Real estate is not normal: A fresh look at real estate return distributions

Young, Michael; Graff, Richard A.

doi:10.1007/bf01096940

Cited by 139 publications

(76 citation statements)

References 28 publications

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“…For example, Myer and Webb (1993) found non-normal evidence for individual U.S. REITs. For direct property in the U.S., Young and Graff (1995) found that during the study period between 1980 and 1992, there was no evidence to support the normality assumption for Russell-NCREIF annual returns in any calendar year. Similar methodology was adopted by when examining Australian commercial real estate returns and where similar results were demonstrated for rejecting normality assumptions.…”

Section: Literature Reviewmentioning

confidence: 84%

“…However, these studies employed variance as a risk measure where it is bound by several strict assumptions such as (a) return distributions are normally distributed and (b) all investors dislike both extreme high and low returns. The normality assumption in return distributions has been debated and challenged by extensive empirical studies (Young and Graff, 1995;Lu and Mei 1999). Furthermore, the second assumption is not intuitively appealing.…”

Section: Introductionmentioning

confidence: 99%

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Momentum Profits in Australian Listed Property Trusts

Lee

Reed

Robinson

2007

Pacific Rim Property Research Journal

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Section: Literature Reviewmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Momentum Profits in Australian Listed Property Trusts

Lee

Reed

Robinson

2007

Pacific Rim Property Research Journal

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“…Real estate returns are known for displaying non normal return. This has long been demonstrated by Myer and Webb (1994) or Young and Graff (1995 In this article we concentrate particularly on direct real estate value at risk and propose the use of Cornish Fisher expansion to improve traditional model.…”

Section: C) Motivationmentioning

confidence: 90%

Cornish-Fisher expansion for real estate value at risk

2012

Proceedings of the 19th Annual European Real Estate Society Conference - Edinburgh, Scotland

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Value at risk is a convenient and popular risk measurement tool. It represents the maximum potential loss on a specific portfolio of financial assets given a specific time horizon and a confidence interval. Principally value at risk is used in finance for risk management, financial reporting and capital requirement. In direct real estate, the calculation of this risk measurement is still rare even if it is now common to compute and disclose it in numerous other fields of finance. Indeed nowadays, financial institutions are facing the important task of estimating and controlling their exposure to market risk following a scope of new regulations such as Basel II, Basel III, NAIC or Solvency II. In this context, financial institutions use internal models for estimating their market risk. The purpose of this paper is to investigate the possibility to use Cornish-Fisher expansion to assess real estate value at risk. We show how Cornish-Fisher approximation can quickly give more accurate measurements than traditional methodologies. In addition, practitioners can find here a methodology to assess quickly value at risk without too many loss of relevancy due to normal hypothesis which is relaxed in our proposal.After a review of literature on value at risk and of the existing methodologies, the paper describes the Cornish-Fisher expansion, the assumptions required to apply it and how the expansion is used to compute value at risk. Then, we apply the proposed model to a UK dataset index and compare the results obtained with those obtained with Gaussian assumption.

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“…However, most financial assets, including real estate equities, are not characterized by a normal distribution. A number of studies such as Webb (1993, 1994), Young and Graff (1995), Lizieri and Satchell (1997), Lu and Mei (1998), Bond and Patel (2003), Liow and Sim (2005), Young, Lee and Devaney (2006), Young (2008), Lee Robinson and Reed (2008), as well as Yang and Chen (2009) demonstrate that the density function of real estate returns does not exhibit normality, but often reveals significant skewness and fat tails. This makes the CAPM unlikely to hold, such that the measurement of systematic risk requires more than covariance with the market return.…”

Section: Introductionmentioning

confidence: 99%