Financial econometrics has become one of the most active areas of research in econometrics. The Journal of Financial Econometrics is dedicated to this fast-growing field. The Journal addresses substantive statistical issues raised by the tremendous growth of the financial industry over the last decades. The goal of the Journal is to reflect and advance the relationship between econometrics and finance, both at the methodological and at the empirical levels.
ADVANCED TEXTS IN ECONOMETRICS General Editors Manuel Arellano Guido Imbens Grayham E. Mizon Adrian Pagan Mark Watson Advisory Editor C. W. J. Granger.Other Advanced Texts in conometrics ARCH: Selected Readings Edited by Robert F. Engle Asymptotic Theory for Integrated Processes By H. Peter Boswijk Bayesian Inference in Dynamic Econometric Models By Luc Bauwens, Michel Lubrano, and Jean-Fran¸ois Richard c Co-tegration, Error Correction, and the Econometric Analysis of Non-Stationary Data By Anindya Banerjee, Juan J. ...
Chapter 1 - Introduction. This chapter sets the scene for the book by discussing in broad terms the questions of what is econometrics, and what are the ‘stylised facts’ describing financial data that researchers in this area typically try to capture in their models. It also collects together a number of preliminary issues relating to the construction of econometric models in finance.
Lecture "Advanced Econometrics (Part II) - Chapter 2: Hypothesis testing" presentation of content: Maximum likelihood estimators, wald test, likelihood ratio test, lagrange multiplier test, application of tests procedures to linear models, hausman specification test, power and size of tests.
Lecture "Advanced Econometrics (Part II) - Chapter 8: Heteroskedasticity" presentation of content: Proterties of ols in rpesence of heteroskedasticity, teesting for heteroskedasticity, treatment for heteroskedasticity.
Lecture "Advanced Econometrics (Part II) - Chapter 10: Models for panel data" presentation of content: General framework for panel data, pooled regression, fixed effects, random effects model, choosing between fixed and random effects models, finding big.
Lecture "Advanced Econometrics (Part II) - Chapter 11: Seemingly unrelated regressions" presentation of content: Model, generalized least squares estimation of sur model, kronecker product, two case when sur provides no eficiency gain over, hypothesis testing.
Lecture "Advanced Econometrics (Part II) - Chapter 12: Simultaneous equations models" presentation of content: Model, rank and order conditions for identification, estimation of a simultaneous equation system.
Lecture "Advanced Econometrics (Part II) - Chapter 13: Generalized method of moments (GMM)" presentation of content: Orthogonality condition, method of moments, generalized method of moments, GMM and other estimators in the linear models, the advantages of GMM estimator, GMM estimation procedure.
The objectives of this chapter are to switching models. In this chapter, you will learn how to: Use intercept and slope dummy variables to allow for seasonal behaviour in time series, motivate the use of regime switching models in financial econometrics, specify and explain the logic behind Markov switching models,...
Lecture "Advanced Econometrics (Part II) - Chapter 6: Dummy varialable" presentation of content: Intercept dummy, intercept dummies with interactions, seasonal efects, pooled data, test for structure break, differences in differences.
Lecture "Applied econometrics course - Chapter 1: Simple regression model" has content: What is simple regression model, how to estimate simple regression model, R – Square, assumption, variance and standard error of parameters,... and other contents.
Lecture "Applied econometrics course - Chapter 2: Multiple regression model" has content: Why we need multiple regression model, estimation, R – Square, assumption, variance and standard error of parameters, the issues of multiple regression model, Illustration by Computer.