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Analysis of Financial Data
Communication, Journalism & Media Studies Program
Madrid, Spain
Dates: 8/29/26 - 12/23/26
Analysis of Financial Data
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Finance
Instruction in: English
Course Code: 14449
Transcript Source: Partner Institution
Course Details: Level 400
Recommended Semester Credits: 3
Contact Hours: 42
Prerequisites: Statistics I, Statistics II
DESCRIPTION
Chapter 1 DYNAMIC DATA: PROPERTIES AND LINEAR MODELS
1.1 Properties of dynamic data: dependence and evolution
1.2 The autocorrelation funacion: linear dependence of financial returns
1.3 Differences between the marginal and conditional distributions: Are returns Normal?
1.4 Linear and non-linear models
1.5 ARMA models for conditional means
1.6 Efficiency tests in financial markets
Chapter 2 UNIVARIATE GARCH MODELS
2.1 Empiric properties of financial returns: Euribor, IBEX35, ¿/$, ¿/£, ¿/Yuan. The role of observation frequency
2.2 ARCH(1) model: properties
2.3 GARCH(1,1) model: properties
2.4 IGARCH model: Riskmetrics
2.5 Asymmetric response of volatility: EGARCH(1,1) model
2.6 GARCH-M model
2.7 Estimation and forecasting of volatility. Constructing forecast intervals for financial returns
2.8 Computing the value at risk of stocks
Chapter 3 MULTIVARIATE GARCH MODELS
3.1 Properties of multivariate financial data
3.2 Multivariate GARCH models: problems
3.3 BEKK model
3.4 CCC model
3.5 Correlations among financial stocks: portfolio management
3.6 Temporal structure of interestrates
1.1 Properties of dynamic data: dependence and evolution
1.2 The autocorrelation funacion: linear dependence of financial returns
1.3 Differences between the marginal and conditional distributions: Are returns Normal?
1.4 Linear and non-linear models
1.5 ARMA models for conditional means
1.6 Efficiency tests in financial markets
Chapter 2 UNIVARIATE GARCH MODELS
2.1 Empiric properties of financial returns: Euribor, IBEX35, ¿/$, ¿/£, ¿/Yuan. The role of observation frequency
2.2 ARCH(1) model: properties
2.3 GARCH(1,1) model: properties
2.4 IGARCH model: Riskmetrics
2.5 Asymmetric response of volatility: EGARCH(1,1) model
2.6 GARCH-M model
2.7 Estimation and forecasting of volatility. Constructing forecast intervals for financial returns
2.8 Computing the value at risk of stocks
Chapter 3 MULTIVARIATE GARCH MODELS
3.1 Properties of multivariate financial data
3.2 Multivariate GARCH models: problems
3.3 BEKK model
3.4 CCC model
3.5 Correlations among financial stocks: portfolio management
3.6 Temporal structure of interestrates