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CODE 108766
ACADEMIC YEAR 2022/2023
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR ING-INF/04
TEACHING LOCATION
  • GENOVA
SEMESTER 1° Semester
TEACHING MATERIALS AULAWEB

OVERVIEW

The course presents the main modelling techniques for complex dynamical processes related to financial engineering. Moreover, the course addresses the identification methods necessary to evaluate the parameters present in the presented models.

AIMS AND CONTENT

LEARNING OUTCOMES

Knowing the main modelling classes for dynamic processes with attention to those adopted in management engineering; defining a class of candidate models for a specific dynamic process; knowing the features of a parameter identification problem; designing the solution of an identification problem; analyzing the convergence properties of the adopted solution algorithm.

AIMS AND LEARNING OUTCOMES

The learning outcomes of the course refer to the capacity of:

  • understand the dynamic features of a process;
  • define a model suitable for representing the process and fulfil the objectives of the required analysis;
  • knowing the features of an identification problem;
  • knowing the most important classes of identification models;
  • designing the solution of an identification problem.

PREREQUISITES

The course prerequisites refer to basic elements of systems theory, statistics and optimization.

TEACHING METHODS

The course consists in lessons during which the theoretical contents of the course are presented together with the solution of numerical cases and the use of some software frameworks related to the course topics.

SYLLABUS/CONTENT

Definition of the main features of dynamic systems and to the main modelling classes. Introduction to the most important dynamic models adopted in management engineering and financial engineering.

Identification techniques: definition of the parameter identification problem, model families (ARX, ARMAX, OE,  ARXAR, BJ),  MPE identification: convergence theorems, identification for ARX models (least squares identification), for ARMAX models and for ARXAR models, batch and iterative algorithms.

RECOMMENDED READING/BIBLIOGRAPHY

L. Ljung, "System Identification: Theory for the user", Prentice Hall (2nd Edition), 1999.

TEACHERS AND EXAM BOARD

Exam Board

SIMONA SACONE (President)

CECILIA CATERINA PASQUALE

SILVIA SIRI

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam is an oral presentation.

ASSESSMENT METHODS

During the exam the student has to present the main arguments of the course, to solve numerical exercises and to explain the theoretical notions necessary for their solution

Exam schedule

Data appello Orario Luogo Degree type Note
16/01/2023 14:00 GENOVA Orale
01/02/2023 14:00 GENOVA Orale
15/02/2023 14:00 GENOVA Orale
01/06/2023 14:00 GENOVA Orale
27/06/2023 14:00 GENOVA Orale
13/07/2023 14:00 GENOVA Orale
31/08/2023 14:00 GENOVA Orale