Currículo
Time Series MP-CA
Contextos
Groupo: Actuarial Science > 2º Ciclo > Parte Escolar > Unidades Curriculares Obrigatórias
ECTS
6.0 (para cálculo da média)
Objectivos
On completion of this course, the student should be able to: - Recognize and understand the main econometric models used in the analysis of time series. - Understand the theoretical reasoning which led to the development of the most important univariate and multivariate models. - Be familiar with the use of econometric software to carry out time series analysis. - Develop critical thinking about empirical work with time series data. - Be able to develop a forecasting study of different sets of variables and formulate statistical hypotheses of interest. Understand the limitations of the econometric methodology applied in the study
Programa
- Introduction to time series analysis. Fundamental concepts - Models for stationary time series. Autoregressive Moving Average (ARMA) models - Box-Jenkins methodology: model identification, estimation and diagnostic checking - Models for nonstationary time series. Autoregressive Integrated Moving Average (ARIMA) models and unit root testing - Forecasting using ARIMA models - Seasonality and Seasonal ARIMA (SARIMA) models - Conditional Heteroskedasticity time series models. ARCH/GARCH models - Forecasting with exponential smoothing methods - Multivariate Time Series Models
Método de Avaliação
Lectures will be theoretical and practical, starting on main empirical patterns found in time series as a basis to present statistical methods and models used to represent it. Core mathematical models for time series will be presented in a constructive way, but practical relevance of different models in terms of time series behavioural patterns and on the nature of implied forecast functions will also be strengthened. Using available software, models and modelling strategies will be applied on real time series data with emphasis in critical analysis as a function of purposes. Students will be assessed based on a final exam (60%) and a practical computational test (40%) using R
Carga Horária
Carga Horária de Contacto -
Trabalho Autónomo - 129.0
Carga Total -
Bibliografia
Principal
- Analysis of Financial Time Series: Tsay, R. S. 2005 Wiley.
- Applied Econometric Time Series: Enders, W. 2009 Wiley
- Time series analysis: univariate and multivariate methods: Wei, W. W. S. 2005 Pearson
- Time series techniques for economists: Mills, T. C. 1991 Cambridge University Press.
Secundária
- Introductory Econometrics: A Modern Approach: Wooldridge, J.M. 2011 Cengage Learning
- Time Series Analysis: Hamilton, J. 1994 Princeton University Press