Non‐Normal Real Estate Return Distributions by Property Type in the UK

Abstract

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD U.K. database over the period 1981 to 2003 than normally distributed risk models. This finding mirrors results in the U.S. and Australia using identical methodology. Real estate investment risk is heteroskedastic, but the characteristic exponent of the investment risk function is constant across timeyet it may vary by property type. Asset diversification is far less effective at reducing the impact of non-systematic investment risk on real estate portfolios than in the case of assets with normally distributed investment risk. The results therefore indicate that multi-risk factor portfolio allocation models based on measures of investment codependence from finite-variance statistics are ineffective in the real estate context.

Tail Parameters of Stable Distributions Using One Million Observations of Real Estate Returns from Five Continents

“…They found that the stable distributions capture the return structure much better than normal distributions. Follow-up studies in this area have been provided by Graff et al (1997), Young et al (2006), Young (2008), Richter et al (2011), and Young and Brown (2012), among others. Based on McCulloch (1986), studies until 2011 used quantile-regression approaches to estimate the parameters.…”

Revisiting Non-normal Real Estate Return Distributions by Property Type in the U.S.

“…Comparing the Characteristic Exponent results of the earlier Australian study with the current updated U.S. study, the statistical estimate of Characteristic Exponent of U.S. returns together with a 95% confidence interval around the value is 1.434±0.022 versus the estimate of The means are shown in Table 2 for purposes of completeness, but will not be needed for discussion or analysis in the body of this article a =99% confidence [statistically significant confidence of non-Normality α≠2.0) or skewness (β≠0) Australian returns of 1.588±0.068, not statistically identical as reported earlier when the U.S. estimate was somewhat higher with greater standard error. Young et al (2006) examined U.K. property returns in the IPD database over the 1981 to 2003 period, again using the same methodology as Young and Graff (1995). The 269,853-property sample size of the U.K. data set dwarfs both the U.S. and Australian samples.…”

“…has been applied to Australian and United Kingdom institutional properties in Graff et al (1997) and Young et al (2006) respectively. Thus, similarities in real estate return distributions can be assessed across three English-speaking countries.…”

Ripple effect and contagious effect in the US regional housing markets

“…Most studies have indicated that the distribution of housing returns is non-normal (e.g., Myer and Webb 1994;Young and Graff 1995;Graff et al 1997;Young et al 2006). When the return distribution does not follow a normal distribution, previous studies have proposed using a Student's t distribution for modeling real estate returns (e.g., Bond and Patel 2003).…”