Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- List of boxes
- List of screenshots
- Preface to the third edition
- Acknowledgements
- 1 Introduction
- 2 Mathematical and statistical foundations
- 3 A brief overview of the classical linear regression model
- 4 Further development and analysis of the classical linear regression model
- 5 Classical linear regression model assumptions and diagnostic tests
- 6 Univariate time series modelling and forecasting
- 7 Multivariate models
- 8 Modelling long-run relationships in finance
- 9 Modelling volatility and correlation
- 10 Switching models
- 11 Panel data
- 12 Limited dependent variable models
- 13 Simulation methods
- 14 Conducting empirical research or doing a project or dissertation in finance
- Appendix 1 Sources of data used in this book
- Appendix 2 Tables of statistical distributions
- Glossary
- References
- Index
1 - Introduction
- Frontmatter
- Contents
- List of figures
- List of tables
- List of boxes
- List of screenshots
- Preface to the third edition
- Acknowledgements
- 1 Introduction
- 2 Mathematical and statistical foundations
- 3 A brief overview of the classical linear regression model
- 4 Further development and analysis of the classical linear regression model
- 5 Classical linear regression model assumptions and diagnostic tests
- 6 Univariate time series modelling and forecasting
- 7 Multivariate models
- 8 Modelling long-run relationships in finance
- 9 Modelling volatility and correlation
- 10 Switching models
- 11 Panel data
- 12 Limited dependent variable models
- 13 Simulation methods
- 14 Conducting empirical research or doing a project or dissertation in finance
- Appendix 1 Sources of data used in this book
- Appendix 2 Tables of statistical distributions
- Glossary
- References
- Index
Summary
Learning econometrics is in many ways like learning a new language. To begin with, nothing makes sense and it is as if it is impossible to see through the fog created by all the unfamiliar terminology. While the way of writing the models – the notation – may make the situation appear more complex, in fact it is supposed to achieve the exact opposite. The ideas themselves aremostly not so complicated, it is just a matter of learning enough of the language that everything fits into place. So if you have never studied the subject before, then persevere through this preliminary chapter and you will hopefully be on your way to being fully fluent in econometrics!
Learning outcomes
In this chapter, you will learn how to
• Compare nominal and real series and convert one to the other
• Distinguish between different types of data
• Describe the key steps involved in building an econometric model
• Calculate asset price returns
• Deflate series to allow for inflation
• Construct a workfile, import data and accomplish simple tasks in EViews
The chapter sets the scene for the book by discussing in broad terms the questions of what econometrics is, and what the ‘stylised facts’ are describing financial data that researchers in this area typically try to capture in their models. Some discussion is presented on the kinds of data we encounter in finance and how to work with them.
- Type
- Chapter
- Information
- Introductory Econometrics for Finance , pp. 1 - 27Publisher: Cambridge University PressPrint publication year: 2014