Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- List of boxes
- Preface
- Acknowledgements
- 1 Introduction
- 2 Mathematical building blocks for real estate analysis
- 3 Statistical tools for real estate analysis
- 4 An overview of regression analysis
- 5 Further issues in regression analysis
- 6 Diagnostic testing
- 7 Applications of regression analysis
- 8 Time series models
- 9 Forecast evaluation
- 10 Multi-equation structural models
- 11 Vector autoregressive models
- 12 Cointegration in real estate markets
- 13 Real estate forecasting in practice
- 14 The way forward for real estate modelling and forecasting
- References
- Index
Preface
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- List of figures
- List of tables
- List of boxes
- Preface
- Acknowledgements
- 1 Introduction
- 2 Mathematical building blocks for real estate analysis
- 3 Statistical tools for real estate analysis
- 4 An overview of regression analysis
- 5 Further issues in regression analysis
- 6 Diagnostic testing
- 7 Applications of regression analysis
- 8 Time series models
- 9 Forecast evaluation
- 10 Multi-equation structural models
- 11 Vector autoregressive models
- 12 Cointegration in real estate markets
- 13 Real estate forecasting in practice
- 14 The way forward for real estate modelling and forecasting
- References
- Index
Summary
Motivations for the book
This book is designed to address the quantitative needs of students and practitioners of real estate analysis. Real estate is a truly multidisciplinary field. It combines specialities from urban economics, geography, land management, town planning, construction, valuations, surveying, finance, business economics and other areas in order to perform a range of tasks, including portfolio strategy, valuations, risk assessment and development feasibility. In performing these tasks, objective analysis, systematic relationships and greater sophistication are essential. The present book targets this fundamental need in the market.
The demand for modelling and forecasting work is expanding rapidly, with a direct requirement for insightful and well-informed processes to be in place. The growing number and larger size of forecasting teams within firms compared with just a few years ago, and the existence of forecasting related research sponsored by industry organisations and of professional courses in this area, demonstrate the significance given by the industry to quantitative modelling and forecasting.
At the same time, undergraduate and postgraduate courses in real estate have increasingly introduced more quantitative analysis into their portfolios of modules. Such students rarely come from a statistics background, which is acknowledged in this book. With increasing demands from employers for their applicants to have received statistical training, academic institutions and other educational establishments need to introduce more formal quantitative analysis in their degrees. Given the greater availability of data, firms require that their intake will be able to analyse the data and to support valuations, fund management and other activities.
- Type
- Chapter
- Information
- Real Estate Modelling and Forecasting , pp. xv - xviiiPublisher: Cambridge University PressPrint publication year: 2010