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Return measurement for Direct Real Estate Investments PowerPoint Presentation
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Return measurement for Direct Real Estate Investments

Return measurement for Direct Real Estate Investments

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Return measurement for Direct Real Estate Investments

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  1. ERES 2009 Conference Stockholm, June 24thAndreas Gohs: An evaluation of the quality of unsmoothing procedures to estimate true market returns from appraisal-based returns

  2. Return measurement for Direct Real Estate Investments • Investors‘ decisions about capital allocation in direct real estate, shares and/or bonds depend on considerations about expected returns and risk structures of assets and comovements between asset returns. • Shares and bonds are standardised products; for example, for the most traded shares there are new quotations on the exchanges every few minutes; quotations are results of auctions. • Properties are heterogenous; transactions of individual properties are typically observable only unregularly and seldom (sometimes every 20-30 years). • Appraisers estimate regularly true market values of properties.

  3. Return measurement for Direct Real Estate Investments • While indices for shares are based on transaction prices, indices for direct investments in commercial real estate are typically based on appraisal values. • Different value concepts make comparisons of the return/risk-structures of different assets more difficult.

  4. Deviations between appraiser values and true market values • Returns of appraisal-based indices seem to be smoothed compared to their underlying true market returns. • In the literature a few reasons are identified why the standard deviations of appraisal-based returns could be biased towards zero: • so called “smoothing phenomena“

  5. Smoothing phenomena • Appraisal smoothing: • Appraisers try to estimate true market value of an individual property but have only incomplete information about it. • Appraisal value is a weighted average of the transaction prices of comparable properties, transacted in the immediate past, and past property appraisals:V(t) = a * T(t) + (1-a) * V(t-1), 0<a<1. • Appraiser will put more weight on “a“ the less there is variation in the transaction prices of comparable properties. • Appraiser will put more weight on “1-a“ the less the valuations varied in the past. • Temporal lag, smoothing of volatility.

  6. Smoothing phenomena • Non-synchronous appraisal: • Index values are typically reported for the end of periods (that means a point in time), but appraisers are allowed to estimate property values in a time span before the end. • Calculated index value is the result of the information about the underlying real estate market inherent in individual property values at different points in time. • Temporal lag, smoothing of volatility

  7. Smoothing phenomena • Stale-appraisal and saisonality of reappraisals: • In the US-American NCREIF Property Index not all properties are reappraised every period; for some properties past appraisal values are reported in a current period. • Since in the fourth quarter there are more reappraisals of properties in the index sample than in the first three quarters of every year, the index suggests that there are higher changes of values in the underlying market in the fourth quarters. • Temporal lag, smoothing of volatility, autocorrelation of time lag four.

  8. What are unsmoothing procedures? • In the literature several “unsmoothing“ procedures to estimate “more true“ returns from appraisal-based index returns are suggested. • Most unsmoothing procedures are similar in that they try to correct the autocorrelation structure of the reported returns. • Unsmoothing procedures differ in assumptions about the underlying property market, the appraiser behaviour and the index construction process. • Evidence about the quality of an unsmoothing procedure: Plausibility of the index values of unsmoothed return series in historical time points.

  9. Empirical study about the impact of smoothing phenomena on index return volatility • Monte Carlo-Simulation: Introduction of smoothing phenomena in return series. • Comparison of the volatilities and other statistics of the manipulated and original return series. • Evaluation of different unsmoothing procedures by a comparison of the unsmoothed manipulated and original return series.

  10. First empirical results • Standard deviation of the manipulated return series in percent of the standard deviation of the original return series • for different types of smoothing phenomena and • Different original return series.

  11. Thank you!