Logo

Financial Econometrics by Roman Kozhan

Small book cover: Financial Econometrics

Financial Econometrics
by

Publisher: BookBoon
ISBN-13: 9788776814274
Number of pages: 116

Description:
The aim of this textbook is to provide a step-by-step guide to financial econometrics using EViews 6.0 statistical package. It contains brief overviews of econometric concepts, models and data analysis techniques followed by empirical examples of how they can be implemented in EViews. This book is written as a compendium for undergraduate and graduate students in economics and finance.

Home page url

Download or read it online for free here:
Download link
(4MB, PDF)

Similar books

Book cover: EconometricsEconometrics
by - Universitat Autonoma de Barcelona
Textbook for graduate econometrics, it teaches ordinary least squares, maximum likelihood estimation, restrictions and hypothesis test, stochastic regressors, exogeneity and simultaneity, numeric optimization methods, method of moments, etc.
(21625 views)
Book cover: Introduction to Python for Econometrics, Statistics and Numerical AnalysisIntroduction to Python for Econometrics, Statistics and Numerical Analysis
by
Python is a widely used general purpose programming language, which happens to be well suited to Econometrics and other more general purpose data analysis tasks. These notes provide an introduction to Python for a beginning programmer.
(24567 views)
Book cover: Structural Analysis of Discrete Data with Econometric ApplicationsStructural Analysis of Discrete Data with Econometric Applications
by - The MIT Press
The book provides a methodological foundation for the analysis of economic problems involving discrete data, and charts the current frontiers of this subject. It is also useful for the researchers involved in the structural analysis of discrete data.
(15729 views)
Book cover: Spatial EconometricsSpatial Econometrics
by - University of Toledo
This text provides an introduction to spatial econometrics as well as a set of MATLAB functions that implement a host of spatial econometric estimation methods. The intended audience is faculty and students involved in modeling spatial data sets.
(12321 views)