
Students also study corporate taxation basics, debt financing options, bankruptcy processes, and banking operations.


Simultaneously, the Accounting component equips students with essential skills in analyzing, interpreting, and reporting financial statements.
They learn to analyze balance sheets, income statements, and cash flow statements, perform ratio analyses to assess performance, and detect fraud in financial statements.
Understanding key accounting concepts, regulatory sources, and interpreting annual reports are vital elements of this component.
Additionally, students delve into corporate taxation principles, sustainability reporting, and their implications for financial decision-making.
Through this integrated approach, students develop a comprehensive understanding of the interaction between accounting practices and corporate finance strategies,
preparing them for effective financial management roles in diverse organizational settings.

Course Objectives

By the end of this course, students will:


– Understand the theoretical foundations of corporate finance, including corporate theory, capital structure, and agency frictions.
– Analyze the impact of taxation on capital structure decisions and financial performance.
– Explore the dynamics of debt financing, bankruptcy, and banking operations in the context of financial engineering.
– Develop skills in analyzing and interpreting financial statements, including constructing financial statements and calculating key ratios.
– Examine corporate taxation principles and their implications for investment decisions and financial reporting.
– Assess the value of environmental, social, and economic sustainability reporting as an alternative to traditional financial reporting methods.



This course introduces students to the fundamental principles of optimization and computational methods applied to finance.
It covers various optimization techniques and their applications in financial engineering, including portfolio optimization, risk management, derivative pricing, and asset-liability management.
Additionally, the course includes numerical methods for solving partial differential equations (PDEs) relevant to finance.
Students will learn how to formulate financial problems into optimization models and use computational methods to solve them efficiently.

Course Objectives

– Understand the theoretical foundations of optimization and computational methods in finance.
– Formulate financial problems into optimization models and apply computational algorithms to solve financial optimization problems.
– Explore the applications of optimization techniques in portfolio management, risk evaluation, and derivative pricing.
– Develop the ability to analyze and interpret optimization results in financial decision-making processes.
– Gain practical experience through programming assignments and real-world case studies.
– Understand numerical methods for solving PDEs and their applications in finance.



This module provides a comprehensive overview of the principles of insurance, modeling techniques, and actuarial practices.
It covers fundamental concepts such as insurance principles, risk assessment, pricing strategies, life and non-life insurance modeling, reinsurance fundamentals, insurance accounting, and social insurance systems.
Through theoretical teachings and practical applications, students gain insights into the economic impact of insurance, regulatory frameworks, risk assessment, premium setting, and industry-specific financial reporting,
preparing them for roles in insurance, actuarial science, risk management, and related fields.

Course Objectives

The objectives of this course aim to enable students to understand the fundamental principles of insurance and pensions,
as well as the financial environment in which most actuarial work is conducted, focusing on key products and principles of insurance and pensions.
Students will learn to apply actuarial techniques, particularly in the areas of insurance, pensions, and social security.
They will also be trained to apply essential aspects of risk management to find appropriate solutions while effectively utilizing their technical knowledge and skills in actuarial science.



This course aims to equip students with essential digital skills for navigating modern finance.
It emphasizes the importance of digital literacy, mastery of information research and evaluation, use of digital communication tools,
optimization of productivity through digital tools, promotion of ethical conduct in financial contexts, and adaptation to emerging financial technologies for professional development.

Course Objectives

By the end of the course, students will understand the importance of digital literacy in finance,
develop mastery in researching and evaluating financial information online,
acquire skills in using digital communication and productivity tools for financial tasks,
demonstrate ethical awareness and responsible digital citizenship,
and learn to adapt to emerging financial technologies for their ongoing professional development.

Semester 3

Portfolio Management
Portfolio Management
Financial Econometrics
Asset-Liability Management (ALM)
Interest Rate Derivatives and Foreign Exchange Derivatives
Quantitative Risk Management and Regulation
Navigating Cultural Diversity in Africa
Professional Skills: Communication and Leadership


This module offers a rigorous and up-to-date study of the key concepts in modern portfolio management.
The course aims to provide learners with a deep understanding of the theoretical foundations and analyses of asset management,
as applied by investors and portfolio managers. It covers financial securities and how to combine them to construct optimal portfolios,
portfolio selection processes, diversification strategies, and equilibrium models in capital markets.
Additionally, it addresses portfolio management in fixed-income markets through immunization processes.
Overall, the module focuses on the principles, methods, and practices necessary for solving portfolio selection problems in the decision-making process.

Course Objectives

The learning outcomes aim to enable students to understand and explore modern portfolio management,
optimize portfolio selection problems, explore fixed-income portfolio management, and grasp key principles of asset pricing models.



This course aims to provide students with a comprehensive understanding of econometric techniques applied to finance.
Econometric methods will be taught with a particular emphasis on their application in financial data analysis
and modeling financial markets. Key topics include linear regression, modeling of financial time series,
estimation of ARCH/GARCH models, hypothesis testing in finance, and analysis of cointegration and causality.

