Quantitative Methods in Finance using R
Chapter 2. Summary statistics and elementary data presentation
Chapter 3. Basic hypothesis tests
Chapter 4. An introduction to regression
Chapter 5. The extra sum of squares principle and regression modelling assumptions
Chapter 6. Violations of regression modelling assumptions – autocorrelation
Chapter 7. Violations of regression modelling assumptions – multicollinearity
Chapter 8. Dummy variable regression models
Chapter 9. Qualitative response regression models
Chapter 10. Linear mixed and generalised linear mixed models
Chapter 11. Non-financial time series models
Chapter 12. Modelling financial price data
Chapter 13. ARCH/GARCH models
“The book will form a solid foundation to support the transition of students into the world of work or further research.”
Professor Jane M Binner, Chair of Finance, Department of Finance, University of Birmingham, UK
“In over 20 years of teaching quantitative methods, I have rarely come across a book such as this which meets/exceeds all the expectations of its intended audience so well”
Tuan Yu, Lecturer, Kent Business School, Canterbury, UK
“This is a fantastic book for anyone wanting to understand, learn and apply quantitative methods in finance using R”
Professor Raphael Markellos, Professor of Finance, Norwich Business School, UK
Quantitative Methods in Finance Using R draws on the extensive teaching and research expertise of John Fry and Matt Burke, covering a wide range of quantitative methods in Finance that utilise the freely downloadable R software. With software playing an increasingly important role in finance, this book is a must-have introduction for finance students who want to explore how they can undertake their own quantitative analyses in dissertation and project work.
Assuming no prior knowledge, and taking a holistic approach, this brand new title guides you from first principles and help to build your confidence in tackling large data sets in R.
Complete with examples and exercises with worked solutions, Fry and Burke demonstrate how to use the R freeware for regression and linear modelling, with attention given to presentation and the importance of good writing and presentation skills in project work and data analysis more generally.
Through this book, you will develop your understanding of:
• Descriptive statistics
• Inferential statistics
• Regression
• Analysis of variance
• Probability regression models
• Mixed models
• Financial and non-financial time series
John Fry is a senior lecturer in Applied Mathematics at the University of Hull. Fry has a PhD in Mathematical Finance from the University of Sheffield. His main research interests span mathematical finance, econophysics, statistics and operations research.
Matt Burke is a senior lecturer in Finance at Sheffield Hallam University. He holds a PhD in Finance from the University of East Anglia. Burke’s main research interests lie in asset pricing and climate finance.