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.
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.
The learning outcomes of the course refer to the capacity of:
The course prerequisites refer to basic elements of systems theory, statistics and optimization.
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.
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.
L. Ljung, "System Identification: Theory for the user", Prentice Hall (2nd Edition), 1999.
Ricevimento: By taking an appointment with the teacher (simona.sacone@unige.it)
SIMONA SACONE (President)
CECILIA CATERINA PASQUALE
SILVIA SIRI
The exam is an oral presentation.
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
