Code
MUSE FIN 3409
Niveau
L3
Discipline
Finance
Langue
Anglais/English
Crédits ECTS
3
Heures programmées
18
Charge totale étudiant
60
Coordonnateur(s)
Département
- Data analytics, Économie et Finances
Equipe pédagogique
Introduction au module
This course provides students with the mathematical and statistical foundations required for finance and management studies. It covers core computational tools, linear and quadratic functions, differentiation, time value of money, probability and descriptive statistics. Students will learn how to apply these quantitative methods to solve financial problems, interpret numerical results and support analytical decision-making.
Finalité d'apprentissage (Bloc de compétences)
- 6. Concevoir et/ou piloter des solutions de gestion innovantes en veillant à garantir une création de valeur soutenable pour toutes les parties prenantes
Objectifs d'apprentissage
- 6.2 - Optimiser l'usage d'outils adaptés aux différents domaines de gestion, et définir et interpréter les KPI pertinents, afin de mesurer et garantir une création de valeur durable et soutenable pour toutes les parties prenantes.
Traits de compétences
By the end of this PGE L3 course, students will be able to:
1. Apply core computational techniques, including percentages, exponentials, logarithms, summations and products, to solve quantitative problems in finance.
2. Solve, graph and interpret linear functions and systems of simultaneous linear equations in applied financial contexts.
3. Analyse quadratic functions by solving equations, graphing functions and identifying key characteristics such as the vertex.
4. Calculate and interpret average and instantaneous rates of change, derivatives and second-order derivatives, including their financial applications.
5. Apply time value of money techniques to compute compound values, discounted values and loan repayment amounts.
6. Use basic probability rules, random variables and probability distributions to analyse uncertainty in financial situations.
7. Calculate and interpret descriptive statistics, including measures of centre, spread, relationship and asymmetry, in order to summarise and analyse financial data.
Contenu : structure du module et agenda
1. Computation
1.1 Percentages
1.2 Exponentials
1.3 Logarithms
1.4 Summation
1.5 Product
2. Linear Functions
2.1 Solving linear equations
2.2 Graphing linear functions
2.3 Solving simultaneous linear equations
3. Quadratics
3.1 Quadratic functions
3.2 Graphing quadratic functions
3.3 Solving quadratic functions
3.4 Vertex
4. Differentiation
4.1 Average rate of change
4.2 Instantaneous rate of change
4.3 Common derivatives and rules
4.4 Second-order derivatives
4.5 Derivative graphs
4.6 Financial applications
5. Time Value of Money
5.1 Compound value
5.2 Discounting
5.3 Loan repayment
6. Probability
6.1 Probability rules
6.2 Random variables
6.3 Probability distributions
7. Descriptive Statistics
7.1 Measures of centre
7.2 Measures of spread
7.3 Measures of relationship
7.4 Measures of asymmetry
Contribution à l'atteinte des ODD (Objets du Développement Durable)
SDG 4 – Quality Education: This course contributes to SDG 4 by developing students’ foundational quantitative skills, enabling them to engage more effectively with finance, economics and management courses throughout their academic and professional development.
Nombre d'ODD abordés parmi les 17
1
Apprentissage
synchrone
Méthode pédagogique
The course combines lectures, guided exercises, case studies and problem-solving sessions. Lectures introduce the mathematical and statistical concepts required for financial applications. Guided exercises and problem-solving sessions help students apply methods step by step and consolidate calculation techniques. Case studies connect quantitative tools to practical financial situations and decision-making problems.
Système de notation et modalités de rattrapage
Attendance is mandatory for this course.
The assessment evaluates students’ ability to apply the mathematical and statistical tools covered in class to structured financial problems. It measures their capacity to perform calculations accurately, solve equations, interpret functions and graphs, apply time value of money techniques, analyse uncertainty through probability tools, and summarise financial data using descriptive statistics.
