69062 - Statistical Methods for Financial Markets

Course Unit Page

Academic Year 2018/2019

Learning outcomes

The course deals with the introduction to financial risk analysis and portfolio management. In its first part, the course covers the basics of time series analysis with particular emphasis on ARIMA modelling and forecasting. The second part deals with the analysis of financial time series.

Course contents

Modulo 1 - Introduction to time series analysis

  1. Basic definitions and main motivations.
  2. Introduction to stochastic processes. Linear processes. Autocovariance e autocorrelation.
  3. ARIMA modelling.
  4. The Box-Jenkins procedure.
  5. Forecasting with ARIMA models.
  6. Decomposition and seasonal adjustments.
  7. Deterministic trends and stochastic trends. Unit root tests and complex dependence.

Modulo 2 - Analysis of financial time series

  1. Features of financial time series.
  2. Analysis of financial returns.
  3. Models for financial time series
    - models for volatility;
    - threshold and regime switching models.
  4. Introduction to time-continuous models.

Readings/Bibliography

  1. T. Di Fonzo, F. Lisi, Serie storiche economiche, Carocci, Roma, 2015 (III Ristampa).
  2. G. M. Gallo, B. Pacini, Metodi quantitativi per i mercati finanziari, Carocci, Roma, 2013 (VII Ristampa).
  3. R.S. Tsay, Analysis of Financial Time Series, 3rd edition, Wiley, 2010

Teaching methods

  • Lectures
  • Classes

Assessment methods

Written examination composed of

  • Theoretical questions
  • Exercises

It is possible to take separately the exam for each of the two Modules.

Teaching tools

  • Slides of the course
  • Exercises

Office hours

See the website of Simone Giannerini

See the website of Greta Goracci