Applied Econometrics for Management and Finance

Key information

Start date
End date
Year of study
Year 1
Term 2
Module code
FHEQ Level
School of Finance and Management

Module overview

This module provides an introduction to the applications of econometric methods in finance. It examines how one can formulate the relationships suggested by financial and economic theory a in mathematical and statistical format, how to estimate these models using sample data, and how to make relevant statements based on the parameters of the estimated models. The module examines the assumptions that are necessary for the estimators to have desirable properties and the assumptions necessary to make statistical inference. In addition, the module explores what happens when these assumptions are not satisfied, and what one can do in these circumstances. The module concludes with an examination of how to select an appropriate model for applications in finance.

Objectives and learning outcomes of the module

  • Understand the principles of regression analysis in finance
  • Use the program R to estimate a regression equation for bivariate and multiple regression models
  • Test hypotheses concerning model parameters
  • Discuss the consequences of multicollinearity, the methods for identifying multicollinearity, and how to deal with it
  • Understand what is meant by heteroscedasticity and the consequences for OLS estimators and prediction based on those estimators
  • Assess the methods used to identify heteroscedasticity, including data plots and more formal tests, and the various methods to deal with heteroscedasticity
  • Understand autocorrelation, and discuss the consequences of autocorrelated disturbances for the properties of OLS estimator and prediction based on those estimators
  • Assess the consequences of disturbance terms not being normally distributed
  • Discuss the main criteria for the selection of an appropriate statistical model in financial applications


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