TIME SERIES AND FINANCIAL TIME SERIES

Syllabus:

  • Introduction to time series 
  • Graphical analysis
  • The components: trend, seasonality and error term.
  • How to eliminate the trend the seasonality
  • The concepts of stationarity and inveribility.
  • The autocorrelation function
  • ARMA models: The AR(p), the MA(q), the ARMA(p,q), the ARIMA(p,d,q): methodology and properties
  • Estimation of parameters: a likelihood approach
  • How to chose an ARMA model: a likelihood approach.
  • Read data analysis using R
  • Stylized facts of financial data
  • ARCH models, methodological aspects and properties
  • GARCH models, mehodological aspects and properties
  • Generalization of GARCH models.
  • During classes we will use the software R

Teaching material will be provided

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