The final grade consists of two closed-book written exams:
• Mid-term exam: 40% of the final grade, 1 hour.
• Final exam: 60% of the final grade, 2 hours.
• Bonus points may be awarded based on attendance and participation in class discussions.
In case of absence from an exam, the grade for that exam will be 0. If the absence is justified and validated by the administration, the corresponding exam will be neutralised.
There is no separate resit exam for the mid-term exam alone.
In case of failing the course, a closed-book written resit exam will be organised. The resit exam will stand alone as the final grade for the course and will be capped at 10/20.
Règlement du module
1. Professor–Student Communication
The professor will communicate with students through their institutional school email address (IMT-BS/TSP) and/or the Moodle portal. No communication will be sent to personal email addresses. Students are responsible for regularly checking their IMT-BS/TSP mailbox and Moodle announcements.
Students may contact the professor by email using the professor’s institutional email address. When necessary, students may meet the professor during office hours or by appointment.
2. Students with Accommodation Needs
Students who have a disability or any specific accommodation need that may affect their ability to complete the required work must inform the professor during the first class, in order to facilitate the necessary arrangements in accordance with the school’s applicable procedures.
3. Class Attendance and Behaviour
Students are expected to attend class, arrive on time and behave respectfully throughout the session.
Unless explicitly authorised by the professor, the use of electronic devices, including computers, mobile phones and tablets, is prohibited during class. Students are not allowed to take photos, videos or audio recordings in the classroom without the professor’s explicit consent.
Students must avoid disruptive or disrespectful behaviour, including arriving late, leaving early, sleeping, reading non-course material, using inappropriate language, speaking over others, eating or drinking during class, or engaging in any behaviour that disturbs the class. A warning may be given for a first violation. Repeated violations may lead to penalties, exclusion from the class and/or disciplinary proceedings.
A delay of up to 10 minutes is tolerated at the beginning of class. Attendance will be recorded on Edusign during this 10-minute period using a QR code provided by the professor at the start of each session.
Leaving the classroom before the end of the session without the professor’s approval will be considered an absence.
In the case of remote learning, students must keep their camera on unless instructed otherwise by the professor.
4. Exams and Assessments
Students must arrive on time for exams and other assessments. A delay of up to 10 minutes is tolerated.
No student may continue the exam once the allocated time is over. No student may leave the room during an examination unless they have finished the exam and handed in all required documents.
Only the following items are allowed during exams:
• pens;
• student card;
• a non-programmable calculator, or a programmable calculator with activated EXAM mode.
All other items are prohibited.
Possession of any unauthorised electronic device, even if turned off, will be considered cheating.
Possession of a programmable calculator without activated EXAM mode, even if turned off, will be considered cheating.
A random check may be carried out after students are instructed to activate EXAM mode. Failure to prove that EXAM mode has been activated after this instruction will be considered cheating.
Students are responsible for knowing how to activate EXAM mode on their calculator before the exam.
Any violation of the instructions given by the professor or the examination supervision team will be reported to the Discipline Committee.
Références obligatoires et lectures suggérées
1. Anthony, M. and Biggs, N., Mathematics for Economics and Finance: Methods and Modelling.
2. Sydsæter, K., Hammond, P., Strøm, A. and Carvajal, A., Essential Mathematics for Economic Analysis.
3. Capiński, M. and Zastawniak, T., Mathematics for Finance: An Introduction to Financial Engineering.
4. Newbold, P., Carlson, W. L. and Thorne, B., Statistics for Business and Economics.
5. Brooks, C., Introductory Econometrics for Finance.
6. Jacques, I., Mathematics for Economics and Business.
Mots-clés
Financial mathematics; percentages; logarithms; linear functions; quadratic functions; differentiation; time value of money; compound interest; discounting; loan repayment; probability; random variables; descriptive statistics; financial applications.
Prérequis
LinkedIn Learning - Statistics Foundations 1 and 2