The course aims at providing base elements for computer programming on some of the most classic topics in Mathematics, Economics, and Finance. At the end of the course, the student is going to be able to: Get the solution of ordinary differential equations; draw 2D plots, 3D surfaces, and the restriction of a 3D surface on a specific plane; plane; students will be able to analyse and set up the pseudocoding of a financial problem involving the use of mathematical and econometric processes and to write the relevant codes.

The student will have acquired basic knowledge of programming techniques in Matlab and Python. He/she will be able to write codes concerning problems of mathematics, statistics and financial mathematics. He/she will acquire knowledge of financial models and will be able to write codes, modify and adapt existing codes to suit new needs. This knowledge will be assessed by means of classroom exercises and homework, which can be discussed with the teacher. Ability to apply knowledge and understanding The student will be able to know the syntax and structures necessary for programming; he/she will also be able to provide a pseudocoding of a series of economic, econometric and mathematical problems that are frequently repeated in the operational context. The achievement of these objectives will be assessed through the evaluation of exercises carried out in the classroom and at home, and through the evaluation of ongoing and final tests. Autonomy of judgement: the student will have developed such knowledge as to be able to assess the correctness and appropriateness of the codes developed, to be able to identify errors and to be able to resolve them.

Basic principles of computer programming: execute an instruction, iterations, conditional choices. Input and output, pseudocode. MATLAB: interface, operations on numbers, vectors, and matrices, solution of ordinary differential equations and systems, solution of unconstrained and constrained optimization problems. Python: editor, packages, base and advanced instructions.

[*] C. Pocci , G. Rotundo, R. De Kok (2016) Matlab economic and financial applications, I ed., Apogeo Education, 8891623027 / 9788891623027 [**] “Python for applications in economics and finance”. Lecture notes. [***] Slides of the lessons.

Frontal instruction; hands on computer exercises

Tests; the student has to show to be able to write down the MATLAB and Python instructions that solve a specific assignment and to answer to questions on the program; eventually posed as multiple choice tests.

N/A

Sustainability issues are covered in several lectures in the second part of the course (from lecture 6 to lecture 11). That part is devoted to writing matlab and/or Python codes for the economic-financial models covered in this and other courses. In particular, portfolio issues (frontier estimation), issues of a' la Sharpe style regressions, and issues related to multivariate and smart beta estimation models involve the addition of ESG factors that the student must include in the model. The aim is to estimate the impact and/or the significance (in all models) and the ranking (in penalized regression models) of sustainability factors.