Teaching Tool :

R (Statistical Programming Language)

Course Description :

This course introduces core concepts of quantitative finance and financial modelling. It combines theoretical foundations with practical applications using real financial data and R programming. Students will learn capital markets theory, portfolio optimization, risk management, and asset pricing models. This course also prepares students for Level I of the CFA exam.

Learning Outcomes :

• Understand financial markets and their instruments (equities, bonds, derivatives, cryptos).
• Analyze and model risk-return profiles for individual assets and portfolios.
• Apply portfolio theory and asset pricing models in real-life settings.
• Implement financial models in R, including data manipulation and visualization.
• Understand the role of economic factors and macro risks in financial decision-making.
• Evaluate investment decisions considering ethical and sustainable development goals.

Topics Covered :

• R Programming: Data manipulation, loops, functions, visualization
• Financial Instruments: Bonds, equities, derivatives, cryptocurrencies
• Risk & Return: Historical returns, measures of risk, statistical tests
• Portfolio Theory: Diversification, efficient frontier, mean-variance optimization
• CAPM & Index Models: Risk pricing, performance evaluation
• Efficient Market Hypothesis: Event studies and EMH tests
• Multifactor Models & Hedging: Inflation hedging, economic factor models
• Applied Portfolio Management & FinTech Applications

Assessment Structure :

• 40% Continuous Assessment: Moodle quizzes and exercises
• 60% Final Project: R-based portfolio modelling and analysis with presentation