Liquidity and real estate asset pricing: a pan-European study

2014 ◽  
Vol 7 (1) ◽  
pp. 59-86 ◽  
Author(s):  
Alexander Scholz ◽  
Stephan Lang ◽  
Wolfgang Schaefers
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Asset Pricing ◽  
Real Estate ◽  
Stock Returns ◽  
Systematic Risk ◽  
Time Series Regression ◽  
Content Type ◽  
Market Factors ◽  
The Impact

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.

The diverging role of the systematic risk factors: evidence from real estate stock markets

2015 ◽  
Vol 33 (1) ◽  
pp. 81-106 ◽  
Author(s):  
Stephan Lang ◽  
Alexander Scholz
Keyword(s):  
Risk Factors ◽  
Time Series ◽  
Asset Pricing ◽  
Real Estate ◽  
Systematic Risk ◽  
Content Type ◽  
Risk Return ◽  
Systematic Risk Factors ◽  
Relationship Of

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.

Does asset liquidity matter? Evidence from real estate stock markets

2015 ◽  
Vol 8 (3) ◽  
pp. 220-242 ◽  
Author(s):  
Alexander Scholz ◽  
Karim Rochdi ◽  
Wolfgang Schaefers
Keyword(s):  
Asset Pricing ◽  
Real Estate ◽  
Risk Premium ◽  
Investment Strategy ◽  
Time Series Regression ◽  
Underlying Asset ◽  
Content Type ◽  
Low Degree ◽  
Asset Liquidity ◽  
The Impact

Purpose – The purpose of this paper in this context is to examine the impact of asset liquidity on real estate equity returns, after taking well-documented systematic risk factors into account. Due to their unique characteristics, real estate equities constitute an inherently low degree of underlying asset liquidity. Design/methodology/approach – Following the Fama-French time-series regression approach, the authors extend the conventional asset pricing model by a real estate-specific asset liquidity factor (ALF), using a sample of 244 real estate equities. Findings – The results, based on monthly data for the period 1999-2012, reveal that asset liquidity is a relevant pricing factor which contributes to explaining return variations in real estate equity markets. Accordingly, investors expect a risk premium from listed real estate companies with a low degree of asset liquidity, which is especially the case for companies facing financial constraints and during economic downturns. Furthermore, an investment strategy exploiting differences in the underlying asset liquidity yields considerable average excess returns of upto 8.04 per cent p.a. Practical implications – Considering the findings presented in this paper, asset liquidity should receive special attention from investors, as well as from the management boards of listed real estate companies. While investors who ignore the magnitude of asset liquidity may systematically misprice real estate equities, management can influence the firm’s cost of capital by adjusting the underlying asset liquidity. Originality/value – This is the first study to examine the role of an ALF in a real estate asset pricing framework.

scholarly journals Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1732
Author(s):  
Mohammad Enamul Hoque ◽  
Soo-Wah Low
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Exchange Rate ◽  
Asset Pricing ◽  
Stock Returns ◽  
Oil And Gas ◽  
Negative Relationship ◽  
Downside Risk ◽  
Total Risk ◽  
Pricing Framework

This study employs a mean semi-variance asset pricing framework to examine the influence of risk factors on stock returns of oil and gas companies. This study also examines how downside risk is priced in stock performance. The time-series estimations expose that market, size, momentum, oil, gas, and exchange rate have significant impacts on oil and gas stock returns, but effects are heterogeneous depending on an individual stock. The two-stage cross-section estimations provide new insights about investors’ risk-return trade-off when facing downside risks. The results show that downside risk exposures to market, momentum, oil, and exchange rate factors are negatively priced in the Malaysian oil and gas stocks. This implies that investors are penalized for their downside exposure to these risk factors, and such inference is consistent with the risk preference explanation of prospect theory. Liquefied natural gas (LNG) is the only risk factor found to be positively priced in the returns of oil and gas stocks. Additionally, we find a negative relationship between LNG factor and total risk. This suggests that as the risk exposure to LNG increases, the total risk decreases, implying that the LNG risk factor is an idiosyncratic risk and not a systematic risk factor. Such interpretation is consistent with the correlation result, which shows no association between LNG and the market risk factor.

