Econometrics: Quantitative Methods in Finance (FINA 8397)

This course is the second part of the first year Ph.D. Econometrics sequence. The pre-requisite for the Econometrics sequence is linear algebra and an introductory econometrics/statistics course. The goal of this sequence is to provide you with a broad overview of modern econometric tools. This means understanding when to use what test, which estimator, and why. This sequence is NOT designed to teach you how to use SAS, or Eviews. A fundamental knowledge of linear and matrix algebra, calculus and statistics is a prerequisite for the Econometrics sequence. I will assume that you know what is OLS, serial correlation, heteroscedasticity, multicollinearity, etc.

Office Hours:
Tuesdays and Thursdays: 1:30-2:30 (MH 210-D) or by appointment.

Textbook:
Econometric Analysis , 5th Edition, by William H. Greene, Prentice Hall, 2003.

Other useful references:
Estimation and Inference in Econometrics, by R. Davidon and J. MacKinnon, Oxford University Press, 1993.
Time Series Analysis, by J. D. Hamilton, Princeton University Press, 1994.
Econometric Analysis of Cross Section and Panel Data, by J. Wooldridge, MIT Press, 1999.

These texts will be supplemented by articles I will be assigning throughout the semester.

Outline of the course:
Introduction
Chapter 9 – Nonlinear Regression Models
Chapter 10 – Nonspherical Disturbances – The Generalized Regression
Chapter 11 – Heteroscedasticity
Chapter 13 – Models for Panel Data
Chapter 14 – Systems of Regression Equation
Chapter 15 – Simultaneous-Equations Model
Chapters 16 to 18 – Estimation Methods: MLE and GMM
Chapters 19 and 20 – Time Series Models
Chapter 21 – Models for Discrete Choice

Exams and Grading:
Exams (75%) - Three to be scheduled (2/19, 3/2x, 4/29)
Homework (25%) - Regular assignments at the end of each chapter

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