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Real Estate Investments Piet Eichholtz & Dirk Brounen April 9, 2001 PowerPoint Presentation
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Real Estate Investments Piet Eichholtz & Dirk Brounen April 9, 2001

Real Estate Investments Piet Eichholtz & Dirk Brounen April 9, 2001

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Real Estate Investments Piet Eichholtz & Dirk Brounen April 9, 2001

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  1. Real Estate Investments • Piet Eichholtz & Dirk Brounen • April 9, 2001

  2. Today’s Program • Organization of the Course • Course Overview • Requirements • Schedule & Speakers • Materials & Readings • Papers • Contact information • Introduction to Real Estate • Risks • Returns • Portfolios

  3. Innovations • 1. English Language • 2. More and New Topics • 3. Debates, more Interaction • 4. Papers, Debates and Participation • More opportunities to show your skills, effort and knowledge

  4. Requirements • To understand and succeed: • Common Sense • Basic Mathematics, Statistics, and Finance Theory • Dedication • Assessment: • Paper 1: 15% • Paper 2: 15% • Debate: 10% • Final Exam: 60% • Final Exam needs to exceed 5.5

  5. Schedule • MO April 9Introduction to Real Estate Eichholtz E0.03 • TU April 17Real Estate Securitization Eichholtz A3.03 • MO April 23Direct Investment Techniques Brounen E0.03 • FR April 27Advanced Topics in Direct Inv. Brounen A1.02 • MO May 7Paper-Debates Eichholtz E0.03 • MO May 21Performance Measurement Hordijk E0.03 • MO May 28Index Construction Theebe E0.03 • TU June 5Mortgage Topics Brounen A3.03 • MO June 11Current Topics Guest E0.03 • MO June 18Paper-Debates Brounen E0.03 • FR June 29Final Exam

  6. Practical Matters • Read Ahead of Lectures!!!!!!! • Better Understanding of Lectures • Less stress and more success during the exam • Lectures will be in English • Readings are in English • Presentations need to be given in English • Paper may be written in Dutch • Final Test may be written in Dutch

  7. Papers, Debates • Form teams of 2 persons each • Send an email to: dirkb@fee.uva.nl with your name, ID-number, team-mate and preference concerning topic 1-4 and 5-8. • Each team needs to write 2 papers • Deadline 1: May 7 • Deadline 2: June 18 • Each team needs to debate at least 1 of their papers

  8. Paper structure • Each paper should consist of: • - a brief introduction • - a discussion of the relevant literature (additional literature will • be appreciated) • - a section on the pro-arguments • - a section on the contra-arguments • - a summarizing conclusion • - a reference list

  9. Paper Topics: • May 7: • 1. Shell Pension to sell off all property. • 2. Real Estate; investing direct or indirect? • 3. Portfolio construction bottom-up or top-down? • 4. The International investment strategy of the ABP. • June 18: • 5. Real Estate; a hedge for inflation? • 6. MBS; US history, European mystery • 7. Home equity insurance; (science) fiction • 8. The internet; mixed effects on the real estate industry • Read the Handout for details

  10. Contact Information • Dirk Brounen Piet Eichholtz • Room E-4.27 Room E-5.35 • Tel: 020 5256004 • dirkb@fee.uva.nl • Course info Additional Literature • www.fee.uva.nl/fm SBV Documentatiecentrum •  courses Wibaustraat 129 •  course material (Parool-toren) • Information board 4th floor • (across room E-4.29)

  11. Introduction to Real EstateReturns, Risks and Portfolios Piet Eichholtz

  12. Risks, returns and portfolios • Risk and return • Portfolios • Mixed-asset • Real Estate • Key Questions: • Can modern finance theory be applied to the real estate investment practice? • How can investors develop a systematic real estate investment policy using faulty data?

  13. Key concepts • Risk and return • returns are being ‘paid’ with risks • Types of risks • only systematic risks will be rewarded • Market efficiency • does this hold for real estate market? • Diversification • maximize differences within the portfolio • Market-portfolio • the optimally diversified portfolio • The are no instant solutions • Portfolio theory is no predictor for the future

  14. Risks and returns • Forecast • Measure • The risk-return tradeoff • Types of risks

  15. Garbage in……… • Appraisal returns • Offer reasonable estimation of average returns • Underestimate volatility • Underestimate correlations with other assets • Overestimate correlation with inflation • Garbage out • The eighties: Portfolio models suggested real estate allocations up to 75% • The nineties: Portfolio models suggested real estate allocations of 0%

  16. Cleaning up the garbage • Rules of thumb: • Risk of real estate is 75% of risk of common stocks • Risk of real estate lies between common stocks and bonds • Multiply standard deviation • Unsmoothing: • Develop model of appraisal-process and remove the inherent • risks (see Fischer, Geltner and Webb) • Surveys: • Portfolio models use expected returns and risks: ask • investors for their expectations • The market portfolio

  17. Diversification • Problems • real estate return data • garbage in / garbage out • Solutions • adjust the data using the rule of thumb • unsmoothing • use survey data • turn the analysis around • use the market portfolio

  18. The Dutch real estate market portfolio, 1992 • Volume Price % % • Residential 6 mln units 135.000 810 46.9 • Retail 21 mln sqm 3100/sqm 65 3.8 • Office 30 mln sqm 2000/sqm 60 3.5 • Industrial 43 mln sqm 1000/sqm 43 2.5 • Miscellan. 24 1.4 • Real Estate 1002 58.1 • Common stocks 17.5 Bonds 24.5 • Sum total 1728 100

  19. The US real estate market portfolio, 1990 • Volume Price % % • Residential 6.122 bln 69.8 • Singlefamily 5.419 61.7 • Multifamily 552 6.3 • Condo’s 96 1.1 • Mobile Homes 55 0.6 • Commercial 2.655 30.2 • Retail 1.115 12.7 • Office 1.009 11.5 • Industrial 531 6.0 • Sum total 100 100

  20. International pension fund portfolios: 1997 (1990)

  21. Possibilities if there are no real estate data at all • Economical diversification • Classify regions with respect to their economic base • How to measure this? • Analyze the composition of the economy • Analyze employment • Measure specialization

  22. Portfolio construction approaches: • Top-down using sophisticated models • Compute optimal allocations over the asset classes • Compute optimal allocations within each asset class • (both with respect to property type and region) • Apply outcomes for portfolio construction • Bottom-up using intuition, deal-making • Select the best deals in town • Construct collection of good deals