Financial Econometrics

Introduction

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

Introduction

• 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