Curso: "Time Series for Macroeconomics and Finance"

Curso: "Management Science Optimization Modeling with SAS/OR"
12 July 2011
Seminario:"Ecuaciones de estimación generalizadas basadas en residuos generalizados"
30 September 2011

El curso “Time Series for Macroeconomics and Finance” se impartirá del 18 al 22 de julio en la Universidad Politécnica de Cataluña (UPC) en Barcelona en el marco de la Summer School 2011 del Master Interuniversitario en Estadística e Investigación de la UPC y de la Universidad de Barcelona.

Datos importantes del curso:

  • Título: Time Series for Macroeconomics and Finance
  • Impartido por: Andrew Harvey
  • Idioma: Inglés
  • Duración: 10 horas
  • Fechas y horarios: 18 al 22 de julio de 2011, de 10 a 12.30h (el día 18 de 10 a 13h)
  • Fechas de matrícula: 20 de junio al 10 de julio de 2011
  • Precios: Ver la página web de la Summer School
  • Página web del curso
  • Objetivo del curso: The course will show how economic and financial time series can be modelled and analysed. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Statistical modelling will be demonstrated using the STAMP 8 package ( and participants will be given the opportunity to use the package in class.
    Participants are expected to have taken an introductory course in econometrics or time series analysis. The references to Time Series Models (TSM) in the course outline give an indication of the material covered. The notes are shown as [TS*] and [FTS*]. Although these notes correspond to the slides, not all the material will be covered in detail during the lectures. Students should be familiar with most of the TS material. The FTS notes is more advanced (F stands for “Further”). Assessment will be made by exercises which will be done as homework.
  • Contenido del curso:
  1. Introduction. [TS1] Stationary time series. ARMA models. Prediction. Unobserved components and signal extraction. [TS2] TSM, chs 1,2,3. ARIMA models. Structural (unobserved components) time series models. Testing for nonstationarity. TSM, ch 5. [TS3] Explanatory variables and intervention analysis [TS4].
  2. State space models and the Kalman filter. Signal extraction. Missing observations and other data irregularities. TSM, ch 4. [FTS1].
  3. Spectral analysis. Spectra of ARMA processes; stochastic cycles; linear filters; estimation of spectrum. TSM, ch6, sections 1 to 7. [FTS2].
  4. Trends and cycles. Analysis of the effects of moving average and differencing operations. Band-pass and Hodrick-Prescott filters. Seasonality. TSM, ch6, sections 5 and 6. [FTS3].
  5. Multivariate time series models. Dynamic econometric models; common trends and co-integration; control groups. TSM, ch 7. [FTS5] Financial econometrics. Nonlinear models; distributions of returns, stochastic volatility and GARCH; nonlinear state space models. TSM, ch8,Taylor, chs 8-11, 15. [FTS4].