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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.

This paper aimed to examine the return/risk performance of direct and indirect real estate (listed property stock) in the Nigerian real estate market and analyzed the short-term integration between the two classes of real estate assets. It also established whether investors could achieve diversification benefits by combining both assets in a portfolio.

The data utilized comprised annual returns on direct real estate calculated from the rental and capital values of 226 direct commercial properties obtained from property valuers in Lagos, Nigeria, for a period of January 1999-December 2014. The appraisal-based direct real estate returns were de-smoothed using the Geltner (1993) procedure. The annual returns of indirect real estate were also computed from the transactions of listed property stock on the Nigerian Stock Exchange for the study period. The return-risk profiles were also broken down into short- and medium-term sub-periods, comprising 3, 5, 8 and 12 years to reflect the level of volatility in the market, whereas the nature of the short-term relationship between the two real estate assets classes was tested using Granger causality technique.

The results revealed that listed property stock performed better than unsmoothed direct real estate on a risk-adjusted performance basis. The performance profile, however, varies over the different sub-periods considered. Short-term integration analysis showed that there was no bidirectional relationship between direct and listed property stock, implying diversification and risk reduction possibilities in combining both assets with other asset classes in a domestic asset portfolio. Overall, the results confirm the findings of previous study that listed property stocks return is segmented from the direct real estate market upon which its pricing and trading in the stock market are based.

The conclusion of the study suggests that investors could achieve improved performance by investing in listed property stocks than direct real estate in the Nigerian real estate market. The inclusion of both assets in a domestic mixed-asset portfolio could also be expected to offer diversification and risk reduction benefits.

This is one of the few studies that examine the short-run integration between direct real estate and listed property stocks with a focus on an emerging African market.

The paper examined the long-run relationship between real estate equity (property listed stock) and non-real estate equity (common stock) in the Nigerian capital market and established the integration between the investments. The paper aims to discuss these issues.

The data collected comprised quarterly returns on property listed stock and All Share Index for the period of January 1999-December 2011. The calculated quarterly returns of the investments were subjected to the Philip-Person unit root test after which the integration between the investments was analysed using the Johansson integration test.

The results showed that real estate equity performed better the non-real estate equity but with corresponding higher risk level. Also, real estate equity had a slightly lower performance when compared with non-real estate equity on return/risk ratio basis. The findings showed that property listed stock (real estate equity) was integrated with common stock or non-real estate equity and suggest that the Nigerian listed property stock, by nature, was similar to REITs. This result negates the belief that property listed stock's returns are integrated with direct real estate market and are often influenced by the returns of the underlying direct real estate assets.

The paper implied that while investors could consider investing in real estate equity and earn better return than investing in common equity in the Nigerian capital market, the inclusion of both in a domestic portfolio could be expected to bring little or no diversification benefit.

The paper is one of the few attempts at assessing the long-run relationship between property listed stock as a form of real estate equity and non-real estate equity and especially from African emerging market perspective.

The purpose of this paper is to investigate and compare the extreme behavior of securitized real estate and stock market returns as well as their value‐at‐risk (VaR) dynamics in international investing. Extreme value theory using the block maxima method is applied to ten securitized real estate and equity market indices representing Asian, European and North American markets.

The paper models the maxima and minima of all return series within the extreme value theory (EVT) framework and derive the VaR estimates. It then compares the VaR estimates derived from the EVT and the normal distribution and investigates the impact of clustered returns on the VaR estimates. Finally, both the conventional standard deviation measure and VaR method are conducted to evaluate and compare the impact of the Asian financial turmoil on the real estate and stock market risk profiles.

Evidence shows that Asian real estate and equity maxima and minima return series are characterized by a fat‐tailed Fréchet distribution. The frequency and severity of extreme Asian real estate returns are greater than their European and North American counterparts. Securitized real estate markets are riskier than the broader stock markets before and during the Asian financial turmoil. In contrast, many stock markets become riskier after the financial crisis with their VaRs higher than the equivalent VaR estimates for the real estate series.

Knowledge about real estate market returns exhibit extreme behavior can help investors and fund managers understand the distribution of real estate market returns better and obtain potentially more accurate real estate return forecasts.

International real estate portfolio risk management should include both extreme risks and standard deviations. Accordingly, global investors should be even more cautious in formulating their diversification strategies since gains from diversification can be reduced significantly by the severity of extreme return levels.

The paper characterizes the distribution of extreme returns for a broad spectrum of international securitized real estate markets from three continents. The extreme value investigation is also conducted for broader stock markets corresponding to the individual real estate markets. The July 1997 turmoil that occurred in Asian financial markets provides interesting exploratory opportunities within which this paper estimates and compares the extreme market risk with the conventional standard deviation measure.

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.

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.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Real estate investment has been generally accepted as a value-adding proposition for a portfolio investor. Such an impression is not only shared by investment professionals and financial advisors but also appears to be supported by an overwhelming amount of research in the academic literature. The benefits of adding real estate as an asset class to a well-diversified portfolio are usually attributed to the respectable risk-return profile of real estate investment together with the relatively low correlation between its returns and the returns of other financial assets. By using the regime-switching technique on an extensive historical dataset, we attempt to look for the statistical evidence for such a claim. Unfortunately, the empirical support for the claim is neither strong nor universal. We find that any statistically significant improvement in risk-adjusted return is very much limited to the bullish environment of the real estate market. In general, the diversification benefit is not found to be statistically significant unless investors are relatively risk averse. We also document a regime-switching behavior of real estate returns similar to those found in other financial assets. There are two distinct states of the real estate market. The low-return (high-return) state is characterized by its high (low) volatility and its high (low) correlations with the stock market returns. We find this kind of dynamic risk characteristics to play a crucial role in dictating the diversification benefit from real estate investment.

Examines the investment performance of Singapore real estate and property stocks over the past 25 years. Evaluations using coefficient of variation (CV), Sharpe index (SI) and time‐varying Jensen abnormal return index (JI) suggest that real estate outperformed property stocks on a risk‐adjusted basis. Results also indicate that risk‐adjusted investment performance for residential properties remained superior to performance for other real estate types and property stocks. Further analysis using time‐varying JI reveals that the excess return performance of property stocks could differ significantly from that of direct properties, and performance of property stock led real estate market performance. Finally, the performance implications arising from the study are evaluated.

The purpose of this study is to investigate the interactive relationships between oil price shocks and the Nigeria stock market.

The paper applied the multivariate vector auto‐regression that employed the generalized impulse response function and the forecast variance decomposition error.

Empirical evidence reveals that stock market returns exhibit insignificant positive response to oil price shocks but reverts to negative effects after a period of time depending on the nature of the oil price shocks. The results are similar even with the inclusion of other variables. Also, the asymmetric effect of oil price shocks on the Nigerian stock returns indices is not supported by statistical evidences.

This is the first study to examine the dynamic linkages between stock market behaviour and oil price shocks in Nigeria.