ADVANCED ECONOMETRICS | Università degli studi di Bergamo

ADVANCED ECONOMETRICS

Attività formativa monodisciplinare
Codice dell'attività formativa: 
110015-ENG

Scheda dell'insegnamento

Per studenti immatricolati al 1° anno a.a.: 
2020/2021
Insegnamento (nome in italiano): 
ADVANCED ECONOMETRICS
Insegnamento (nome in inglese): 
Advanced Econometrics
Tipo di attività formativa: 
Attività formativa Caratterizzante
Tipo di insegnamento: 
Obbligatoria
Settore disciplinare: 
ECONOMETRIA (SECS-P/05)
Anno di corso: 
1
Anno accademico di offerta: 
2020/2021
Crediti: 
6
Responsabile della didattica: 
Altri docenti: 
Alain Roger PIROTTE
Mutuazioni
  • Corso di studi in INTERNATIONAL MANAGEMENT, ENTREPRENEURSHIP AND FINANCE - Percorso formativo in MANAGEMENT AND FINANCE FOR INTERNATIONAL MARKETS

Altre informazioni sull'insegnamento

Modalità di erogazione: 
Didattica Convenzionale
Lingua: 
Inglese
Ciclo: 
Secondo Semestre
Obbligo di frequenza: 
No
Ore di attività frontale: 
48
Ore di studio individuale: 
102
Ambito: 
Economico
Prerequisites

Very good knowledge of Statistics (Probability and Inferential), Linear Algebra, Introductory Econometrics.

Educational goals

To provide students with wide knowledge of econometric techniques useful to modelling micro (MICROECONOMETRICS) and financial (FINANCIAL ECONOMETRICS) variables. Students will be very well equipped to undertake research careers at national (for instance Bank of Italy) and international (for instance European Central Bank, Bank of England, International Monetary Fund, ..) institutions, financial industry and academia.

Course content

FINANCIAL ECONOMETRICS - Introduction to financial econometrics. Standard deviation, asymmetry, kurtosis, calendar effects and plausible distributions of log returns. - Modelling of volatility of prices and returns: ARCH, GARCH, (G)ARCH-M, IGARCH, EGARCH, AGARCH, ZARCH and GJRGARCH models. - Multivariate GARCH models and dynamic conditional correlations models- Empirical applications using G@RCH: portfolios choice and VaR analysis. - Long memory models and applications to credit risk models. - Evaluation of the impact of macro news and rating agencies on financial assets. Measuring contagion and systemic risk. Dynamic factor models in financial assets.

MICROECONOMETRICS - Introduction to the econometrics of panel data. Stationary Panels (fixed vs random effects, pooled-OLS, within-groups, between-groups, GLS-BN, Anderson & Hsiao, Arellano & Bond, GMM estimators). Non Stationary Panels: unit root tests and cointegration with panels, cross dependence, issue related to aggregation (micro vs macro cointegration analysis). Factor models: static and dynamic factor models with application in economics and finance. Discrete choice models: logit, probit, tobit, binary and multinomial models.

Teaching methods

Lectures and practical classes using the econometric packages OxMetrics8 (PcGive and G@RCH) and STATA 16.

Assessment and Evaluation

The assessment consists of
a) A home-take COURSEWORK to be assigned by the lecturer, to be executed using either OxMetrics (PcGive and G@RCH) or STATA, and to be submitted by the 28 May 2021.
Mark: 40% of the total mark.

b) two-hour FINAL WRITTEN EXAM (short-answer, proofs, and numerical questions) based on the material in the syllabus and in the coursework. Mark: 60% of the total mark.
Students must pass both coursework and final written exam.

Further information

If lectures and classes will be delivered blended or remotely in full, the syllabus and the assessment process will be modified accordingly.