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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.

Purpose – The purpose of this chapter is to examine whether or not the Capital Asset Pricing Model (CAPM) reasonably describes the return generating process on the Ghanaian Stock Exchange using monthly return data of 19 individual companies listed on the Exchange during the period January 2000 to December 2009.

Methodology/approach – We follow a methodology similar to Jensen (1968) time series approach. Parameters are estimated using OLS. This study is designed to measure beta risk across different times by following the time series approach. The betas of the individual securities are estimated using time series data of the excess return version of the CAPM.

Findings – Our test results show that although market beta contributes to the variation in equity returns in Ghana, its contribution is not as significant as predicted by the CAPM, and in some cases very weak. Our results also reject the strictest form of the Sharpe–Lintner CAPM, but we found positive linear relationship between equity risk premium and market beta. Instead, our evidence uphold the Jensen (1968) and Jensen, Black, and Scholes (1972) versions of the CAPM.

Research limitations/implications – This study is limited to the single-factor CAPM. Future studies will extend the test to include both size and BE/ME fundamentals and factors relating to P/E ratio, momentum and liquidity.

Practical implications – Our results will make corporate managers to be cautious when using CAPM as a basis to determine cost of equity for investment appraisal purposes, and fund managers when evaluating asset and portfolio performance.

Originality/value – The CAPM is applied to individual securities instead of portfolios, since the model was developed using information on a single security.

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.

This study aims to investigate the risk-return trade-off in the Indian equity market at both the aggregate equity market level and in the cross-sections of stock return using alternative risk measures.

The study uses weekly and monthly data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019. The study evaluates the risk-return trade-off at the aggregate equity market level using the value-weighted and the equal-weighted broader portfolios. Eight different risk proxies belonging to the conventional, downside and extreme risk categories are considered to analyse the cross-sectional risk-return relationship.

The results show a positive equity premium on the value-weighted portfolio; however, the equal-weighted portfolio of these stocks shows an average return lower than the return on the 91-day Treasury Bills. The inverted size premium mainly causes this anomaly in the Indian equity market as the small stocks have lower returns than big stocks. The study presents a strong negative risk-return relationship across different risk proxies. However, under the subsample of more liquid stocks, the low-risk anomaly regarding other risk proxies becomes moderate except the beta-anomaly. This anomalous relationship seems to be caused by small and less liquid stocks having low institutional ownership and higher short-selling constraints.

The findings have important implications for investors, managers and practitioners. Investors can incorporate the effects of different highlighted anomalies in their investment strategies to fetch higher returns. Managers can also use these findings in their capital budgeting decisions, resource allocations and other diverse range of direct and indirect decisions, particularly in emerging markets such as India. The findings provide insights to practitioners while valuing the firms.

The study is among the earlier attempts to examine the risk-return trade-off in an emerging equity market at both the aggregate equity market level and in the cross-sections of stock returns using alternative measures of risk and expected returns.

The purpose of this paper is to measure the risk perception of the employees in respect of equity shares, from the perspective of elements of marketing mix and to ascertain the degree of influence of elements of marketing mix on equity‐related risk perception.

Primary data based on the interview schedule were collected from the employees of Oil India Limited and various tables prepared. For analysis of data, Cronbach's alpha and Friedman test analysis were employed.

Out of the four elements of marketing mix considered in the study, the degree of influence of price driven measure of risk perception is highest and others in order are product, promotion and place driven measure of risk perception, respectively.

The paper is the first of its kind and hence original in nature.

The purpose of this paper is to show that subordinated debt regulatory proposals assume that transactions in the secondary market of subordinated debt can attenuate moral hazard on the part of management if secondary market prices are informative signals of the risk of the institution. Owing to the proprietary nature of dealer prices and the liquidity of secondary transactions, the practical value of information provided by subordinated debt issues in isolation is questionable.

A multivariate dynamic risk signal is proposed that combines fluctuations in equity prices, subordinated debt and senior debt yields. The signal is constructed as a coincident indicator that is based in a time series model of yield fluctuations and equity returns. The extracted signal monitors idiosyncratic risk of the intermediary because yields and equity returns are filtered from market conditions. It is also predictable because it is possible to construct a leading indicator based almost entirely on spreads to Treasury.

The signal for the Bank of America and Banker's Trust is implemented. For Bank of America, the signal points mainly to two events of uprising risk: January 2000 when the bank disclosed large losses in its bond and interest‐rate swaps portfolios; and November 2000 when it wrote off $1.1 billion for bad loans. For Banker's Trust, the signal points to October/November 1995 after the filing of federal racketeering charges against Banker's Trust; and October 1998 when the bank suffered substantial losses from its investments in emerging markets.

The signal is a complementary instrument for regulators and investors to monitor and assess in real time the risk profile of the financial institution.

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.

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.

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.

Although this study sheds some light on investor sentiment in European real estate stock markets, further research could usefully concentrate on alternative sentiment proxies.

This is the first study to disentangle the relationship between investor sentiment and European real estate stock returns.

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.