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ERES Conference Milano, 24.-26.06.2010

Alignment Of Interest In Non-Listed Real Estate Funds - Fee Structure And Its Impact On Real Estate Fund Performance. ERES Conference Milano, 24.-26.06.2010 Hubertus Bäumer, Dr. Tobias Pfeffer, Dr. Christoph Schumacher Generali Deutschland Immobilien, Cologne, Germany

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ERES Conference Milano, 24.-26.06.2010

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  1. Alignment Of Interest In Non-Listed Real Estate Funds -Fee Structure And Its Impact On Real Estate Fund Performance ERES Conference Milano, 24.-26.06.2010 Hubertus Bäumer, Dr. Tobias Pfeffer, Dr. Christoph Schumacher Generali Deutschland Immobilien, Cologne, Germany Contact: hubertus.baeumer@generali.de / tobias.pfeffer@generali.de

  2. Agenda 1 2 3 4

  3. IntroductionResearch Problem and Purpose 1 Problem description: • Fund terms and structures among non-listed real estate vehicles are extremely heterogeneous. • Information on performance, fund-specific variables in particular “fees” is hardly available. • Research on link between property fund performance and fund attributes is limited. • Non-listed real estate vehicles are a relatively “young “ segment for institutional RE investors. • Short time series, often small samples, market data not standardized. • Scope: • Non-listed property funds, institutional investors, European allocation including Eastern Europe, mostly “core” and “value-added” funds, European and some international promoters, funds from all jurisdictions. • Purpose of the study: • “The aim of this paper is to critically analyze the effect of fee structures on performance of property vehicles. In this way, the paper contribute to a better understanding of the role of fund terms for the alignment-of-interest between investors and fund managers.”

  4. Agenda 1 1 2 2 3 4

  5. Literature ReviewFew research on performance of non-listed funds in Europe available 2 Baum, A. (2008), “The Emergence of Real Estate Funds”, in Peterson, A (ed.) Real Estate Finance: Law, Regulation and Practice, London, LexisNexis. Baum, A., Farrelly, K. (2009): ‘Sources of alpha and beta in property funds: a case study’, JRER, Vol. 2., No. 3, 2009, pp. 218-234. Fuerst, F., Matysiak, G. (2009), “Drivers of Fund Performance: A Panel Data Analysis”, Working Papers in Real Estate & Planning 02/09. Brounen, D., Veld, H. O. and Raitio, V. (2007), Transparency in the European Non-Listed Real Estate Funds Market. Journal of RPM, 107-118. Devaney, S., Lee, S. and Young, M. (2007) Serial persistence in individual real estate returns in the UK. JPIF, 25/3, 241-273. Fuerst, F., Matysiak, G. (2009), “Drivers of Fund Performance: A Panel Data Analysis”, Working Papers in Real Estate & Planning 02/09. Hoesli, M. and Lekander, J. (2005), Real estate portfolio strategy and product innovation in Europe, JPIF, 26/2, 162-176. McAllister, P, 2000, ‘Is direct investment in international property markets justifiable?’,Property Management, vol. 18, no. 1, pp. 25-33. Cheng, P., Ziobrowski, A., Caines, R. ,Ziobrowski, B. (1999): “Uncertainty and Foreign Real Estate Investment.”JRER, Vol. 18, No. 3, pp. 463-479. Eicholtz, P, 1996, ‘Does International Diversification Work Better for Real Estate than for Stocks and Bonds?’, FAJ, vol. 52, no. 1, pp. 56-62. Benjamin, J., Sirmans, G., Zietz, E. (2001): ‘Returns and Risk on Real Estate and Other Investments: More Evidence.’, JREPM, Vol.7, No. 3. Viezer, T, 1999, ‘Econometric Integration of Real Estate's Space and Capital Markets,’ Journal of Real Estate Research, vol. 18, no. 3, pp. 503-519. Brown, G.R. and Matysiak, G.A. (2000): ‘Real Estate Investment: A Capital Market Approach’, Edinburgh: Financial Times Prentice Hall.

  6. Set-up of the study – Regression & Mean-varianceCreate a standardized sample with consistent and coherent data 2 Y X (Step 1) X (Step 2) • „Fees“ • Management fees • Transaction fees • Performance fees • Total fees 1. Performance Total Return Income Return Capital Appreciation • „Fees“ • Management fees • Transaction fees • Performance fees • Total fees INREV Index / Fund reports INREV Fee & Terms Study 3. Fund-specific Leverage Investment style Property sector Regional allocation Fund size 467 vehicles GAV € 261 bn 67% Core 23% Value-added 10% Opportuniity 268 vehicles GAV € 144 bn 53% Core 33% Value-added 14% Opportunity Fund reporting to INREV

  7. Data Sources and definitionsCreate a standardized sample with consistent and coherent data 2 Management fee Standardized to GAV-based figures. Includes yearly based charges to fund management excluding third-party fees eg. custodian fees. Transaction fee Includes acquisition and sale fees. More than 85% of transactions fees are acquisition fees. Performance fee Hurdle rate instead of “total performance fee paid” more significant for this study (Little perf. fees paid in 2009, often at end of fund life, escrow accounts, base on multiple years...) Regional Split into five different regions (North, West, East, South, Other) Property sector Split into three four different sectors (office, retail, industrial > 67%, Diversified) Performance Based on 2009 performance, calculated based on INREV methodology. Fund Size Gross Asset Value (GAV); dummy variables for small, (<25%), medium, large (>75%) funds. Leverage Leverage as reported by the funds to INREV. Investment style As reported by the fund manager to INREV for the individual vehicles.

  8. Data Sources and definitionsCreate a standardized sample with consistent and coherent data 2

  9. Agenda 1 2 3 4

  10. Descriptive Statistics Sample represents 178 European property funds with a volume of € 89 bn. 3

  11. Sample Mean Variance Analysis – Total Return and Fund Attributes“Size” and “leverage” have negatively impacted performance 3 Role of Fund Size Role of Leverage

  12. Sample Mean Variance AnalysisHigh hurdle rates have adversely affected fund performance significantly 3 Role of Total Fees combined with Hurdle Rate

  13. Regression - Total fees, hurdle rate, leverage on total returnFees and leverage are significant factors in fund performance 3

  14. Regression –Multiple factors on total returnRegional allocation, property type and style / leverage are important 3

  15. RegressionResidual / normality tests normal and homoscedastic 3

  16. Regression –Multiple factors on capital appreciationRegionEast, SectorIndustrial, Leverage, FeeHurdle negative effect 3

  17. Regression –Multiple factors on distributionStyle / leverage most important for income component 3

  18. Agenda 1 1 2 3 4

  19. SummaryFee structures are crucial in non-listed property fund investments 4 • Results confirm evidence of former research on effect of leverage, style, region, property type. • Including fee structures in performance analysis of property funds is essential. • Different fees have a different effect on performance. • Hurdle rate is extremely important factor in fee structure / incentive scheme. • Positive effect of transactions costs on performance is related to market cycle. • Leverage is dominant factor / performance driver. • Distribution strategy requires careful consideration of investment restrictions to prevent style drift. • Future research questions / aspects: • How can a fee structure be optimized? • What impact does an alignmentof Interest have on real estate performance? • Includevintageyears and extend analysis to time-seriesassoonasavailable!

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