Firm location and systematic risk: the real estate channel

2020 ◽  
Vol 19 (3) ◽  
pp. 387-409
Author(s):  
Xiang Gao ◽  
John Topuz
Keyword(s):  
Asset Pricing ◽  
Real Estate ◽  
Abnormal Returns ◽  
Systematic Risk ◽  
Local Economy ◽  
Firm Risk ◽  
Firm Level ◽  
Content Type ◽  
Land Availability ◽  
Real Estate Prices

Purpose This paper aims to investigate whether the cyclicality of local real estate prices affects the systematic risk of local firms using a geography-based measure of land availability as a quasi-exogenous proxy for real estate price cyclicality. Design/methodology/approach This paper uses the geography-based land availability measure as a proxy for the procyclicality of real estate prices and the location of a firm’s headquarters as a proxy for the location of its real estate assets. Four-factor asset pricing model (market, size, value and momentum factors) is used to examine whether firms headquartered in more land-constrained metropolitan statistical areas have higher systematic risks. Findings The results show that real estate prices are more procyclical in areas with lower land availability and firms headquartered in these areas have higher systematic risk. This effect is more pronounced for firms with higher real estate holdings as a ratio of their tangible assets. Moreover, there are no abnormal returns to trading strategies based on land availability, consistent with stock market betas reflecting this local real estate factor. Research limitations/implications This paper contributes to the literature on local asset pricing factors, the collateral role of firms’ real estate holdings and the co-movement of security prices of geographically close firms. Practical implications This paper has important managerial implications by showing that, when firms decide on the location of their buildings (e.g. headquarters building, manufacturing plant and retail outlet), the location’s influence on systematic risk should be part of the decision-making process. Originality/value This paper is among the first to use a geography-based measure of land availability to study whether the procyclicality of local real estate prices influences firm risk independent of the procyclicality of the local economy. Thus, both the portfolio formed and firm-level analyses provide a more direct evidence of the positive relation between the procyclicality of local real estate prices and firm risk.

scholarly journals The information content of US stock market factors

2020 ◽  
Vol 37 (2) ◽  
pp. 323-346
Author(s):  
Mohammed M. Elgammal ◽  
Fatma Ehab Ahmed ◽  
David G. McMillan
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Information Content ◽  
Predictive Power ◽  
Output Growth ◽  
Economic Conditions ◽  
Content Type ◽  
Economic Information ◽  
Market Factors ◽  
The Impact

Purpose The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth. Design/methodology/approach Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth. Findings The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime). Research limitations/implications The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior. Practical implications Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models. Originality/value This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.

International Real Estate Review

2012 ◽  
Vol 15 (1) ◽  
pp. 107-126
Author(s):  
Hongyan Du ◽  
◽  
Yongkai Ma ◽  
Keyword(s):  
Real Estate ◽  
Stock Returns ◽  
Positive Impact ◽  
Abnormal Returns ◽  
Systematic Risk ◽  
Stock Performance ◽  
Significant Difference ◽  
Corporate Real Estate ◽  
Systematic Risks ◽  
The Impact

This paper attempts to study the relationships among corporate real estate (CRE), capital structure and stock performance of China¡¦s non-real estate firms, including the bidirectional relationships between debt ratio (DR) and corporate real estate ratio (CRER), the impact of CRER on stock performance, and whether this impact differs across firms with different debt levels. The results show that for the overall sample, DR has a positive effect on CRER, while CRER negatively affects DR. CRER has no significant positive impact on the abnormal returns of stocks, and even decreases those for firms in the information industry. However, it can significantly reduce the systematic risks of stock returns. Moreover, we find that CRER has no significant effect on abnormal returns regardless of the amount of debt level that a firm has, and there is no significant difference between the effects of CRER on abnormal returns for firms with different levels of debt. On the other hand, the effect of CRER on systematic risk is significantly negative for firms in the low debt group, and insignificantly positive for firms in the high debt group. The CRER of lower debt firms can significantly reduce much more systematic risk than that of the high debt firms.

