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The Journal of Real Estate Finance and Economics

Erschienen in:

01.05.2009

Idiosyncratic Risk and REIT Returns

verfasst von: Joseph T. L. Ooi, Jingliang Wang, James R. Webb

Erschienen in: The Journal of Real Estate Finance and Economics | Ausgabe 4/2009

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Abstract

The volatility of a stock returns can be decomposed into market and firm-specific volatility, with the former commonly known as systematic risk and the later as idiosyncratic risk. This study examines the relevance of idiosyncratic risk in explaining the monthly cross-sectional returns of REIT stocks. Contrary to the CAPM theory, a significant positive relationship is found between idiosyncratic volatility and the cross-sectional returns. This suggests that firm-specific risk matters in REIT pricing. The regression results further show that once idiosyncratic risk is controlled for in the asset-pricing model, the size and book-to-market equity ratio factors ceased to be significant. The explanatory power of the momentum effect remains robust in the presence of idiosyncratic risk.

Vorheriger Artikel The Relative Impacts of Trails and Greenbelts on Home Price

Nächster Artikel Regional Housing Prices in the USA: An Empirical Investigation of Nonlinearity

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In addition to incomplete information, there are a number of other factors that could also attribute to why investors hold undiversified portfolios. They include market segmentation and institutional restrictions including limitations on short sales, taxes, transaction costs, liquidity, imperfect divisibility of securities (Merton 1987; p. 488)

For example, to allow for variation in beta that is unrelated to firm size, FF (1992) subdivide each size decile into ten portfolios on the basis of pre-ranking betas for individual stocks. This results in 100 size-beta portfolios.

In another study, Chaudhry et al. (2004) observe that different firm characteristics impact idiosyncratic risk depending on the time period examined.

The rise in firm-specific risk of common stocks can be attributed to two interacting factors, namely a dramatic increase in the number of new listings and a simultaneous decline in the age of the firm at IPO. Fink et al. (2005), in particular, argue that since the equity of young firms typically represents a claim on cash flows that are further into the future, it is not surprising that the idiosyncratic risk of the typical public firm has increased. Xu and Malkiel (2003) further suggest that the rising idiosyncratic volatility is attributed to more institutional ownership and high growth.

Besides size, Chaudhry et al. (2004) also observe that efficiency, liquidity and earnings variability are important determinants of idiosyncratic risk of REITs.

In addition, to ensure that the observed patterns in the volatility series are not driven by outliers, we recompute the two series by omitting 5% observations at both ends of the distribution. The time trend for the reconstructed series is similar to that observed in Fig. 2 and hence, is not reported for brevity.

Goyal and Santa-Clara (2003) find that over the period 1926–1999, idiosyncratic volatility is on average 80% of total volatility of common stocks. In comparison, Anderson et al. (2005) observe that 62% of the monthly return volatility of the NAREIT index is unrelated to any of the capital market factors, namely large cap stock, small cap growth stock, small cap value stock, bond and real estate, in their asset pricing model.

Chui et al. (2003) and Ooi etal. (2007) adopted a similar approach to examine the payoffs of REIT portfolios constructed based on the momentum- and value-effect.

Given that Figs. 2 and 3 show a countercyclical pattern, we further examine the payoff associated with adopting the idiosyncratic risk strategy in different market conditions using the portfolio sorting methodology. We sub-divide the sample period according to whether the market as represented by the NAREIT index is moving upwards or downwards. The corresponding risk-adjusted returns for the zero-cost idiosyncratic portfolio remain positive and statistically significant under both rising (0.46%) and declining market conditions (0.32%). This indicates that payoffs from the idiosyncratic risk strategy are robust to the overall performance of the market.

Although other studies have identified other factors that affect cross-sectional stock returns, such as leverage (Bhandari 1988) and earnings-price ratio (Basu 1983), FF (1992) test the joint role of market equity, book-to-market equity (BE/ME) ratio, leverage and earnings-price ratio (E/P), and conclude that the combination of market equity and book-to-market equity ratio seems to absorb the roles of leverage and E/P in average stock returns.

Following FF (1992) and Fu (2005), the smallest and largest 1% of the observations on ME, B/M and Ret (−2,−13) are set equal to the next smallest and largest values of the observations (the 0.01 and 0.99 fractiles) to avoid giving extreme observations heavy weight in the regressions.

The intuition underlying the theory is best illustrated using the following thought experiment proposed by Berk (1995): Consider a one-period economy in which all investors trade off risk and return. Assume that all firms in this economy are exactly the same size; that is, assume that the expected value of every firm’s end-of-period cashflow is the same. Since the riskiness of each firm’s cashflow is different..., the market value of each firm must also differ. Given that all firms have the same expected cashflow, riskier firms will have lower market values and so, by definition, will have higher expected returns. Thus, even though all firms are the same size, if market value is used as the measure of size, then it will predict return (p.277).

Nevertheless, we would like to point out that the three-factor model is generally more useful than the single-factor model in explaining the variation in EREIT returns and in providing stable estimates of market betas (Peterson and Hsieh 1997; Chiang et al. 2005).

For brevity reason, the estimation results are not presented here.

Note that the two sub-periods, 1990–1999 and 1996–2005, include overlapping years from 1996 to 1999 to provide sufficient length of time for the sub-period tests. Due to the substantial month-to-month variability of the parameters of the risk-return regressions, FM (1973) recommend that a longer time-period of analysis to make the t-statistic value meaningful (page 624). Consequently, subsequent studies such as Chui et al. (2003) and Ang et al. (2006) have carried out sub-period tests using at least 10 years data.

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Titel: Idiosyncratic Risk and REIT Returns
verfasst von: Joseph T. L. Ooi
Jingliang Wang
James R. Webb
Publikationsdatum: 01.05.2009
Verlag: Springer US
Erschienen in: The Journal of Real Estate Finance and Economics / Ausgabe 4/2009
Print ISSN: 0895-5638
Elektronische ISSN: 1573-045X
DOI: https://doi.org/10.1007/s11146-007-9091-1

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