Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° Year activated in the A.Y. 2017/2018
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Financial statistics (2017/2018)
Teaching code
4S00489
Teacher
Coordinator
Credits
9
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/03 - ECONOMIC STATISTICS
Period
Primo Semestre Magistrali dal Oct 2, 2017 al Dec 22, 2017.
Learning outcomes
The goal of the course is to introduce students to the modern econometric and time series tools for analyzing and modeling financial returns and volatility.
The course provides students with theoretical and practical knowledge of the statistical and computational skills needed for the identification, estimation and test of stochastic processes used by the financial operators to manage risk and develop investment strategies.
At the end of the course, students will be able to critically compare the price dynamic of different assets and to estimate the parameters of the stochastic processes that captures the main stylized facts observed in the financial markets.
Program
1. Financial prices and stock indexes
1.1 Price formation in financial markets
1.2 Stock indexes
- Computational methods
- Main Italian stock indexes
1.3 Correction factors for financial prices
2. Empirical Properties of Returns
2.1 Financial returns
2.2 Distributional properties of returns
2.3 Correlation properties of returns. The autocorrelation function.
3. Stochastic processes for returns
3.1 Moments: definitions and estimation
3.2 Stochastic processes for financial returns: white noise, random walk, autoregressive, moving average.
3.3 Box-Jenkins procedure: preliminary adjustments, identification, estimation and test.
4. Volatility of financial returns
4.1 Characteristics of Volatility.
4.2 Models with constant volatility and models with time-varying volatility.
4.3 Symmetric GARCH processes.
Text books
- G. M. Gallo, B. Pacini, Metodi quantitativi per i mercati finanziari, Carocci, Roma, 2013 (VII Ristampa).
- Bee M., Santi F., Finanza Quantitativa con R, Apogeo, 2013
The interaction with students will be encouraged by discussing real financial cases. Exercises will be held in the classroom by means of the freeware R statistical software and analyzing the prices of financial assets quoted in the Italian market.
All slides projected during lessons will be made available on the e-learning platform before the beginning of the course. For this reason, students are strongly invited to register to the e-learning page of the course. Lectures will be recorded. Videos will be made available the next few days to allow students to revise or to attend lessons to which they have not been able to join directly. The availability of videos is also extended to all students who are unable to attend for work reasons or because they are abroad within the Erasmus program.
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| GALLO M.-PACINI B. | Metodi quantitativi per i mercati finanziari | Carocci editore | 2002 | 8843023063 |
Examination Methods
Both the student's preparation will be evaluated as well as its ability to interpret and evaluate the results of the analyses based on the topics taught during the course.
The written test is compulsory. The structure of the test is as follows:
- one open question (up to 10 points, out of 30),
- two numerical exercises (up to 20 points, out of 30). Data will be provided for the solution of real case-studies using the basic tools learned during classes.
The oral test is optional.
Project work (optional activity. For attending students only)
It is carried out by groups of 3/4 students. The first part of the project work must be completed and sent by e-mail to the teacher for evaluation by November 13, 2017. Students will have to demonstrate that they are able to implement all the techniques studied during course through the software R.
The final version of the project work must be sent by email to the teacher for approval at least one week before the exam.
Project work should NOT be presented in the classroom.
Project Work's evaluation will entitle you to a bonus of up to 3/30 that will be added to the grade you have earned in the written test, provided the written grade is equal to or greater than 18/30. The bonus will be valid until September 2018. The bonus can be added to the written exam evaluation only once.
