Very good knowledge of Statistics (Probability and Inferential), Linear Algebra, Introductory Econometrics.
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.
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 randon 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.
S. BOFFELLI and URGA, G., 2016. FINANCIAL ECONOMETRICS USING STATA. Stata Corporation.
O. Linton, 2019. FINANCIAL ECONOMETRICS: MODELS AND METHODS.
Cambridge University Press.
J.Fan and Yao, Q. 2017. THE ELEMENTS OF FINANCIAL ECONOMETRICS. Cambridge University Press.
J.Y. Campbell, A.W. Lo, e MacKinlay A.C., 1997. THE ECONOMETRICS OF FINANCIAL MARKETS, Princeton University Press.
Gourieroux, C. and J. Jasiak (2001), FINANCIAL ECONOMETRICS, Princeton University Press
Tsay, S. R. (2005), ANALYSIS OF FINANCIAL TIME SERIES, 2nd Edition, Wiley.
Verbeek, M. (2004), A GUIDE TO MODERN ECONOMETRICS. Wiley (2012)
B. Baltagi (2008), ECONOMETRIC ANALYSIS OF PANEL DATA, Wiley.
A.C. Cameron and P.K. Trivedi (2005), MICROECONOMETRICS. METHODS AND APPLICATIONS, Cambridge University Press.
J.M. Wooldridge (2010), ECONOMETRIC ANALYSIS OF CROSS SECTION AND PANEL DATA. The M.I.T. Press.
Lectures and practical classes using the econometric packages OxMetrics8 (PcGive and G@RCH) and STATA 15.
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 25 May 2020.
Mark: 30% 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: 70% of the total mark.
Students must pass both coursework and final written exam.