Summary
The lectures provide an introduction to MATLAB programming with a focus on finance. The first set of lectures are devoted to the introduction of standard programming of loops and function. A second set of lectures is devoted to the computation of financial returns on assets, and optimization methods applied to portfolio theory. At the end of the lectures, students are expected to master the basics of programming, and apply portfolio theory to real time financial data. Installing MATLAB: Dauphine provides a free licence for students. Please use your own laptop if you can with MATLAB installed. Please have Datafeed, Optimization and Econometrics toolboxes installed.

# Real time macro-data on MATLAB

This is a must-read as all of the lectures will rely on DBnomics. The latter is a database aggregator which can be queried directly from MATLAB. Please read carefully this following note on DBnomics and download as well the MATLAB function which allows to get real time macro data:

# Handouts list

Lecture 1: Introduction to MATLAB Programming
Objectives of the Lecture:

• Utilize the basic mathematical operations;
• Get know the general purpose commands of Matlab;
• Manipulate matrix calculus;

Materials:

Lecture 2: Plotting
Objectives of the Lecture:

• UPlotting 2D and 3D graphs;
• Define the curve shape, titles and legends.

Materials:

Lecture 3: Loops and Conditional Statements
Objectives of the Lecture:

• Mastering the use of conditional statements;
• Coding loops with both while and for.
Materials:

Lecture 4: Functions
Objectives of the Lecture:

• Write a function with n-input arguments;
• Code a function n-output variables;
Materials:

Lecture 5: Bonds and Interest Rates Valuation
Objectives of the Lecture:

• Compute the price of a zero coupon bonds;
• Calculate its interest rate;
• Use loops and functions;
Materials:

Lecture 6: Portfolio Theory
Objectives of the Lecture:

• Understanding the concept of efficient portfolio;
• Compute welfare-maximizing portfolios on real time data;

Materials:

Exam 2017.