Market Data and Methods for Real Estate Portfolio Ratings (Lausberg/Wiegner)

1. University Background Introduction Market Data Methods Conclusion Market Data and Methods for Real Estate Portfolio Ratings(Lausberg/Wiegner) OUTLINE Presentation by Carsten Lausberg prepared for the 16th Annual Conference of the European Real Estate Society,June 24-27, 2009 in Stockholm/Sweden

2. University Background Introduction Market Data Methods Conclusion Nürtingen-Geislingen University: One of the Pioneers in Real Estate Education in Germany • Located in south-western Germany • 3,500 students in 20 degree courses • Several rankings show HfWU in the top flight of Germany‘s business schools (Stern, Spiegel, ManagerMagazin, Stiftung Warentest, Wirtschaftswoche, Focus) • Major in real estate management since 1983 • Degree course in real estate management since 1998 (Diplom/Master and B.S.) • Today: Appr. 360 real estate students currently enrolled, 12 real estate professors and more than 27 lecturers, 500 alumni in the real estate industry • Accredited by RICS and FIBAA Stuttgart GEISLINGEN Munich

3. Motivation: Improvement of market transparency in real estate risk management Rating: Central element of modern risk management Especially for Banks, thanks to Basel II Huge leap of development Not well documented in the real estate literature Subject: Internal credit rating for a large group of German banks(4 years, 800 loans in the development sample, 3,000+ in the validation) External rating for German open-ended funds(3 years, 35 portfolios, 3,800 properties, 70,000 contracts) Market rating for 125 German cities University Background Introduction Market Data Methods Conclusion Motivation For This Study

4. Subjects: Physical assets Property/Project Portfolio Financial assets based on properties Loans, bonds, MBS Stocks Others (market, tenant, manager…) University Background Introduction Market Data Methods Conclusion Definitions • Rating: A holistic evaluation of the future perspectives of a property, a real estate portfolio, a real estate product or another issue connected with real estate on the basis of indicators • Purposes: • Credit rating • Investment rating

5. Input Data University Background Introduction Market Data Methods Conclusion Rating Quality Method Person Data Others Property Market Management

6. University Background Introduction Market Data Methods Conclusion Classification of Market Data According to the Frame of Reference

7. University Background Introduction Market Data Methods Conclusion Classification of Market Data According to Scale Type and Objectivity

8. University Background Introduction Market Data Methods Conclusion Evaluating the Suitability of Market Data • Criteria: • Objectivity, reliability, validity • Long time series • Completeness and consistency • Comparibility of definitions • Availability in a timely fashion and on a low level of aggregation • Problematic fields: • Market segments with a general lack of data • Correlations • Conclusion: • Still a lot of work to do • Compromises necessary • Expertise of the rating analyst important

9. University Background Introduction Market Data Methods Conclusion Developing a Real Estate Rating • Methods for Development: • Scoring • Simulation • Combination 1) Scoring • Empirical-statistical approach • Univariate analysis of all risk factors • Multivariate analysis • Combination of the scorecards to an overall model • Empirical-qualitative approach • Transfer into a rating grade

10. University Background Introduction Market Data Methods Conclusion Developing a Real Estate Rating 2) Simulation • Basis: investment calculation (DCF model) • Simplified • Extended • Partial models to reduce complexity and concentrate on the objectives of the rating • Core: modelling the rental cash flow • Transfer into a rating grade 3) Combination

11. Rent [€] University Background Current Contract Rent Modelled Contract Rent Frictional Vacancy Modelled Contract Rent Modelled Contract Rent Introduction Market Data Incentives Forecasted ContractRent Methods Conclusion I II III IV 2007 2008 2009 2010 2011-2012 Modelling the Rental Cash Flow Forecasted Property-Specific Market Rent Adaptation of Contract Rent to Market Rent

12. University Background Introduction Market Data Methods Conclusion

13. University Background Introduction Market Data Methods Conclusion Testing • Absolutely necessary… but often neglected in practice • Key elements: • Calibration • Validation (out of time, out of sample, use-test)

14. University Background Introduction Market Data Methods Conclusion Summary and Conclusions • Combination of data from different sources and mix of methods can contribute to meaningful real estate portfolio ratings • Improvement of the data situation necessary • Official statistics, length of time series, international comparability • Role of researchers, ERES, and others to promote transparency • Formalization of risk management in real estate • Standard defintions • Benchmarking • Research and Development • Methods can be improved • Lack of knowledge and experience as well as wrong incentives have to be taken into account • Training • Spreading the knowledge • Necessary to reduce human errors in calculating and interpreting rating grades

15. Contact: Dr. Carsten Lausberg, M.S. Professor of Real Estate Banking Nuertingen-Geislingen University Parkstr. 4 73312 Geislingen Germany carsten.lausberg@hfwu.de