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Real Estate Modelling and Forecasting

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Real Estate Modelling and Forecasting

As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.

About the Author

Chris Brooks is Professor of Finance at the ICMA Centre, University of Reading, where he also obtained his PhD. He has published over sixty articles in leading academic and practitioner journals including the Journal of Business, the Journal of Banking and Finance, the Journal of Empirical Finance, the Review of Economics and Statistics and the Economic Journal. He is associate editor of a number of journals including the International Journal of Forecasting. He has also acted as consultant for various banks and professional bodies in the fields of finance, econometrics and real estate. He is the author of the bestselling textbook Introducing Econometrics for Finance (Cambridge, 2009), now in its second edition.

Product details

  • Full PDF E-Book Included
  • Good Quality for print
  • Publisher : Cambridge University Press; 1st edition (May 24, 2010)
  • Language : English
  • Print Length : 474 pages
  • ISBN-10 : 0521873398
  • ISBN-13 : 978-0521873390

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