Property Derivatives in the Strategic Asset Allocation

MotivationData

Research DesignPreliminary Results

Appendix

Property Derivatives in the Strategic AssetAllocation

ERES 2009 - Doctoral Session

Bertram SteiningerIRE|BS, University of Regensburg

June 24, 2009

Bertram Steininger IRE|BS, University of Regensburg Property Derivatives in the Strategic Asset Allocation

MotivationData


Appendix

Table of Contents

Motivation

DataData CollectionInterpolation

Research Design

Preliminary Results

AppendixMarket CapitalizationTransaction CostsTrading Volumes


MotivationData


Appendix

Motivation I

I real estate as a major asset classI real estate’s characteristics:

I stability of their valuesI opportunity to hedge against inflationI specific risk-return characteristicsI low co-movements with traditional stock and bond marketsI lot size transformationI transaction costsI no short possibility

However, insufficient asset class for individuals!?


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Motivation II

Benefits from property derivatives

I term transformation and liquidity

I transaction costs

I bridge finance and efficient leverage

I short possibility

I lot size transformation

I diversification

I alpha generating

I physical portfolio management

I no property knowledge


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Motivation III

Drawbacks from property derivatives

I price to pay

I mark to market risk

I counterparty risk

I liquidity drying up

I lack of traditional alpha

I underlying risk


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Motivation IV

UK IPD Certificate: Key Features

I underlying: IPD UK Annual Index under ”All Properties TR”

I ”100% exposure to physical UK commercial property”

I Issuer: Goldman Sachs Jersey (Limited)

I Guarantor: Goldman Sachs Europe and The Goldman SachsGroup, Inc. (A, A1, A+; outlook: -, -, )

I minimum investment: GBP 10.00

I issue date: 26 June 2006

I expiry date: 31 March 2011

I liquidity: continuously quoted on the LSE

I fixed leg: 2.80% p.a.


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Motivation V

Studies suggest a optimal allocation of real estate in a mixed assetportfolio of 5-25% (for an overview see e.g. Hoesli, Lekander andWitkiewicz (2004)).The difference between suggested and actual allocation to realestate is considered to be a puzzle in real estate research (Chun,Sa-Aadu and Shilling (2004)).

Can property derivatives solve this puzzle?

I mean-downside-risk analysis

I by using forward contracts with optimal hedge ratios

I 130/30-portfolio strategy

I comparison between ex ante and ex post adjustments


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Data CollectionInterpolation

Data Collection

I included asset classes: stocks, bonds, and real estatederivatives

I based on quarterly data from Q1 1996 to Q4 2008

I investment countries: the USA, the UK, France (FRA), andGermany (GER)


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Interpolation

Problem: For FRA and GER only annual real estate dataSolution: Interpolation?!

I Nearest neighbor interpolation

I Linear interpolation

I Cubic spline interpolation

I Modified cubic spline interpolation

I Monte-Carlo simulation


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Interpolation Comparison

Figure: Comparison of different Spline Interpolation Methods


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Estimation Errors for the USA

The nearest neighbor interpolation (NNI), the linear interpolation (PLI), thecubic spline interpolation (CSI), the modified cubic spline interpolation (MCSI),and the Monte-Carlo simulation (MCS), are compared with the real returns(RR) by dint of the mean (µ), the standard deviation (σ), the coefficient ofvariation (CV), the mean squared error (MSE), and the root mean squarederror (RMSE).

RR NNI PLI CSI MCSI MCS

µ 11.47 11.36 11.74 11.94 11.39 11.37σ 7.67 6.43 4.94 4.87 6.89 6.66CV 0.67 0.57 0.42 0.41 0.60 0.59

MSE 0 20.35 15.67 17.26 7.82 21.89RMSE 0 4.51 3.96 4.16 2.80 4.68

Table: Estimation Errors for the USA


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AA in a Shortfall-Risk Framework I

Initial Position: International Asset Allocation

I no normality

I different currency areas

Research design:

I Mean-Downside-Risk Analysis

I by using forward contracts with optimal hedge ratios

I 130/30-portfolio strategy

I comparison between ex ante and ex post adjustments

I stochastic dominance analysis (EWP, MRP, TP)


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AA in a Shortfall-Risk Framework IIModifying Harlow (1991), the optimization approach is defined as:

minxi

→ 1

T

TXt=1

max

rf ;t −

NXi=1

xiRi ;t ; 0

!2

, (1)

subject to the constraints:

NXi=1

xiR i = RP ,

NXi=1

xi = 1,

NXi=1

(xi |xi < 0) ≥ −0.3,

i = 1, 2, ..., N.


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AA in a Shortfall-Risk Framework III

T is the number of observed periods,

R i is the mean return on the asset alternative i over all periods,

RP is the prescribed portfolio return,xi is the portfolio weight of asset alternative i , andrf ;t is the risk free rate at the beginning of period t.


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AA in a Shortfall-Risk Framework IV

I the returns are realized in different currency areas

I the returns has to be converted for an euro-investor

Ri = (1 + Rai ) (1 + ea) − 1 = Ra

i + ea + Rai ea (2)

Rai is the the uncertain monthly return on asset alternative i

in country a, andea is the exchange rate return between the euro and the

foreign currency area.


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AA in a Shortfall-Risk Framework VI

Rhi = Ri + hi (f

a − ea) (3)

The forward premium f a between currency a and the euro isdefined as:

f a =F a

t+1 − Sat

Sat

(4)

F at+1 is the forward price at the point in time t for the delivery

of the currency at the point in time t + 1from the perspective of the home country, and

hi is the hedge ratio.


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Preliminary Results

monthly data from 1998-2008/6; mean − lpm1

Figure: Efficient Portfolio Sets


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Preliminary Results

Figure: Optimal Weights for the MRP and TP Portfolios


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Market CapitalizationTransaction CostsTrading Volumes

Market Capitalization

Country Stocks Bonds Real Estates

United States 13,552.2 4,478.3 1,287.2People’s Republic of China 4.230.2 1,136.7 NAJapan 3.211.0 4,854.4 201.2United Kingdom 2.621.5 613.5 411.3France 1.882.8 954.6 203.3Germany 1.430.5 946.4 277.6

Source World Bank BIS IPD

Table: Market Size in 2007 (billion euro)


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Transaction Costs

Figure: Transaction Costs

The values for Belgium, the United Kingdom, Australia, Hong Kong, Japan,

Singapore, and the United States are averaged in subject to the different legal

basis points in their countries.


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Transaction Costs

Total annualised cost of buying a commercial property unit trustand selling it after 5 years

Country

United States 0.75%United Kingdom 0.25%France 0.50%Germany 0.35%

Source: GS (2008)

Table: Transaction Costs


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Trading Volumes

Figure: Notional Amount of Derivatives

(in billion euro)


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Property Derivatives in the Strategic Asset Allocation