Corso avanzato per le analisi delle serie storiche univariate e multivartiate. Con particolare riguardo alle serie finanziare ad alta frequenza per la previsione della volatilita' e la gestione del rischio.
Jón Daníelsson, 2015, Financial Risk Forecasting: The Theory and Practice of Forecasting Market Risk, with Implementation in R and Matlab, Wiley Finance.
W. Enders, 2014, Applied Econometric Time Series, 4th Edition, Wiley.
Metodi Didattici
Lezioni classiche.
Altre Informazioni
Materiale addizionale fornito dal docente.
Programma del corso
Time-Series Models, Difference Equations and Their Solutions, Lag Operators. Stochastic Difference Equation Models, ARMA Models, Stationarity, Stationarity Restrictions for an ARMA (p, q) Model , The Autocorrelation Function, The Partial Autocorrelation Function, Sample Autocorrelations of Stationary Series, Box–Jenkins Model Selection, Properties of Forecasts, Seasonality, Structural Change, Combining Forecasts. Deterministic and Stochastic Trends, Removing the Trend, Univariate volatility modeling, Modeling volatility, Moving average models, EWMA model, GARCH and conditional volatility, Maximum likelihood estimation of volatility models, Likelihood ratio tests and parameter significance, Analysis of model residuals
Other GARCH-type models, Implied volatility, Realized volatility, Multivariate volatility models, Orthogonal GARCH, CCC and DCC models, Risk measures,
Value-at-risk, Expected shortfall, Backtesting and stress testing. Intradaily data and models.