Real Estate Mathematics: Applied Analytics and Quantitative Methods for Private Real Estate Investing

517 Pages·2011·3.096 MB·English

by  David Lynn, Tim Wang (eds.)

REAL ESTATE
MATHEMATICS
Applied analytics and quantitative methods
for private real estate investing
Edited by
David Lynn and Tim Wang
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Published in October 2011 by
PEI
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© 2011 PEI
ISBN 978-1-904-696-93-3
eISBN 978-1-908783-52-3
This publication is not included in the CLA Licence so you
must not copy any portion of it without the permission of the
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PEI editor: Wanching Leong
Production editor: Julie Foster
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Printed in the UK by: Hobbs the Printers
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Contents
Figures and tables
About the editors
Introduction and acknowledgements
By David Lynn, Clarion Partners
SECTION I: FUNDAMENTALS
1Private real estate allocations in multi-asset investment
portfolios
By Greg MacKinnon, Pension Real Estate Association
Introduction
The standard arguments for real estate
Mean-variance optimisation
Portfolio theory issues
An alternative allocation paradigm: liability-driven investing
Conclusion
2Forecasting real estate returns
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By Timothy Bellman
Introduction
Why forecast real estate performance?
What to forecast?
How to forecast?
Qualitative approaches
Forecasting in practice
3Real estate investment capital structure
By Hugh Kelly, Real Estate Economics
Introduction
Capital structure at the industry level
Industry structure reflects individual investment
characteristics
Leverage generates risk and opportunity for the equity
investor – and the lender
Why not ‘borrow to the max’?
What is the lender paid for?
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The premium for taking real estate equity investment risk
The mezzanine
How the mezzanine preferred equity solution works
Concluding observation
4Contrasting approaches to quantifying risk in real estate
investments
By Jon Southard, CBRE Econometric Advisors
Introduction
Scenario approach
Stochastic Monte Carlo analysis
Using the standard error of the estimate (SEE)
Combinations of the three approaches
Conclusion
Appendix A: Procedure for approximating VaR level of a
specific scenario
5Modelling uncertainty: Monte Carlo analysis and the
pricing of real estate
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By Randall Zisler and Matthew Zisler, Zisler Capital
Associates, LLC
The nature of real estate and recent encounters with risk
Monte Carlo analysis
Building a Monte Carlo model
A sample application of Monte Carlo modelling
The future of real estate risk analysis
6Analysing and pricing risk in international real estate
markets
By Maurizio Grilli and Richard Barkham, Grosvenor
Introduction
Hurdle rates
The risk-return equation
The risk premium
Target versus expected returns
Conclusion
7Special considerations in sustainable property financial
analysis
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By Scott Muldavin, Green Building Finance Consortium
Introduction
Step 1: Selecting the financial model
Step 2: Evaluating property sustainability
Step 3: Assessing the costs/benefits of sustainability
Step 4: Evaluating the financial implications of costs/
benefits
Step 5: Determining financial model inputs
Step 6: Conducting a risk analysis and presentation (RAP)
Sustainability investment performance
Conclusion
8Real estate loans and real estate debt
By Sam Chandan, Chandan Economics
Introduction
Leverage and the incentive to borrow
Why borrow?
When to borrow
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