Time series analysis of economic and financial data - Appunti
Appunti di Time series analysis of economic and financial data per l'esame della professoressa Petrone su:
Course Content Summary
Part I. Classical analysis of univariate time series.
Descriptive techniques. Decomposition of a time series; trends, seasonality, cycle. Moving average models. Nonparametric techniques
Exponential smoothing. Forecast and model comparison
Stochastic models. Stationary processes. Markov chains (basic notions). ARMA and ARIMA models (basic notions).
Parte II. Dynamic linear models for time series analysis.
State space models for time series analysis. Examples: non-stationary series; series with structural breaks; series with stochastic volatility; multivariate time series.
Hidden Markov models. Dynamic linear models.
Estimation, forecasting and control. Kalman filter.
Examples and applications to economic and financial time series Dynamic linear models for trend, seasonality, cycle. Dynamic regression by dlm.
Maximum likelihood estimation of unknown parameters.
Bayesian inference. Conjugate exppne analysis. Unknown covariance matrices: simple models (discount factors).
Analysis of multivariate time series (multivariate ARMA models; dynamic regression (estimation of the term structure of interest rates), models for macroeconomic variables).
Bayesian inference and forecasting via Markov chain Monte Carlo (MCMC). Recent developments.
- Esame di Time series analysis of economic and financial data docente Prof. S. Petrone
- Università: Bocconi - Unibocconi
- CdL: Corso di laurea magistrale in discipline economiche e sociali - economics and social sciences