The interest rate sensitivity of real estate Alain

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The interest rate sensitivity of real estate Alain Chaney♣ ♣ University of Geneva (HEC),

The interest rate sensitivity of real estate Alain Chaney♣ ♣ University of Geneva (HEC), Switzerland (Ph. D Student), Informations- und Ausbildungszentrum für Immobilien, Switzerland, (Consultant) and Neue Aargauer Bank, Switzerland (Risk Manager) June 24, 2009

Outline 1. Motivation 2. Data 3. Methodology 4. Empirical Results 2 Motivation Data Methodology

Outline 1. Motivation 2. Data 3. Methodology 4. Empirical Results 2 Motivation Data Methodology Empirical Results ERES Conference 2009 July 24 -27, Stockholm

Previous work § Despite the facts that… § real estate plays an important role

Previous work § Despite the facts that… § real estate plays an important role for many financial investors § interest rate risk is difficult to diversify § traditional estimates of the interest rate sensitivity (i. e. Macaulay and Modified Duration) are not applicable to real estate …surprisingly little research performed on impact of interest rate changes on the value of a property Survey Estimated duration Approach Ward (1988) 2. 8 to 36 Hartzell et al. (1988) DCF-formula; simulation of formula parameters 0 to 6 Adams et al. (1999) 11. 4 to >100 Brown (2000) Equivalent Yield Model (DCF); use of IPD statistics formula parameters (i. e. rental values, income received and equivalent yields) 12. 8 Hamelink et al. (2002) Use of Ward's formula; empirical estimates of formula parameters (i. e. discount rate, growth rate and inflation flow-through) 3. 2 Motivation Data Methodology Empirical Results 3 ERES Conference 2009 July 24 -27, Stockholm

Previous work and research questions Past studies § Are based on simplistic DCF formulae

Previous work and research questions Past studies § Are based on simplistic DCF formulae § Duration derived by simulating values formulae parameters (Ward [1988], Hartzell et al. [1988], Adams [1999]) and / or empirical estimation up to a maximum of 3 formula parameters (Brown [2000], Hamelink et al. [2002]) § Indication of accuracy of final estimates is missing Research questions § How sensitive is the value of office properties to changes in interest rates… § …and how accurate is this measure? Motivation Data Methodology 4 Empirical Results ERES Conference 2009 July 24 -27, Stockholm

Data Variable Source Inflation Federal Statistic Office LIBOR 3 month Reuters Euromarket 3 month

Data Variable Source Inflation Federal Statistic Office LIBOR 3 month Reuters Euromarket 3 month Swiss National Bank Term structure (money market rates and yields of Confederation bonds) Swiss National Bank Office market rent Swiss National Bank GDP State Secretariat for Economic Affairs Vacancy rate IAZI Swiss Property Benchmark Expenses IAZI Swiss Property Benchmark CPI indexation degree IAZI AG Term of leases IAZI AG Risk premium Hedonic discount rate model from IAZI AG Public statistics Exclusive data from the Swiss property database owned by IAZI 5 Motivation Data Methodology Empirical Results ERES Conference 2009 July 24 -27, Stockholm

Basic idea § The interest rate sensitivity is equal to § Investment properties are

Basic idea § The interest rate sensitivity is equal to § Investment properties are usually valued according to the DCF method ➢ Required § § time series of FCF and of discount rates pay special attention on how discount rates and FCF change following a change in interest rates 6 Motivation Data Methodology Empirical Results ERES Conference 2009 July 24 -27, Stockholm

Approach 1. Model important macroeconomic time series and their interdependencies § interest rates, inflation,

Approach 1. Model important macroeconomic time series and their interdependencies § interest rates, inflation, economic condition, office market rent 2. Simulate the whole life of a typical office property, that is embedded in the macroeconomic environment, in order to derive the FCF § § FCF = CRP - EX, where CRP = f(MR, VAC, TOL, I, DII) 3. Use of MCS to incorporate the uncertainty of § § underlying stochastic processes of the time series and their interdependencies, i. e. of the modelling uncertainties 7 Motivation Data Methodology Empirical Results ERES Conference 2009 July 24 -27, Stockholm

