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The purpose of this paper is to investigate the pricing of European real estate equities. The study examines the main drivers of real estate equity returns and determines whether loadings on systematic risk factors – the excess market return, small minus big (SMB), HIGH minus low (HML) – can explain cross‐sectional return differences in unconditional as well as in conditional asset pricing tests.

The paper draws upon time‐series regressions to investigate determinants of real estate equity returns. Rolling Fama‐French regressions are applied to estimate time‐varying loadings on systematic risk factors. Unconditional as well as conditional monthly Fama‐MacBeth regressions are employed to explain cross‐sectional return variations.

Systematic risk factors are important drivers of European real estate equity returns. Returns are positively related to the excess market return and to a value factor. A size factor impacts predominantly negatively on real estate returns. The results indicate increasing market integration after the introduction of the Euro. Loadings on systematic risk factors have weak explanatory power in unconditional cross‐section regressions but can explain returns in a conditional framework. Beta – and to a lesser extent the loading on HML – is positively related to returns in up‐markets and negatively in down markets. Equities which load positively on SMB outperform in down markets.

The implementation of a liquidity or a momentum factor could provide further evidence on the pricing of European real estate equities.

The findings could help investors to manage the risk exposure more effectively. Investors should furthermore be able to estimate their cost of equity more precisely and might better be able to pick stocks for time varying investment strategies.

This is the first paper to examine the pricing of real estate equity returns in a pan‐European setting.

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.

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.

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.

The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets.

This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.

Real estate is the last major asset class without liquid derivatives markets. The reasons for that are not fully known or understood. Therefore, the purpose of this paper is to better understand the main factors that influence the propensity of commercial real estate investors in the UK to employ property derivatives.

The research methodology that was chosen for this research is grounded theory which, in its original form, goes back to Glaser and Strauss (1967). A total of 43 interviews were conducted with 46 real estate professionals in the UK from property investment management firms (investing directly or indirectly in real estate), multi-asset management firms, real estate investment trusts, banks, and brokerage and advisory firms, among others.

The research results show 29 factors that influence the propensity of direct and indirect real estate investors in the UK to employ property derivatives. Out of the 29 factors, the current research identified 12 factors with high-explanatory power, 6 with a contributing role and 11 with low explanatory power. Moreover, factors previously discussed in the literature are tested and assessed as to their explanatory power. The focus of this paper is on those factors with high-explanatory power. From the research data, three main reasons have been identified as the sources of investor reluctance to trade in property derivatives. The first and main reason is related to a mismatch between motivations of property investment managers and what can be achieved with the instruments. The second reason, which ties in with the first one, is a general misunderstanding as to the right pricing technique of property derivatives. Finally, the third reason is a general lack of hedging demand from the investor base owing to the long investment horizons through market cycles.

The research contributes to the literature on property derivatives in various ways. First, it extends the literature on market hurdles in property derivatives markets by testing and extending the hurdles that were proposed previously. Second, the research shows that the existing pricing models need to be extended in order to account for the risk perception of practitioners and their concerns with regard to liquidity levels.

For both theory and practice, the research has shown some limitations in using property derivatives for purposes such as creating index exposure or hedging. Another contribution, in this case to practice, is that this study provides a clearer picture as to the reasons that keep property investment managers away from using property derivatives.

The research results indicate that liquidity per se is not a universal remedy for the problems in the market. In addition to the need for improving the understanding of the pricing mechanism, practitioners should give more thought to the notion of real estate market risk and the commensurate returns that can reasonably be expected when they take or reduce it. This implies that property index futures currently do not price like those on any other investable asset class.

This study is the first to examine the role of idiosyncratic risk in the pricing of European real estate equities. The capital asset pricing model predicts that in equilibrium, investors should hold the market portfolio. As a result, investors should only be rewarded for carrying undiversifiable systematic risk and not for diversifiable idiosyncratic risk. The study is adding to the growing body of countering studies by first examining time trends of idiosyncratic risk and subsequently the pricing of idiosyncratic risk in European real estate equities. The paper aims to discuss these issues.

The study analyses 293 real estate equities from 16 European capital markets over the 1991-2011 period. The framework of Fama and MacBeth is employed. Regressions of the cross-section of expected equity excess returns on idiosyncratic risk and other firm characteristics such as beta, size, book-to-market equity (BE/ME), momentum, liquidity and co-skewness are performed. Due to recent evidence on the conditional pricing of European real estate equities, the pricing is also investigated using the conditional framework of Pettengill et al. Either realised or expected idiosyncratic volatility forecasted using a set of exponential generalized autoregressive conditional heteroskedasticity models are employed.