The risk of real estate ownership: evidence from German equities

2015 ◽  
Vol 8 (2) ◽  
pp. 107-129 ◽  
Author(s):  
Karim Rochdi
Keyword(s):  
Risk Factors ◽  
Real Estate ◽  
Risk Premium ◽  
Balance Sheet ◽  
Systematic Risk ◽  
Considerable Proportion ◽  
Content Type ◽  
Corporate Real Estate ◽  
Systematic Risk Factors ◽  
Estate Ownership

Purpose – This paper aims to investigate the repercussions and impact of corporate real estate on the returns of non-real-estate equities in a time-series setting. While the ownership of real estate constitutes a considerable proportion of most listed firms’ balance sheet, in the existing literature, whether or not the benefits outweigh the risks associated with corporate real estate, is the subject of controversy. Design/methodology/approach – The role of corporate real estate ownership in the pricing of returns is examined, after taking well-documented systematic risk factors into account. Employing a data sample from 1999 to 2014, the conditions and characteristics faced by firms with distinct levels of corporate real estate holdings are identified and analyzed. Findings – The findings reveal that corporate real estate intensity indeed serves as a priced determinant in the German stock market. Among other results, the real-estate-specific risk factor shows countercyclical patterns and is particularly relevant for companies within the manufacturing sector. Practical implications – The findings provide new insights into the interpretation of corporate real estate and expected general equity returns. Thus, the present analysis is of particular interest for investors, as well as the management boards of listed companies. Originality/value – To the best of the author’s knowledge, this is the first paper to investigate the ownership of corporate real estate as a priced factor for German equities, after accounting for the well-documented systematic risk factors, namely, market (market risk premium), size (small minus big) and book-to-market-ratio (BE/ME) (high minus low).

The role of efficiency in capital asset pricing: a research on Nasdaq technology sector

2020 ◽  
Vol 46 (11) ◽  
pp. 1479-1493
Author(s):  
Hakan Aygoren ◽  
Emrah Balkan
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Explanatory Power ◽  
Efficiency Factor ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Content Type ◽  
The Impact ◽  
Three Factor

PurposeThe aim of this study is to investigate the role of efficiency in capital asset pricing. The paper explores the impact of a four-factor model that involves an efficiency factor on the returns of Nasdaq technology firms.Design/methodology/approachThe paper relies on data of 147 firms from July 2007 to June 2017 to examine the impact of efficiency on stock returns. The performances of the capital asset pricing model (CAPM), Fama–French three-factor model and the proposed four-factor model are evaluated based on the time series regression method. The parameters such as the GRS F-statistic and adjusted R² are used to compare the relative performances of all models.FindingsThe results show that all factors of the models are found to be valid in asset pricing. Also, the paper provides evidence that the explanatory power of the proposed four-factor model outperforms the explanatory power of the CAPM and Fama–French three-factor model.Originality/valueUnlike most asset pricing studies, this paper presents a new asset pricing model by adding the efficiency factor to the Fama–French three-factor model. It is documented that the efficiency factor increases the predictive ability of stock returns. Evidence implies that investors consider efficiency as one of the main factors in pricing their assets.

Is there a priced risk factor associated with conservatism?

2016 ◽  
Vol 17 (5) ◽  
pp. 545-561 ◽  
Author(s):  
Kerstin Lopatta ◽  
Felix Canitz ◽  
Christian Fieberg
Keyword(s):  
Risk Factor ◽  
Stock Returns ◽  
Design Methodology ◽  
Systematic Risk ◽  
Factor Loading ◽  
Related Factor ◽  
Cross Sectional ◽  
Content Type ◽  
Conditional Conservatism ◽  
The Cross

Purpose García Lara et al. (2011) argue that there is a conservatism-related priced risk factor in US stock returns. To put this to the test, the authors aim to analyze whether the conditional conservatism effect comes from the loading on a conditional conservatism-related factor-mimicking portfolio (systematic risk) or the conservatism characteristic itself. Design/methodology/approach The authors form characteristic-balanced portfolios from dependent sorts of stocks on the firm’s degree of conservatism and the firm’s loading on the conservatism-related factor-mimicking portfolio as proposed by Daniel and Titman (1997) and Davis et al. (2000). Findings The tests indicate that it is the conditional conservatism characteristic rather than the factor loading that explains the cross-sectional differences in average stock returns. Consequently, they do not find evidence for a conservatism-related priced risk factor. Originality/value This finding suggests that investors misvalue the conservatism characteristic and casts doubt on the rational risk explanation as proposed by García Lara et al. (2011).

Examining the sentiment-return relationship in European real estate stock markets

2015 ◽  
Vol 8 (1) ◽  
pp. 24-45 ◽  
Author(s):  
Stephan Lang ◽  
Wolfgang Schaefers
Keyword(s):  
Asset Pricing ◽  
Real Estate ◽  
Stock Returns ◽  
Stock Markets ◽  
Investor Sentiment ◽  
High Sensitivity ◽  
Investment Strategy ◽  
Data Set ◽  
Content Type ◽  
Low Sensitivity

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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