- Oggetto:
- Oggetto:
FINANCIAL ECONOMETRICS
- Oggetto:
FINANCIAL ECONOMETRICS
- Oggetto:
Academic year 2024/2025
- Course ID
- SEM0087
- Teachers
- Luca Gambetti (Lecturer)
Ivan Petrella (Lecturer) - Degree course
- Finance
- Year
- 2nd year
- Teaching period
- First semester
- Type
- Related or integrative
- Credits/Recognition
- 6
- Course disciplinary sector (SSD)
- SECS-P/05 - econometrics
- Delivery
- Formal authority
- Language
- English
- Attendance
- Obligatory
- Type of examination
- Written
- Oggetto:
Sommario del corso
- Oggetto:
News
- Oggetto:
Course objectives
This course provides an introduction to the econometric techniques used for the analysis of economic and financial time series. The course begins with an overview of ARMA and VARMA models, and then focuses on the nonlinear time series model used for the analysis of financial time series. In particular, the course will introduce the univariate nonlinear time series models used for the analysis of financial volatility (GARCH models) and the multivariate nonlinear models for the analysis of correlations (DCC models).- Oggetto:
Results of learning outcomes
Students are expected to learn how to use the economeetric models discussed and to conduct individually analyses of economic and financial data.- Oggetto:
Program
0. User's Guide1. Intro to Times Series
1.1. Time Series in Economics and Finance
1.2. Time Series as Stochastic Processes
1.3. Time Series Properties
2. Univariate Linear Time Series (ARMA)
2.1. Linear Time Series: Models
2.2. Linear Time Series: Estimation
2.2 Linear Time Series: Forecasting
2.4. Linear Time Series: Practice
3. Multivariate Linear Time Series (VARMA)
3.1. Linear Time Series: Models
3.2. Linear Time Series: Estimation
3.3. Linear Time Series: Forecasting
3.4. Linear Time Series: Practice
4. Volatility Modeling4.1. Volatility Modeling: ARCH and GARCH4.2. Volatility Modeling: Asymmetric Effects4.3. Volatility Modeling: Prediction and Evalution4.4. Volatility Modeling: Stochastic Volatility4.5. Volatility Modeling: High Frequency Data Based Volatility Modelling4.6. Application: Risk management (VaR and ES)4.7. Application: Density Forecasting5. Multivariate Volatility Modeling5.1. Factor Models5.2. Multivariate Volatility Models5.3. Time varying correlation models- Oggetto:
Course delivery
The course consists of 48 lecture hours. The course includes both theory lectures and practical sessions. Practical sessions will be done using Matlab.- Oggetto:
Learning assessment methods
- The exam consists of two parts: 1) a short paper (50% of the grade), and 2) in-class exam (50% of the grade)Suggested readings and bibliography
- Oggetto:
- Analysis of Financial Time Series (13rd Edition). Ruey S. Tsay
Time Series Analysis. James D. Hamilton
- Oggetto:
Courses that borrow this teaching
- Financial Econometrics (FIS0252)Corso di laurea magistrale Interateneo in Fisica dei sistemi complessi
- FINANCIAL ECONOMETRICS (SEM0087)Two - Year Master Degree in Economics
- Financial Econometrics (FIS0252)
- Oggetto:
