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.

To fully function in today’s global real estate industry, students and professionals increasingly need to understand how to implement essential and cutting-edge quantitative techniques. This book presents an easy-to-read guide to applying quantitative analysis in real estate aimed at non-cognate undergraduate and masters students, and meets the requirements of modern professional practice. Through case studies and examples illustrating applications using data sourced from dedicated real estate information providers and major firms in the industry, the book provides an introduction to the foundations underlying statistical data analysis, common data manipulations and understanding descriptive statistics, before gradually building up to more advanced quantitative analysis, modelling and forecasting of real estate markets. Our examples and case studies within the chapters have been specifically compiled for this book and explicitly designed to help the reader acquire a better understanding of the quantitative methods addressed in each chapter. Our objective is to equip readers with the skills needed to confidently carry out their own quantitative analysis and be able to interpret empirical results from academic work and practitioner studies in the field of real estate and in other asset classes. Both undergraduate and masters level students, as well as real estate analysts in the professions, will find this book to be essential reading.

Foundations of Real Estate Financial Modelling is specifically designed to provide an overview of pro forma modelling for real estate projects. The book introduces students and professionals to the basics of real estate finance theory before providing a step-by-step guide for financial model construction using Excel. The idea that real estate is an asset with unique characteristics which can be transformed, both physically and financially, forms the basis of discussion. Individual chapters are separated by functional unit and build upon themselves to include information on: Amortization Single-Family Unit Multi-Family Unit Development/Construction Addition(s) Waterfall (Equity Bifurcation) Accounting Statements Additional Asset Classes Further chapters are dedicated to risk quantification and include scenario, stochastic and Monte Carlo simulations, waterfalls and securitized products. This book is the ideal companion to core real estate finance textbooks and will boost students Excel modelling skills before they enter the workplace. The book provides individuals with a step-by-step instruction on how to construct a real estate financial model that is both scalable and modular. A companion website provides the pro forma models to give readers a basic financial model for each asset class as well as methods to quantify performance and understand how and why each model is constructed and the best practices for repositioning these assets.

The authors provide a descriptive account of the processes involved in property market forecasting, with a strong critical reflective element running through the chapters. A careful introduction is given to the technical issues of forecasting and then real estate topics are used to demonstrate practical applications. The book will start with an assumption of basic statistical knowledge and deal with the main modelling techniques in the real estate field. The aim is not to provide a mathematical analysis of modelling, but a guide to and assessment of standard modelling techniques. Econometrics is the applications of mathematical and statistical techniques to economics in the analysis of data, and the development and testing of theories and models. The use and abuse of econometrics in real estate will be discussed and new developments in modelling examined, as well as how these changes are being received in the real estate world.

Learn how to identify the bottom of your local real estate market and understand when to buy by using the tools and tips in Forecasting for Real Estate Wealth: Strategies for Outperforming Any Housing Market. Take advantage of the great deals created by falling real estate prices and discover the four questions every real estate investor must ask before buying, selling, or holding any property. With this guide, you can forecast the value of any property in 1 or 5 years, predict which investment property will give you maximum return, and secure low-cost financing.

NAMED ONE OF THE BEST COMMERCIAL REAL ESTATE BOOKS BY THE MOTLEY FOOL "Staiger gives us the technical tools needed to build robust pro forma modeling around our real estate assets." –MillionAcres Now in its third edition, Foundations of Real Estate Financial Modelling equips a new generation of students and professionals with a resource MillionAcres guarantees they’ll "use throughout [their] commercial investing career[s]." Designed to provide increased scalable basis of pro forma modelling for real estate projects, this complete update and revision of the classic text offers a step-by-step introduction to building and understanding the models underlying investments in properties from single-family rentals to large-scale developments. Case studies drawn from the author’s storied investment career put models into real-world context while problem sets at the end of each chapter provide hands-on practice for learners at any stage of their real estate careers. This edition employs the innovative financial metric P(Gain) to quantify the probability of a Return of Capital, ensuring readers’ ability to answer the most fundamental question of investing—What is the probability I’ll get my money back? The fully revised and enhanced third edition is organized in three functional units: (1) Real Estate Valuation Basics, Theory, and Skills, (2) Real Estate Pro Forma Modelling, and (3) Real Estate Pro Forma (Enhancements). Chapters cover: Interest Rates (Prime, LIBOR, SOFR) Amortization (Cash-Out Refinance modelling) ADC (Acquisition, Development, Construction) Module Rent Roll Module (including seasonality) Waterfall Hotel Consolidation Stochastic Modelling and Optimization Additional chapters are dedicated to risk quantification and include scenario, stochastic, and Monte Carlo simulations, equity waterfalls, and integration of US GAAP financial statements. A companion website provides the real estate pro forma models to readers as a reference for their own constructed models, www.pgainllc.com. An ideal companion in the classroom and the boardroom, this new edition of Foundations of Real Estate Financial Modelling will make even novices the "experts in the room on [their] chosen asset class" (MillionAcres).

There is a small and growing literature that explores the impact of digitization in a variety of contexts, but its economic consequences, surprisingly, remain poorly understood. This volume aims to set the agenda for research in the economics of digitization, with each chapter identifying a promising area of research. Economics of Digitizationidentifies urgent topics with research already underway that warrant further exploration from economists. In addition to the growing importance of digitization itself, digital technologies have some features that suggest that many well-studied economic models may not apply and, indeed, so many aspects of the digital economy throw normal economics in a loop.Economics of Digitization will be one of the first to focus on the economic implications of digitization and to bring together leading scholars in the economics of digitization to explore emerging research.

This eBook contains six chapters on the application of quantitative techniques to real estate, they are as follows:* 'To use or not to use; which type of property should you choose? Predicting the use of activity based offices' by Rianne Appel-Meulenbroek, Astrid Kemperman, Marleen Kleijn and Els Hendriks.* 'Property market modelling and forecasting: simple vs. complex models' by Arvydas Jadevicius and Simon Huston.* 'Comparing approaches to economic impact analysis of property redevelopment' by Christopher Hannum.* 'The long-term linkages between direct and indirect property in Australia' by Jaime Yong and Anh Khoi Pham.* A Practice Briefing on 'Real estate risk: heavy tail modelling using Excel' by Roger Brown and Beate Klingenberg. * An Education Briefing on 'The plethora of yields in property investment & finance: a summary' by Nick French and Michael Patrick.