The course covers the main statistical tools to analyse economic and financial data. Topics include multiple linear regression, panel data, models suitable to interpret and forecast the temporal dynamic of phenomena observed in time series form, such as macroeconomics indicators, prices and returns of financial assets and their volatility. The focus is mainly applied, with the aim to provide the relevant statistical theory and experience. To make the results easily understandable and gain expertise in analyzing data, during the classes real examples using R will be extensively used.
Curriculum
teacher profile teaching materials
Econometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Programme
Notes on basic statistical concepts finalized to the analysis of financial data (random variables, sample distributions, hypothesis verification), and on methods for exploratory data analysis. Multiple regression: estimation of coefficients, ANOVA, selection of models, assumption verification and their removals. Models for panel data. Distributed lag models. Stochastic processes and models for time series (MA, AR, ARMA and ARIMA): definition, estimation and forecast. Notes on multiple time series models (VAR)Core Documentation
Intoductory Econometrics for Finance, C. Brooks, Cambridge University PressEconometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Type of delivery of the course
Theoretical lessons and applications to real data in the class with the Professor.Type of evaluation
Oral interview on program topics teacher profile teaching materials
Econometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Mutuazione: 21201732 METODI STATISTICI PER LA FINANZA in Finanza e impresa LM-16 N0 NACCARATO ALESSIA
Programme
Notes on basic statistical concepts finalized to the analysis of financial data (random variables, sample distributions, hypothesis verification), and on methods for exploratory data analysis. Multiple regression: estimation of coefficients, ANOVA, selection of models, assumption verification and their removals. Models for panel data. Distributed lag models. Stochastic processes and models for time series (MA, AR, ARMA and ARIMA): definition, estimation and forecast. Notes on multiple time series models (VAR)Core Documentation
Intoductory Econometrics for Finance, C. Brooks, Cambridge University PressEconometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Type of delivery of the course
Theoretical lessons and applications to real data in the class with the Professor.Type of evaluation
Oral interview on program topics teacher profile teaching materials
Econometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Mutuazione: 21201732 METODI STATISTICI PER LA FINANZA in Finanza e impresa LM-16 N0 NACCARATO ALESSIA
Programme
Notes on basic statistical concepts finalized to the analysis of financial data (random variables, sample distributions, hypothesis verification), and on methods for exploratory data analysis. Multiple regression: estimation of coefficients, ANOVA, selection of models, assumption verification and their removals. Models for panel data. Distributed lag models. Stochastic processes and models for time series (MA, AR, ARMA and ARIMA): definition, estimation and forecast. Notes on multiple time series models (VAR)Core Documentation
Intoductory Econometrics for Finance, C. Brooks, Cambridge University PressEconometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Type of delivery of the course
Theoretical lessons and applications to real data in the class with the Professor.Type of evaluation
Oral interview on program topics teacher profile teaching materials
Econometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Mutuazione: 21201732 METODI STATISTICI PER LA FINANZA in Finanza e impresa LM-16 N0 NACCARATO ALESSIA
Programme
Notes on basic statistical concepts finalized to the analysis of financial data (random variables, sample distributions, hypothesis verification), and on methods for exploratory data analysis. Multiple regression: estimation of coefficients, ANOVA, selection of models, assumption verification and their removals. Models for panel data. Distributed lag models. Stochastic processes and models for time series (MA, AR, ARMA and ARIMA): definition, estimation and forecast. Notes on multiple time series models (VAR)Core Documentation
Intoductory Econometrics for Finance, C. Brooks, Cambridge University PressEconometric Analysis of Panel Data, B. H. Baltagi, Wiley
Time Series Analysis, J. D. Hamilton, Princeton University Press
New Introduction to Multiple Time Series Analysis, H. Lütkepohl, Springer
Type of delivery of the course
Theoretical lessons and applications to real data in the class with the Professor.Type of evaluation
Oral interview on program topics