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FINANCIAL ECONOMETRICS
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FINANCIAL ECONOMETRICS
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Academic year 2023/2024
- Course ID
- SEM0087
- Teacher
- Luca Gambetti (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
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Sommario del corso
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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:
Course delivery
The course consists of 48 lecture hours. Strong interaction between teachers and students is encouraged. Part of the course will be given at the Computer Lab.- Oggetto:
Learning assessment methods
- The exam consists of writing a short paper and presenting the work in a 20-minute presentation.- 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: Prediction
2.2 Linear Time Series: Estimation
2.4. Linear Time Series: Practice
3. Multivariate Linear Time Series (VARMA)
3.1. Linear Time Series: Models
3.2. Linear Time Series: Prediction
3.3. Linear Time Series: Estimation
3.4. Linear Time Series: Practice
4. Volatility Modeling
4.1. Volatility Modeling: ARCH and GARCH
4.2. Volatility Modeling: Asymmetric Effects
4.3. Volatility Modeling: Prediction and Evalution
4.4. *Volatility Modeling: Stochastic Volatility
4.5. *Volatility Modeling: High Frequency Data Based Volatility Modelling
5. Covariance Modeling
5.1. Multivariate Volatility Models
6. Nonlinear Time Series Models
6.1 TVAR
6.2 STVAR
6.3 TVC-VAR
Suggested readings and bibliography
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- Analysis of Financial Time Series (13rd Edition). Ruey S. Tsay
Time Series Analysis. James D. Hamilton
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