The initial analysis of time trends in idiosyncratic risk reveals that while the early 1990s are characterised by both high total and idiosyncratic volatility, a strong downward trend emerged in 1992 which was only interrupted by the burst of the dotcom bubble and the 9/11 attacks along with the global financial and economic crisis. The largest part of total volatility is idiosyncratic and therefore firm-specific in nature. Simple cross-correlations indicate that high beta, small size, high BE/ME, low momentum, low liquidity and high co-skewness equities have higher idiosyncratic risk. While size and BE/ME are priced unconditionally from 1991 to 2011, both measures of idiosyncratic risk fail to achieve significance at reasonable levels. However, once conditioned on the general equity market or real estate equity market, a strong positive relationship between idiosyncratic risk and expected returns emerges in up-markets, while the opposite relationship exists in down-markets. The relationship is robust to firm-specific factors and a series of robustness checks.

The results show that ignoring the conditional relationship between idiosyncratic risk and returns might result in the false realisation that idiosyncratic risk does not matter in the pricing of risky (real estate) assets.

This study is the first to examine the role of idiosyncratic risk in the pricing of European real estate equities. The study reveals differences in the pricing of European real estate equities and US REITs. The study highlights that ignoring the conditional relationship between idiosyncratic risk and returns might result in the false realisation that idiosyncratic risk does not matter in the pricing of risky assets.

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.

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.

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.

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.

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.

The financial and economic turmoil that resulted from the Global Financial Crisis (GFC), included a marked increase in the volatility in real estate markets. Property asset prices were impacted by the real economy and market sentiment, particularly concerning the determination of risk. In an economic downturn, the perception of investment risk becomes increasingly important relative to overall total returns, and thus impacts on yields and performance of assets. In a recovery phase, and particularly within an environment of historically low government bonds, risk and return compete for importance. The aim of this paper is to assess the interrelationships and impacts on pricing between real estate risk, yield modelling outcomes and market sentiment in selective European city office markets.

This paper specifically considers the modelling of commercial property pricing in relation to the appetite for risk in the financial markets. The paper expands on previous work by determining a specific measure of risk pricing in relationship to changing financial market sentiment. The methodology underpinning the research specifically examines the scope for using national and international risk pricing within specific real estate markets in Europe.

This paper addresses whether there is a difference between the impact of risk on the pricing of real estate in international versus regional cities in Europe. The analysis, therefore, determines which city centre office markets in Europe have been most impacted by globalisation including the magnitude on real estate prices and market volatility. The outcome of the paper provides important insights into how changes in risk preferences in the international capital markets have driven and continues to drive yield movements under different market conditions.

The paper considers the driving forces which have led to the volatile movements of yields, emanating from the GFC.

This paper considers the property market effects on pricing of commercial real estate and the drivers in selected European cities.

The outcome of the paper provides important insights into how changes in risk preferences in the international capital markets have driven and continue to drive the yield movements in different real estate markets in Europe.

In the light of past financial and economic turmoil, there has been a marked increase in the volatility in real estate markets. This has impacted on the pricing of property assets, partly through market sentiment and particularly concerning risk. It also limits modelling accuracy model accuracy. The purpose of this paper is to create a new variable and model to enhance analysis of what drives real estate yields incorporating market sentiment to risk.

This paper specifically considers the modelling of property pricing within a volatile economic environment. The theoretical context begins by analysing the relationship between property yields and government bonds. The analytical context then moves on to specifically include a measurement of risk which stresses its role and importance in investment markets since the Global Financial Crisis. The model thus incorporates macroeconomic and real estate data, together with an international risk multiplier, which is calculated within the paper.

The paper finds the use of measurements of market sentiment and risk are more powerful tools for modelling yields than previous techniques alone.

This is an initial paper outlining the creation of sentiment and risk measurements in the financial market and showing an example of its application to a commercial real estate market. The implication is that this could add a major new explanatory variable to modelling of yields.

The paper highlights the importance of risk in the pricing of commercial real estate, over and above normal variables. It highlights how this can help explain over and undershooting of yields within commercial real estate which would be of great importance in the investment world.

This paper attempts to explicitly measure market sentiment, pricing of risk and how this impacts real estate pricing.

The home is a substantial investment for most individual investors but the assessment of risk and return of residential real estate has not been well explored yet. The existing real estate pricing literature using a CAPM-based model generally suggests very low risk and unexplained excess returns. However, many academics suggest the residential real estate market is unique and standard asset pricing models may not fully capture the risk associated with the housing market. The purpose of this paper is to extend the asset pricing literature on residential real estate by providing improved CAPM estimates of risk and required return.

The improvements include the use of a levered β which captures the leverage risk and Lin and Vandell (2007) Time on Market risk premium which captures the additional liquidity risk of residential real estate.

In addition to presenting palatable risk and return estimates for a national real estate index, the results of this paper suggest the risk and return characteristics of multiple cities tracked by the Case Shiller Home Price Index are distinct.

The results show higher estimates of risk and required return levels than previous research, which is more consistent with the academic expectation that housing performs between stocks and bonds. In contrast to most previous studies, the authors find residential real estate underperforms based on risk, using standard financial models.

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.

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.

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.

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.

This is the first study to examine the role of an ALF in a real estate asset pricing framework.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.