Courses at Roma Tre University:
  • Finanza Computazionale (Master Degree), 2015 - present.
  • Financial Modeling (Master Degree), 2018 - present.

  • A rapid introduction to MATLAB
  1. MATLAB basics: Preliminary elements; Variable assignment; Workspace; Arithmetic operations; Vectors and matrices; Standard operations of linear algebra; Element-by-element multiplication and division; Colon (:) operator; Predefined function; inline Function; Anonymous Function
  2. M-file: Script and Function
  3. Programming fundamentals: if, else, and elseif scheme; for loops; while loops
  4. Matlab graphics
  5. Preliminary exercises on programming
  6. Exercises on the financial evaluation basics
  • Preliminary elements on Probability Theory and Statistics
  1. Random variables
  2. Probability distributions
  3. Continuous random variable
  4. Higher-order moments and synthetic indices of a distribution
  5. Some probability distributions: Uniform, Normal, Log-normal, Chi-square, Student-t
  • Linear and Non-linear Programming
  1. Some MATLAB built-in functions for optimization problems
  2. Multi-objective optimization: Determining the efficient frontier
  • Portfolio Optimization
  1. Portfolio of equities: Prices and returns
  2. Risk-return analysis: Mean-Variance; Effects of the diversification in an Equally Weighted portfolio; Mean-MAD; Mean-MinMax; VaR; Mean-CVaR; Mean-Gini portfolios
  3. Bond portfolio immunization
  • Further elements on Probability Theory and Statistics
  1. Introduction to the Monte Carlo simulation
  2. Stochastic processes: Brownian motion; Ito's Lemma; Geometrical Brownian motion
  • Pricing of derivatives with an underlying security
  1. Binomial model (CRR): A replicating portfolio of stocks and bonds; Calibration of the model; Multi-period case
  2. Black-Scholes model: Assumptions of the model; Pricing of a European call; Pricing equation for a call; Implied Volatility
  3. Option Pricing with Monte Carlo Method: Solution in integral form; Path Dependent Derivatives.