Franke – Statistics of Financial Markets

Argomenti del programma: 1. Presentazione del corso. Variabili casuali e loro proprietà. Momenti. Distribuzioni condizionate. Momenti condizionali. Legge dei valori attesi iterati. Serie temporali e loro caratteristiche. Natura e caratteristiche dei dati finanziari. Asimmetria, curtosi e volatility clustering. Processi stocastici. Stazionarietà, Nonstazionarietà, random walk e martingale. Test di stazionarietà e del rapporto di varianze.

Argomenti del programma: 1 Introduction. Asset returns. Stylized facts: asymmetry, kurtosis and volatility clustering. Stochastic processes: stationarity, purely random processes. Random walks and martingales. Review of prediction theory. Optimal prediction. (Lectures 1-3) 2 Volatility measurement and analysis: autoregressive Conditional Heteroscedasticity (ARCH): model specification, properties, maximum likelihood estimation, prediction.

Argomenti del programma: 1 Introduction. Asset returns. Stylized facts: asymmetry, kurtosis and volatility clustering. Stochastic processes: stationarity, purely random processes. Random walks and martingales. Review of prediction theory. Optimal prediction. (Lectures 1-3) 2 Volatility measurement and analysis: autoregressive Conditional Heteroscedasticity (ARCH): model specification, properties, maximum likelihood estimation, prediction.

Argomenti del programma: Introduction to statistical methods for asset management. Review of linear time series analysis. From data to models: stylised facts, volatility modelling, risk management. Nonlinear time series analysis: GARCH models, Score Driven models, extension.