Ateneo - UPO

The main objective of the course is to introduce the students to Matlab programming, providing some of the basic IT tools used in quantitative finance. The course will be mainly applicative with several examples and exercises using Matlab. When necessary, a refresh of some theoretical argument will be made. The course is at the introductory level and will be the basis for further study in the subsequent curriculum courses.

The course is worth 4 CFU, corresponding to 30 hours of classroom teaching. Overall, approximately 12 hours consist of lecture-based teaching (DE) and 18 hours of interactive teaching (DI), with variable proportions within each lesson.

-Knowledge and understanding: Students will acquire a basic knowledge of the Matlab programming language and of the main packages commonly used in quantitative finance. The understanding objective will be pursued by presenting students with simple problems requiring the ability to select and develop the algorithmic procedures introduced.
-Applying knowledge and understanding: Students will learn to correctly apply the numerical algorithms studied, understanding their functionalities and limitations, and to develop simple programs in Matlab, autonomously choosing the most suitable procedure.
-Making judgements: Students will be able to use the acquired knowledge, both conceptually and operationally, with autonomous evaluation skills.
-Communication skills: Students will acquire the technical language typical of computer programming and will also develop the ability to argue for and justify the implemented solutions.
-Learning skills: Students will learn how to select and apply the appropriate numerical techniques presented during the course.

Linear algebra, basic optimization tools from the courses of Calculus 1 and 2

Interactive classes with PC use, integrated when necessary by theoretical notions.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/servicesstudents-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

Pass/fail assessment (no grade). The assessment takes place at a computer. Students are given a set of three exercises to complete in Matlab within one hour: one compulsory exercise designed to test knowledge of the main commands and simple Matlab programs, and two more articulated exercises designed to test understanding of the programming language through the ability to select the most appropriate tool and the ability to implement more complex programs.
A pass is achieved if the compulsory exercise and at least one of the two articulated exercises are completed correctly, i.e. the Matlab code compiles and produces correct numerical results. In addition, students are required to write a brief comment on the procedures used and the results obtained in relation to the Matlab functions employed. This comment is part of the exercise and must be consistent with the Matlab code produced.
Registration for the exam via the student portal is mandatory: once the maximum number of exam participants has been reached, the system will not allow further registrations. A final assessment is scheduled at the end of the lessons for first-year students.

1. Introduction to Matlab: variables, Matrices in Matlab: calculus with matrices, inverse, determinant,
solution of linear systems.
2. Graphics in Matlab, for loop and if logical operator,
functions, plots, read data from Excel sheet, write data to Excel sheet.
3. Some basic applications in Finance and Statistics.
4. Introduction to optimization with Matlab.

By the end of the course, students are expected to have achieved the following learning outcomes, articulated according to the Dublin Descriptors:
Knowledge and understanding
● Know the basic elements of the Matlab language: variable types, matrix calculus (operations between matrices, inverse and determinant), solving linear systems.
● Know the main control statements (if, while, for), functions, and how to read/write data from and to a spreadsheet.
● Know the basic Matlab tools for graphical representation (2D, with an introduction to 3D), for elementary statistical analysis, and for simple optimization problems applied to quantitative finance.
Applying knowledge and understanding
● Be able to write and run, independently, simple Matlab scripts that solve matrix-calculus and basic statistical-analysis problems.
● Be able to choose and correctly apply the control statement or function best suited to solving a given applied problem, recognising its potential and limitations.
● Be able to implement, starting from a quantitative-finance problem expressed in applied terms, a simple Matlab program that provides its numerical solution.
Transversal abilities (3rd, 4th and 5th Dublin Descriptors)
● Making judgements: be able to independently assess the correctness and plausibility of the numerical results produced by a Matlab program.
● Communication skills: be able to comment, including in written form, on the procedures implemented and the results obtained, using appropriate technical terminology.
● Learning skills: be able to independently transfer the Matlab techniques learned to the solution of new and increasingly complex problems, including in other courses of the curriculum.
Minimum passing level
Students demonstrate that they:
● know the basic Matlab commands needed to solve the compulsory exercise of the idoneità test;
● can produce Matlab code that compiles and returns correct numerical results for at least one of the two articulated exercises;
● can accompany the code with an essential comment, consistent with what has been implemented.
Advanced level
Students further demonstrate that they:
● can independently choose, among several possible alternatives, the most efficient Matlab procedure to solve articulated problems in quantitative finance and statistics.