Random Disaggregate Appraisal Error in Commercial Property: Evidence from the Russell-NCREIF Database

Previous studiesIn order to test the usefulness of real estate as a portfolio diversifier, price indexes are needed to compute holding period returns. Whereas price indexes are readily available for financial assets, this is not the case for real estate owing to the lack of transactions, the scarcity of data and the heterogeneity of assets. Several methods are used to construct price indexes for real estate. These include appraisal-based series, indexes constructed with securitized data, indices of the average of transactions prices, hedonic models and the repeat sales method. Although the first two methods have serious limitations, they have been widely used in empirical studies as they are easier to use and less data intensive. Very few studies have used hedonic indexes in order to test the attractiveness of real estate as an asset class. Indexes constructed from averages of transactions prices are usually discarded as the biases are too serious. To date, no study has made use of data derived from the repeat sales method to investigate the opportunity of including real estate in mixed-asset portfolios. Thus almost all studies have used either appraisal-based indexes or securitized data, while few have relied on the hedonic approach.To construct efficient portfolios, it is necessary to have information on the average return and risk of each asset class, as well as on the correlation coefficients between each pair of assets. As could be expected, the results vary quite substantially depending on what data series is used for real estate. When appraisal-based indexes are used, very low risk levels are found for real estate. Ibbotson and Siegel (1984), for instance, report a standard deviation of 3.7 per cent for US real estate for the period 1947-1982, compared with a standard deviation of 17.5 per cent for stocks and 9.7 per cent for bonds. Moreover, correlations between real estate returns and the returns on financial assets are usually found to be negative. Hartzell et al. (1986) report a correlation of -0.12 between real estate and stocks and a correlation of -0.39 between real estate and bonds. When such parameters are used to construct efficient portfolios, real estate is heavily represented in mixed-asset combinations. Webb and Rubens (1987), for instance, find that real estate should have constituted 83 per cent of a US portfolio over the period 1947-1959, 98 per cent over the period 1960-1972 and 91 per cent over the period 1973-1984. Similar results have been reported for the UK. MacGregor and Nanthakumaran (1992), for instance, find that the optimal weight for real estate goes up to 88 per cent in low return and low risk portfolios for the period 1977-90.These results, however, are not convincing as several authors have documented the appraisal smoothing which leads to downwardly biased standard deviations (Geltner, 1993;Geltner et al., 1994). When securitized data are used for the USA, the return and risk parameters of real estate are similar to those of common stocks (see Ross and Zisler, 1991). Moreov...

Section: Previous Studiesmentioning

confidence: 90%

mentioning

confidence: 99%

EUROPEAN PAPER: Diversification of Swiss portfolios with real estate, Results based on a hedonic index

Hoesli¹,

Hamelink²

1996

“…These results, however, are not convincing as several authors have documented the appraisal smoothing which leads to downwardly biased standard deviations (Geltner, 1993;Geltner et al, 1994). When securitized data are used for the USA, the return and risk parameters of property are similar to those of common stocks, and the correlation between property and common stocks is high (Brueggeman et al, 1989;Ross and Zisler, 1991).…”

Section: Literature Reviewmentioning

confidence: 98%

An examination of the role of Geneva and Zurich housing in Swiss institutional portfolios

Hoesli

Hamelink

1997

2012),"Wealth effect, credit price effect, and the inter-relationships between Hong Kong's property market and stock market", Property Management, Vol. 30 Iss 3 pp. 255-273 http://dx.If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.

“…While this model of appraisal procedure is simplified, it seems reasonable, especially for the simple world of Oz, and, I argue, it also captures the essence of much actual appraisal in the real world as far as the issues we are focusing on here are concerned[14].…”

Section: Reconsidering Optimal Appraisal Procedures: a Simulation Analysismentioning

confidence: 99%

The use of appraisals in portfolio valuation and index construction

Geltner

1997

Self Cite

Provides a review of basic appraisal and statistical principles combined with a simple numerical simulation. Suggests two main directions in which the appraisal profession should move. First, because public stock exchanges tend to be more informationally efficient than private property markets, appraisal accuracy can be improved by making increased quantitative use of the information in the share prices of publicly‐traded property companies. Second, it must be recognized that the valuation techniques which are optimal for individual property appraisal are suboptimal for the mass appraisal of aggregate portfolios or indexes of property market values. Suggests that regression‐based techniques based purely on transaction prices may be superior for this latter function.