Teaching code

4S00489

Teacher

Coordinator

Credits

9

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/03 - ECONOMIC STATISTICS

Period

Primo semestre (lauree magistrali) dal Oct 3, 2022 al Dec 23, 2022.

Lessons timetable Moodle Seminars 0

Learning objectives

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.

Prerequisites and basic notions

The course requires knowledge of the fundamental notions of probability calculus and statistical inference taught in the bachelor's degree programmes.

Program

1. Prices and index numbers
* Prices and returns
* Moving averages
* Index numbers and stock indexes
2. Probability and inference
3. Risk measures and validation of statistical models
* Risk measures
* Monte Carlo
* Cross-validation and backtesting
4. Analysis of returns: empirical facts
* Unconditional distribution of returns
* Time dependence and autocorrelation function
* Correlograms
5. Analysis of returns: stochastic mean models
* Stochastc processes: iid, AR, MA and ARMA
* Identification and fitting of ARMA processes
* Conditional risk measures on ARMA processes
6. Analysis of returns: stochastic variance models
* Stochastic processes: ARCH and GARCH
* Identification and fitting of GARCH processes
* Conditional risk measures on GARCH and ARMA-GARCH processes
7. Introduction to extreme value theory
* Heavy-tailed distributions and risk measures
* Parametric and semiparametric models of conditional risk measures
* Generalised Pareto distribution
Methods and techniques illustrated throughout the course are applied to real data by means of the open source environment R.

Bibliography

Didactic methods

Frontal lectures in classroom and recorded lectures available online.

Learning assessment procedures

The assessment of learning outcomes consists in a written examination.
The examination consists of:
* six short, multiple choice, or calculated questions
* one open-ended question
* one open-ended question chosen from two available
All kinds of questions may be focussed on theoretical and methodological issues, may consist in exercises, or may require the student to discuss and analyse some practical problem using notions and tools learned throughout the course.
The teacher may require students to take an oral examination which completes the evaluation of the acquired knowledge. The final grade may be equal, higher or lower than the grade got on the written part of the exam.

Evaluation criteria

The written examination assesses the level of knowledge of the topics of the course, the mastery of technical language and the writing skills, the ability to analyse financial time series by means of the methods illustrated in the course and the ability to interpret the results of the analyses.

Criteria for the composition of the final grade

The examination score is on a 30-point scale (passing mark: 18).

Exam language

Italiano