Course Objectives

By the end of the course, students will be able to understand the fundamental concepts of econometrics applied to finance,
acquire practical skills in applying econometric techniques to financial data analysis,
estimate and interpret financial econometric models, and develop the ability to use statistical and financial software for conducting econometric analyses.



This course provides a thorough understanding of asset-liability management (ALM) in the banking sector,
including interest rate and liquidity risk management. It is designed to give students comprehensive knowledge
of the principles, techniques, and strategies used in managing the assets and liabilities of financial institutions.
Focusing on both the practical and theoretical aspects of ALM, the course addresses key concepts such as balance sheet analysis,
liquidity and interest rate risk management, as well as risk hedging strategies and banking engineering.
Students will have the opportunity to explore real-world case studies, analyze financial data, and develop practical skills in financial modeling.

Course Objectives

By the end of the course, students will understand the key challenges and issues of asset-liability management in the banking sector,
the implications of ALM for the banking industry, and be able to measure and manage interest rate and liquidity risks.
They will grasp the origins of these risks, understand the fundamental principles of ALM in financial institutions,
and acquire practical skills in balance sheet analysis and liquidity and interest rate risk management.
Furthermore, they will explore various risk hedging techniques and banking engineering used in ALM,
develop the ability to model economic capital, internal transfer rates, and evaluate pricing based on RAROC (Risk-Adjusted Return on Capital).
Finally, they will apply theoretical concepts to real-life situations and develop strategic solutions to optimize the financial performance of institutions.



This module provides an in-depth exploration of interest rates, derivatives, and essential modeling techniques in the financial industry.
Students will examine the dynamics of interest rates, focusing on measurement methodologies, benchmark rates, and their implications for various financial instruments.
The course covers advanced topics such as interest rate derivatives, including bond options, swaptions, and cancellable swaps,
emphasizing their role in hedging interest rate risks. Students will also analyze equilibrium and no-arbitrage models for interest rates,
gaining practical experience in modeling forward rates. Through real-world case studies and practical exercises, the module aims to develop critical thinking skills
and enhance students’ ability to apply theoretical concepts to complex financial problems.
It is designed to prepare students for careers in finance, risk management, and financial engineering by providing a solid foundation in interest rate modeling
and pricing of fixed-income derivatives.

Course Objectives

By the end of this module, students will demonstrate a deep understanding of interest rate dynamics,
be able to analyze and price interest rate-related instruments confidently, and apply advanced techniques for managing interest rate risks.
They will evaluate the impact of foreign exchange derivatives on currency risk and use theoretical concepts from equilibrium and no-arbitrage models to address practical finance challenges.
Additionally, they will develop skills in modeling forward rates, enhance their analytical capabilities through case studies,
collaborate effectively with peers, and communicate complex financial concepts clearly. Ultimately, they will be well-prepared for careers in finance, risk management, and financial engineering.



The primary goal of this module is to provide students with advanced knowledge and skills in managing financial risks,
with a focus on post-crisis contexts. This program aims to equip students with in-depth knowledge and practical skills in evaluating and managing financial risks,
emphasizing understanding and managing different types of risks within banks and financial institutions.

Course Objectives

By the end of this module, students should be able to:


– Understand key pricing and risk management models in financial markets.
– Analyze the implications of recent financial crises on interest rate markets and models.
– Acquire knowledge of various types of financial risks, including market risk, credit risk, operational risk, and liquidity risk.
– Develop skills to identify, measure, and manage market, credit, and liquidity risks in banking operations.
– Evaluate strategies for managing interest rate and liquidity risks in the banking sector.
– Apply modeling techniques in asset-liability management (ALM) to mitigate interest rate and liquidity risks.



The aim of this module is to enable students to understand the importance of cultural and artistic capital in personal and professional development.
Students will explore various forms of cultural and artistic expression to broaden their horizons and sensitivity.
They will develop practical skills in at least one artistic or cultural discipline and learn to critically interpret and appreciate cultural and artistic works.
Ultimately, the course aims to foster creativity and personal expression through artistic and cultural projects.



This module aims to develop a set of essential skills for success in the modern professional world.
It focuses on the personal and professional development of students, preparing them to face challenges encountered in the workplace.
The course combines practical and behavioral skills vital for success in today’s professional environment,
equipping students to adapt and excel in various work settings.

6-Month Internship: Principles and Procedures

The internship represents the culmination of the Master’s program in Financial Engineering, allowing students to apply their theoretical knowledge in real-world contexts and gain practical experience in their chosen field. It provides a valuable opportunity for students to acquire hands-on experience, develop key skills, and prepare for their future careers in financial engineering. Collaborative efforts between the Africa Business School and host organizations ensure the success and relevance of the internship experience. 

General Principles 

  • Students must complete an internship during the fourth semester of the program. 
  • The internship must take place within an organization affiliated with the University or in the socio-economic environment. 
  • Special emphasis is placed on internships in financial institutions such as banks (trading rooms, risk management departments, internal audit, ALM departments), insurance companies, asset management firms, consulting firms, etc. 

 

SELECTED FACULTY

LEARN MORE ABOUT THE PROGRAM

The faculty is made up of high-level finance research professors and senior executives experienced in financing techniques.

Apply Now