DETAILED DESCRIPTION OF THE TOPICS TO BE COVERED IN THE COURSE
1 Statistical recalls
- Univariate and multivariate random variables.
2 Finacial returns, volatility and their carachteristics
3 Stochastic processes for mean structure
- AR, MA and ARIMA processes
Conditional and not conditional moments
Parameters estimation and analysis of residuals
Forecasting
4 Stochastic processes for volatily structure
- ARCH, GARCH and EGARCH processes
Conditional and not conditional moments
Parameters estimation and analysis of residuals
Volatility forecasting
- Stochastic Volatility (SV) process
Moments
Parameters estimation
5 Generalized Linear Models (GLM) and Logistic Regression (LR)
Introduction
Loglikelihood function and parameters estimation
Analysis of residuals
Hosmer and Lemenshow Test for LR.
6 Classification models
Naive Bayes
Tree-Based methods for classification
Support Vector Machines