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 SchumacherGenerali Deutschland Immobilien, Cologne, Germany

Contact: hubertus.baeumer@generali.de / tobias.pfeffer@generali.de

Introduction

Analysis

Results

Summary

Agenda

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IntroductionResearch Problem and Purpose

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.”

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Introduction

Analysis

Results

Summary

Agenda

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Literature ReviewFew research on performance of non-listed funds in Europe available

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.

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Set-up of the study – Regression & Mean-varianceCreate a standardized sample with consistent and coherent data

1. Performance

a. Total Return

b. Income Return

c. Capital Appreciation

2. „Fees“

a. Management fees

b. Transaction fees

c. Performance fees

d. Total fees

3. Fund-specific

a.Leverage

b.Investment style

c.Property sector

d.Regional allocation

e.Fund size

2. „Fees“

a. Management fees

b. Transaction fees

c. Performance fees

d. Total fees

Y X (Step 1) X (Step 2)

INREV Index / Fund reports INREV Fee & Terms Study

Fund reporting to INREV

467 vehiclesGAV € 261 bn

67% Core23% Value-added10% Opportuniity

268 vehiclesGAV € 144 bn

53% Core33% Value-added14% Opportunity

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Investment style Investment style

Leverage Leverage

Fund Size Fund Size

Performance Performance

Property sector Property sector

Regional Regional

Performance fee Performance fee

Transaction fee Transaction fee

Data Sources and definitionsCreate a standardized sample with consistent and coherent data

Based on 2009 performance, calculated based on INREV methodology.

Gross Asset Value (GAV); dummy variables for small, (<25%), medium, large (>75%) funds.

Leverage as reported by the funds to INREV.

As reported by the fund manager to INREV for the individual vehicles.

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...)

Includes acquisition and sale fees. More than 85% of transactions fees are acquisition fees.

Management fee Management fee Standardized to GAV-based figures. Includes yearly based charges to fund management excluding

third-party fees eg. custodian fees.

Split into five different regions (North, West, East, South, Other)

Split into three four different sectors (office, retail, industrial > 67%, Diversified)

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Data Sources and definitionsCreate a standardized sample with consistent and coherent data

Fee based on Assumption

GAV No further assumption was needed

NAV Recalculation to a fee based on GAV dependent on the individual leverage of the fund

Property values It was assumed that the fee is identical with a fee on GAV

Drawn Commitment

It was assumed that the fee is identical with a fee on NAV and it was recalculated accordingly

Region Countries

West Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Luxembourg, The Netherlands, Norway, Sweden, Switzerland, United Kingdom

East Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Russia, Slovakia

South Greece, Italy, Portugal, Spain, Turkey

Rest Non-Europe Asia, Non-Europe North America, Non-Europe South America, Not Reported

Sector Assumption

Sector One type of sector (office, retail, industrial) more than 67 percent of the fund

Diversified No specific sector has more than 67 percent of the fund

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Introduction

Analysis

Results

Summary

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Agenda

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

Dive East South West DiverIndus Offi Resid Retail Core Value Mean 0.07 0.07 0.13 0.73 0.29 0.12 0.28 0.08 0.22 0.69 0.31 Median 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00 1.00 0.00 Maximum 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Minimum 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Std. Dev. 0.26 0.25 0.34 0.45 0.46 0.33 0.45 0.27 0.42 0.47 0.47 Skewness 3.28 3.45 2.21 -1.04 0.91 2.29 0.98 3.13 1.32 -0.80 0.80 Kurtosis 11.77 12.91 5.89 2.08 1.84 6.23 1.95 10.80 2.74 1.64 1.64

Style Region Sector

Fees Fund Size Performance / Return OthersHurdle Manag. Total Trans. Big Medi Small Capital Income Total Lever GAV

Mean 6.67 0.80 1.50 0.70 0.25 0.50 0.25 -0.11 0.03 -0.08 44% 500,000,000 € Median 7.25 0.60 1.30 0.00 0.00 0.50 0.00 -0.11 0.03 -0.07 48% 352,000,000 € Maximum 14.00 3.70 5.26 3.88 1.00 1.00 1.00 0.12 0.20 0.18 89% 4,930,000,000 € Minimum 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.54 0.00 -0.48 0% 1,850,000 € Std. Dev. 4.11 0.71 1.08 0.93 0.44 0.50 0.43 0.12 0.03 0.13 23% 534,000,000 € Skewness -0.65 2.04 0.78 1.24 1.14 0.00 1.17 -0.53 1.50 -0.54 -0.46 4.17 Kurtosis 2.10 6.96 3.05 3.85 2.29 1.00 2.37 3.11 8.03 2.80 2.26 30.19

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Sample Mean Variance Analysis – Total Return and Fund Attributes“Size” and “leverage” have negatively impacted performance

Size GAV nach 0.25/0.75 QuartileTR size small TR size medTR size big

Mean -4.50% -7.65% -12.42%Sd 10.64% 12.71% 12.50%Var 1.13% 1.61% 1.56%Min -34.21% -38.34% -48.42%Max 15.26% 13.65% 17.58%0.25 quart -10.78% -16.61% -19.91%0.75 quart 0.95% 1.81% -2.44%Sample 51 90 45gew Var 1.44% 1.60%t-Stat 3.12 4.39gew Var 1.33%t-Stat 6.72

Leverage nach 0.25/0.75 QuartileTR lev smallTR lev med TR lev large

Mean -0.23% -7.34% -19.20%Sd 6.21% 11.62% 11.89%Var 0.39% 1.35% 1.41%Min -16.09% -38.34% -48.42%Max 17.58% 14.52% 4.29%0.25 quart -3.17% -15.89% -27.41%0.75 quart 2.09% 1.85% -13.24%Stichp. Umfang 55 89 42gew Var 0.98% 1.37%t-Stat 8.60 11.60gew Var 0.83%t-Stat 20.51

Role of Fund Size Role of Leverage

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Sample Mean Variance AnalysisHigh hurdle rates have adversely affected fund performance significantly

Fee + HurdlRat based on 0.25/0.75 QuartileTR lev large TR small small TR med med TR large large TR large small TR small large

Mean 0.22% -9.44% -13.53% 3.07% -15.40%Sd 5.48% 10.12% 14.32% 5.00% 15.49%Var 0.30% 1.02% 2.05% 0.25% 2.40%Min -12.40% -24.36% -36.82% -9.76% -38.34%Max 12.28% 12.03% 7.25% 14.52% 9.26%0.25 quart 0.00% -19.39% -24.19% 1.37% -24.39%0.75 quart 2.03% -0.27% -0.57% 4.67% -11.26%Stichp. Umfang 21 31 16 15 9gew Var 0.73% 1.37% 1.03%t-Stat 8.13 2.40 8.91

Role of Total Fees combined with Hurdle Rate

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

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

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RegressionResidual / normality tests normal and homoscedastic3

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

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

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Introduction

Analysis

Results

Summary

Agenda

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4

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SummaryFee structures are crucial in non-listed property fund investments

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 alignment of Interest have on real estate performance?

Include vintage years and extend analysis to time-series as soon as available!

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