Results Key figure Sim. rf 3 m real 1. 1% GDP real 1. 6%

Results Key figure Sim. rf 3 m real 1. 1% GDP real 1. 6% RENT real 1. 5% Historical (avg; [80% CI]) R 2 Sample 1. 0% [-0. 3% ; 1. 8%] 1. 2% [-0. 3% ; 3. 5%] 1. 4% [-0. 7% ; 3. 6%] 1. 9% [-0. 5% ; 4. 2%] 1. 2% [-2. 0% ; 5. 6%] Inf: 57. 2% rf: 91. 2% 1994 -2009 1975 -2008 1966 -2008 1972 -2008 70. 4% 62. 7% Modelled macro economy is plausible… ➢ ➢ Key figure Sim. Historical (avg; [80% CI]) Source NCF return 4. 42% 4. 40% [2. 41% ; 6. 40%] IAZI SPB® 2000 -2008 Vacancy 3. 91% [0. 00% ; 18. 66%] IAZI SPB® 2000 -2008 …and applied valuation approach is accurate, i. e. represents the historical stochastic property behaviour as well as the market valuations of office properties Motivation Data Methodology Empirical Results 8 ERES Conference 2009 July 24 -27, Stockholm

Results § The interest rate sensitivity of a typical office property, embedded in an

Results § The interest rate sensitivity of a typical office property, embedded in an average macroeconomic environment is § § equal to 13. 1% and associated with a standard deviation of 6% § Main determinants of interest rate sensitivity § State of the macroeconomic environment (level of interest rates, inflation, GDP growth, steepness of term structure) § Property’s risk premium and remaining lifetime § Office properties provide a fairly good hedge against changes in the short term interest rates 9 Motivation Data Methodology Empirical Results ERES Conference 2009 July 24 -27, Stockholm

Appendix

Appendix

A 1. Traditional Duration Estimates Source: www. pascalroussel. net § Macaulay-Duration (present value weighted

A 1. Traditional Duration Estimates Source: www. pascalroussel. net § Macaulay-Duration (present value weighted time until the receipt of the CF) § Modified Duration (% change in value) § Lead to a Duration of real estate of roughly 20 years, or 20 % § Are based on 3 basic assumptions 1. Flat term structure 2. Parallel shift of the term structure only, i. e. no rotation 3. Cash flows do not change when interest rates change 11 ERES Conference 2009 July 24 -27, Stockholm

Level of risk free interest rates A 2. Swiss Term Structures since 01/1999 low

Level of risk free interest rates A 2. Swiss Term Structures since 01/1999 low stdev high stdev Time to maturity 12 ERES Conference 2009 July 24 -27, Stockholm

A 3. Description of the Approach § Inflation possible simulation results from AR(2) model

A 3. Description of the Approach § Inflation possible simulation results from AR(2) model (with structural break in mean inflation rate in 19941) inflation price stability (SNB) Because time dummy was most significant for this year (p-value = 0. 0593) within a pre-specified range of possible break dates ranging from 1993 up to 2000. According to time series plot, during 1993 and 2000 Swiss inflation as well as its volatility declined. Additionally, Switzerland joined the Breton Woods institutions in 1993, while at the beginning of 2000 Switzerland abandoned the monetary targeting in favour of a new policy framework based on explicit definition of price stability as the SNB’s overriding long term goal. 1) 13 ERES Conference 2009 July 24 -27, Stockholm

A 3. Description of the Approach § Short term interest rates Historical comparision result

A 3. Description of the Approach § Short term interest rates Historical comparision result from one simulation run 14 ERES Conference 2009 July 24 -27, Stockholm

A 3. Description of the Approach § Interest curve Level of interest rates %

A 3. Description of the Approach § Interest curve Level of interest rates % 3. 1 -2. 8 =0. 3 Interest curve acc. to model Interest curve after interest rate shock by +0. 5% Interest curve march 2009 0. 7 -0. 2 =0. 5 time to maturity 15 ERES Conference 2009 July 24 -27, Stockholm

A 3. Description of the Approach § Simulated time series 16 ERES Conference 2009

A 3. Description of the Approach § Simulated time series 16 ERES Conference 2009 July 24 -27, Stockholm