Claim up to $500 in flight credits!
Get up to $500 in flight credits or grants toward study or internship programs abroad when you apply by January 01, 2025. See our Official Rules for full details.
Analysis of Financial Data
History, Politics & International Studies Program
Madrid, Spain
Dates: early Sep 2025 - mid Dec 2025
Analysis of Financial Data
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Finance
Instruction in: English
Course Code: 14449
Transcript Source: Partner Institution
Course Details: Level 400
Recommended Semester Credits: 3
Contact Hours: 42
Prerequisites: Statistics I, Statistics II
DESCRIPTION
Chapter 1 DYNAMIC DATA: PROPERTIES AND LINEAR MODELS
1.1 Properties of dynamic data: dependence and evolution
1.2 The autocorrelation funacion: linear dependence of financial returns
1.3 Differences between the marginal and conditional distributions: Are returns Normal?
1.4 Linear and non-linear models
1.5 ARMA models for conditional means
1.6 Efficiency tests in financial markets
Chapter 2 UNIVARIATE GARCH MODELS
2.1 Empiric properties of financial returns: Euribor, IBEX35, ¿/$, ¿/£, ¿/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