Excerpt from course description

Financial Econometrics


Financial Econometrics can be understood as the application of statistical techniques using a digital tool (the software R) to answer questions in Finance. Therefore, Financial Econometrics can be used to test theories in Finance. As such, it is supports financial decision-making.

Course content


  • What is Financial Econometrics about?
  • Types of data
  • Returns in financial modelling
  • Steps involved in formulating an econometric model

Mathematical and statistical foundations

  • Sum and product notation
  • Functions
  • Differential calculus
  • Matrices
  • Probability and probability distributions
  • Descriptive statistics

The classical linear regression model (CLRM)

  • Regression versus correlation
  • Simple regression
  • Some further terminology
  • The assumptions underlying the CLRM
  • Properties of the OLS etsimator
  • Precision and standard errors
  • Statistical inference
  • The exact significance level

Further development and analysis of the CLRM

  • From simple to multiple linear regression
  • Calculating the parameters in the generalized case
  • The t-statistic
  • Testing multiple hypothesis: the F-test
  • Goodness of fit statistics

CLRM assumptions and the diagnostic tests

  • Statistical distributions for diagnostic tests
  • Assumption 1: Errors have zero mean
  • Assumption 2: Errors have constant variance
  • Assumption 3: Errors are linearly independent from each over time 
  • Assumption 4: Errors are linearly independent from x-variables at the same point in time
  • Assumption 5: Errors are normally distributed
  • Multicollinearity
  • Adopting the wrong functional form
  • Parameter stability tests


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