Purpose – Understanding the pricing of real estate equities is a central objective of real estate research. This paper aims to investigate the impact of liquidity on European real estate equity returns, after accounting for well-documented systematic risk factors. Design/methodology/approach – Based on risk factors derived from general equity data, the authors extend the Fama-French time-series regression approach by a liquidity factor, using a pan-European sample of 272 real estate equities. Findings – The empirical results indicate that liquidity is a significant pricing factor in real estate stock returns, even after controlling for market, size and book-to-market factors. In addition, the authors detect that real estate stock returns load predominantly positively on the liquidity risk factor, suggesting that real estate equities tend to behave like illiquid common equities. These findings are underpinned by a series of robustness checks. Running a comparative analysis with alternative factor models, the authors further demonstrate that the liquidity-augmented asset-pricing model is most appropriate for explaining European real estate stock returns. Research limitations/implications – The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets. Originality/value – This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.
Purpose – The risk-return relationship of real estate equities is of particular interest for investors, practitioners and researchers. The purpose of this paper is to examine, in an asset pricing framework, whether the systematic risk factors play a significantly different role in explaining the returns of listed real estate companies, compared to general equities. Design/methodology/approach – Running the difference test of the Fama-French three-factor and the liquidity-augmented asset pricing model, the authors analyze the effect of the systematic risk factors related to market, size, BE/ME and liquidity in a time-series setting over the period July 1992 to June 2012. By applying the propensity score matching (PSM) algorithm, the authors bypass the “curse of dimensionality” of traditional matching techniques and identify a comparable control sample of general equities, in terms of the relevant firm characteristics of size, BE/ME and liquidity. Findings – The empirical results indicate that European real estate equity returns load significantly differently on the size, value and liquidity factor, while the influence of the market factor seems to be equivalent. In addition, the authors find an economically and statistically significant underperformance of European real estate equities, after accounting for the diverging role of systematic risk factors. Running the conditional time-series regression, the authors further reveal that these findings are predominately caused by the divergent risk-return behavior of real estate equities in economic downturns. Practical implications – Due to the diverging role of the systematic risk factors in pricing real estate equities, the authors provide evidence of potential diversification benefits for investors and portfolio managers. Originality/value – This is the first real estate asset pricing study to dissect the unique risk-return relationship of real estate equities by employing propensity score matching.
Purpose – Recent studies in the field of behavioral finance have highlighted the importance of investor sentiment in the return-generating process for general equities. By employing an asset pricing framework, this paper aims to evaluate the performance of European real estate equities, based on their degree of sentiment sensitivity. Design/methodology/approach – Using a pan-European data set, we classify all real estate equities according to their sentiment sensitivity, which is measured relative to the Economic Sentiment Indicator (ESI) of the European Commission. Based on their individual sentiment responsiveness, we form both a high- and low-sensitivity portfolio, whose returns are included in the difference test of the liquidity-augmented asset pricing model. In this context, we analyze the performance of sentiment-sensitive and sentiment-insensitive real estate equities with a risk-adjusted perspective over the period July 1995 to June 2012. Findings – While high-sensitivity real estate equities yield significantly higher raw returns than those with low-sensitivity, we find no evidence of risk-adjusted outperformance. This indicates that allegedly sentiment-driven return behavior is in fact merely compensation for taking higher fundamental risks. In this context, we find that sentiment-sensitive real estate equities are exposed to significantly higher market risks than sentiment-insensitive ones. Based on these findings, we conclude that a sentiment-based investment strategy, consisting of a long-position in the high-sensitivity portfolio and a short-position in the low-sensitivity one, does not generate a risk-adjusted profit. Research limitations/implications – Although this study sheds some light on investor sentiment in European real estate stock markets, further research could usefully concentrate on alternative sentiment proxies. Originality/value – This is the first study to disentangle the relationship between investor sentiment and European real estate stock returns.
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