analysis of Financial Time Series

Intended audience: Intermediate and advanced users of S-PLUS who had limited or no experience with S+FinMetrics

Course’s prerequisites: Basic statistics and time series analysis (e.g.
S-PLUS Essentials course)

Course’s aims: The participants should learn how to use S-PLUS and the S+FinMetrics module for time series modelling, and should be able to write their own simple functions in the S language.

Day 1

Introduction to Time Series Analysis in S-PLUS

• Review of S language and basic programming
• Manipulating calendar dates and sequences
• Importing and exporting data
• Creating lags of time series

Time Series Regression Modelling

• Dynamic Regression                      
• Distributed Lags and Polynomial Distributed Lags 
• Recursive OLS and rolling regression models

GARCH Models

• Estimation of univariate GARCH models
• Estimation of multivariate GARCH models
• Forecasting from GARCH models
• Model diagnostics

Day 2

Estimation of Factor Models for Asset Returns

• Maximum likelihood factor analysis
• Principal components estimation
• Asymptotic principal components          
• Determining the number of factors

Dynamic Latent Variable and State-space Models

• State-space models and the Kalman filter
• GMM estimation of variance components models
• Markov-switching models in state-space
• Non-linear SUR models

 Applications in Finance

• Term structure of interest rates
• Multivariate market risk models and backtesting
• Credit risk models and estimation of economic capital
• Multivariate Vasicek models in state-space
• Multi-state Markov switching models for migration transitions probabilities