Program Overview

Master in Financial Engineering

The Master in Financial Engineering is a program offered by the College of Management of Technology at EPFL. The program is designed to provide students with a comprehensive education in financial engineering, covering topics such as accounting, finance, and risk management.

Study Plan

The study plan for the Master in Financial Engineering is divided into several blocks, each covering a specific area of financial engineering. The blocks include:

• Block 1: Courses
  • Accounting for finance (FIN-411)
  • Convex optimization (MGT-418)
  • HSS: Introduction to project (SHS course offer)
  • HSS: Project (SHS course offer)
  • Introduction to econometrics (MGT-581)
  • Introduction to finance (FIN-401)
  • Probability and stochastic calculus (FIN-415)
• Block 2: Courses
  • Advanced derivatives (FIN-503)
  • Derivatives (FIN-404)
  • Ethical behavior in the financial industry (FIN-419)
  • Interest rate and credit risk models (FIN-416)
  • Investments (FIN-405)
  • Machine learning in finance (FIN-407)
  • Macroeconomics and monetary policy (FIN-424)
  • Quantitative risk management (FIN-417)
• Group 1: Courses
  • Advanced numerical analysis II (MATH-351)
  • Algorithmic game theory (MGT-435)
  • Applied data analysis (CS-401)
  • Causal inference (MGT-416)
  • Cryptography and security (COM-401)
  • Data science for business (MGT-432)
  • Data visualization (COM-480)
  • Deep learning (EE-559)
  • Deep reinforcement learning (CS-456)
  • Financial applications of blockchains and distributed ledgers (FIN-413)
  • Financial big data (FIN-525)
  • Financial intermediation (FIN-420)
  • Fundamentals of machine learning (EE-311)
  • Information: strategy & economics (MGT-431)
  • Information security & digital trust (MGT-493)
  • Information security and privacy (COM-402)
  • Introduction to stochastic PDEs (MATH-485)
  • Machine learning (CS-433)
  • Machine learning I (MICRO-455)
  • Machine learning II (MICRO-570)
  • Machine learning methods in econometrics (MGT-424)
  • Machine learning programming (MICRO-401)
  • Mathematical modelling of behavior (MATH-463)
  • Multivariate statistics (MATH-444)
  • Nature finance (MGT-541)
  • Numerical analysis and computational mathematics (MATH-456)
  • Numerical approximation of PDEs (MATH-451)
  • Numerical integration of stochastic differential equations (MATH-450)
  • Principles of microeconomics (MGT-454)
  • Regression methods (MATH-408)
  • Statistical analysis of network data (MATH-448)
  • Statistical machine learning (MATH-412)
  • Stochastic simulation (MATH-414)
  • Sustainable Finance (FIN-400)
  • Time series (MATH-342)
  • Venture capital (FIN-522)

Master Project

The master project is an essential part of the Master in Financial Engineering program. Students can choose from two options:

• Engineering internship credited with master project (FIN-598)
• Master project in Financial Engineering (FIN-599)

Useful Documents

• MFE Study Plan and Rules
• MFE rules – English version (for information only)