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  3. Vrije Universiteit Amsterdam (VU)
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  5. Empirical Finance

Summary

Summary Classical Linear Regression Model

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  • Course
  • Empirical Finance
  • Institution
  • Vrije Universiteit Amsterdam (VU)
  • Book
  • Introductory Econometrics for Finance

Summary of the 1st lecture, week 1. It includes explanations of the Dummy variables and interactions, visualisation of interaction effects, R-squared, Adjusted R-Square, Multicollinearity, interpretation of the entire Stata table, interpretation of the sign of the coefficients, p-values, t-values, ...

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Document information

  • Unknown
  • November 23, 2017
  • 14
  • 2017/2018
  • Summary

Subjects

  • clrm
  • empirical finance
  • vu university
  • vrije university
  • andre lucas
  • week 1
  • lecture 1
  • dummy
  • dummy interactions
  • r squared
  • adjusted r squared
  • multicollinearity
  • classical linear regression model
  • a opschoor

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Written for

  • Vrije Universiteit Amsterdam (VU)
  • Msc Finance
  • Empirical Finance
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Content preview

, CLRM – Classical Linear Regression Model

Dummy variables: Distinguish between groups, the average and the slope between groups, that´s all
about Dummy variables.
In empirical finance we have two important concepts
1. Estimations
- We have a group and we look at their salaries. We take the average of the salaries.
- Taking the average is estimation
2. Inference
- We split the group in two. We have two different averages.
- Afterwards we ask ourselves: Are they different? Are they surprisingly different?
H0 = everybody earns the same salary.
H1 = otherwise
- Inference is about interpreting the results.
- When we check at the differences we look coefficients.
Exam Questions: How do I interpret these results?
Notation Issues: What is random and non-random in the linear regression model?




- B/M – book to market  valuation multiple  high book to market  high value
- Gov – governance  better governance is better for valuation  so, lower book to
market
- Lev – leverage  leverage affects valuation
- The slope of the line is β2
- The data is only dots. You have the data and then you infer the slope. That is the
estimation part of β2.
- High governance is a very good variable. Very good governance means high market value
 therefore low book to market. Low book to market means the stock is overvalued.

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