This innovative textbook develops students' understanding of empirical research in corporate finance, enabling them to apply econometric methods to their own research. Features include lab work and mini case studies. Code is provided in Stata, Python, and R, so students can develop their programming skills.
This innovative textbook develops students' understanding of empirical research in corporate finance, enabling them to apply econometric methods to their own research. Features include lab work and mini case studies. Code is provided in Stata, Python, and R, so students can develop their programming skills.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Taylan Mavruk is a Professor of Finance at the University of Gothenburg. His research focuses on corporate finance, investor behaviour, home/local bias, insider trading, CSR/ESG, mutual fund performance, and economics of patents. His research has been published in leading finance journals. Taylan has been teaching in courses related to corporate finance and econometrics since 2006.
Inhaltsangabe
1. Introduction 2. The nature of sampling, non-parametric analysis, and hypothesis testing 3. Basic data analysis in Stata 4. Survey data analysis 5. Classical linear regression model 6. Endogeneity bias 7. Time series analysis 8. Event studies 9. Panel data analysis 10. Selection of models with limited dependent variables 11. Writing empirical papers in corporate finance 12. Future directions: Machine learning methods.
1. Introduction 2. The nature of sampling, non-parametric analysis, and hypothesis testing 3. Basic data analysis in Stata 4. Survey data analysis 5. Classical linear regression model 6. Endogeneity bias 7. Time series analysis 8. Event studies 9. Panel data analysis 10. Selection of models with limited dependent variables 11. Writing empirical papers in corporate finance 12. Future directions: Machine learning methods.
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