Lecture
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05 Mar 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
Lezione in aula e trasmessa su Teams. Introduzione al corso. Sunspots. Serie temporali fisiologiche. Previsione di serie temporali. Modelli deterministici e stocastici. Scatterplots.
06 Mar 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
Lezione in aula e trasmessa su Teams. Il problema dell'induzione statistica. Eventi estremi. Medie mobili. Medie mobili esponenziali. Previsione. Trend, Livello, Stagionalità. Modello di Holt Winters.
12 Mar 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
lezione in aula e trasmessa su Teams: strong and weak stationarity, autocorrelation and dependencies, approaches to time series analysis. White noises and random walks. Lag operator Linear models. Wold decomposition theorem. Autoregressive, Moving averages, ARMA processes, partial autocorrelation, invertibility.
13 Mar 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
lezione in aula e trasmessa su Teams: Autoregressive integrated and fractionally integrated models ARIMA and ARFIMA. Seasonal ARIMA and ARFIMA processes. Examples of fit. Deterministic dynamical systems and observables. Measure preserving transformations and strong stationarity. Ergodicity, weak and strong mixing. Delay map. Takens theorem. Choose of delay embedding dimension. Embedology and reconstruction of attractors from time series.
04 Apr 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
lezione in aula e trasmessa su Teams: Maximum likelihood estimation. Application to ARMA models. Ordinary Least Squares. Generalized generalized method of moments. Identification. Model averages and shrinking. Box-Jenkins approach
05 Apr 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
lezione in aula e trasmessa su Teams: model selection in time series analysis. Ljung-Box test. Heteroskedasticity. Tests of normality. Prediction and out-of-sample performance. Bias, MAFE, MSFE. Wiener-Kolmogorov prediction formula. Introduction to Vector Auto Regressive models. Examples.
09 Apr 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
lezione in aula e trasmessa su Teams: introduction to VAR models. Identifiabilty, stationarity, estimation and inference. Spurious regressions. Cointegration. Cointegration in economics and in finance (pairs trading). Cointegrated VAR model
10 Apr 2024 (2h 00m)
Stefano Marmi - Course (teaching activity) - Face to face
lezione in aula e trasmessa su Teams: VAR models and ADL models. Structural models. Boostrap. Granger causality. Independent Component Analysis
22 Apr 2024 (3h 00m)
Giulia Livieri - Course (teaching activity) - Face to face
Introduction to Machine Learning for finance and first definitions of Neural Networks.
23 Apr 2024 (3h 00m)
Giulia Livieri - Course (teaching activity) - Face to face
Recurrent Neural Networks.
24 Apr 2024 (3h 00m)
Giulia Livieri - Course (teaching activity) - Face to face
Kalman filter and introduction to Score Driven Models.
25 Apr 2024 (3h 00m)
Giulia Livieri - Course (teaching activity) - Face to face
Score Driven Models, continuation.
26 Apr 2024 (3h 00m)
Giulia Livieri - Course (teaching activity) - Face to face
Convolutional Neural Networks.
13 May 2024 (3h 00m)
Piero Mazzarisi - Course (teaching activity) - Face to face
Advanced models of neural networks 1
15 May 2024 (3h 00m)
Piero Mazzarisi - Course (teaching activity) - Face to face
Advanced models of neural networks 2
17 May 2024 (3h 00m)
Piero Mazzarisi - Course (teaching activity) - Face to face
The problem of synthetic data generation and machine learning solutions with GANs
20 May 2024 (3h 00m)
Piero Mazzarisi - Course (teaching activity) - Face to face
Introduction to Reinforcement learning
22 May 2024 (3h 00m)
Piero Mazzarisi - Course (teaching activity) - Face to face
Advances in reinforcement learning and application to portfolio management and trading
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