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This paper aims to gain exposure to Australian real estate investment trusts (A‐REITs). Many institutional investors make use of securitised property funds as they employ experienced property professionals with specialist knowledge of underlying property fundamentals, direct property markets and the 30‐plus A‐REITs. As securitised property funds operate in a competitive environment, investment performance benchmarks are important.

To add to the familiar risk and return benchmarks, the risk adjusted performance (RAP) measure first outlined by Modigliani and Modigliani provides an additional and valuable return measure to a definite level of risk. This research selected 16 wholesale securitised property funds each with seven years of continuous quarterly total return data.

Overall a large proportion of the selected funds (14 out of 16), on average, outperformed the market benchmark return (14.53 per cent) with the worst fund marginally under‐performing the index by 0.54 per cent. In contrast, the annualised RAP measure highlighted the differences in the securitised property fund returns for a given level of risk, with a wide 12.90‐16.66 per cent range. To achieve this uniform level of risk, five securities property funds had to replace up to 21 per cent of their property portfolio with a risk‐free asset (90 day bank bills). The RAP measure also decomposes the excess returns above the benchmark. In this instance, the securitised property funds outperformance was from a mixture of active portfolio selection and simply taking on additional risk exposure.

The research demonstrated the benefits of analysing securitised property funds beyond the standard return and risk measures. The RAP approach provides a measure of return for a definite level of risk with the benchmark excess attributed to portfolio selection and additional risk. This performance information can provide valuable additional information for an astute investor.

The theory of finance is built around return and risk concepts and a basic tenet of finance is that there is a trade off between the risk and returns of assets. As such the measurement of risk goes to the very core and foundation of the theory of finance. Given that the main theories of finance have been maturing over several decades of discussion and debate, one would imagine that a concept as fundamental as the measurement of risk would be a well settled issue by now. On the contrary, the recent finance literature shows ample evidence that risk measurement and risk concepts are drawing continued scrutiny from academic researchers. This is because there are several alternative, and competing ways in which risk can be conceived of and it is not clear which of the alternative concepts is most appropriate. Each concept of risk can be measured or estimated in several ways as well. Estimation methods can be diverse in their precision. Risk measurement can be further complicated by the fact that risk is not a static feature. Risk changes over time. Whether risk changes can be modelled satisfactorily is a major challenge taken up by researchers.

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.

This paper seeks to address the question of consistency, regarding the allocation of real estate in the mixed‐asset portfolio.

To address the question of consistency the allocation of real estate in the mixed‐asset portfolio was calculated over different holding periods varying from five to 25 years. For each portfolio and holding period, the percentage of portfolios with real estate was computed, as was the average real estate allocation in the optimum solution. Then, the risk and return differences between the two efficient frontiers, with and without real estate, were calculated to estimate real estate's marginal impact on portfolio performance.

First, the results suggest strongly that real estate has possessed the attribute of consistency in optimised portfolios. Second, the benefits from including real estate in the mixed‐asset portfolio tend to increase as the investment horizon is extended. Third, the position of real estate changes across the efficient frontier from its return enhancing ability to its risk‐reducing facility. Finally, the results show that the gain in return from adding real estate to the mixed‐asset portfolio is typically less compared with the reduction in portfolio risk.

The results highlight a number of issues in relation to the role of direct real estate within a mixed‐asset framework. In particular, the rationale behind the inclusion of real estate in the mixed‐asset portfolio depends on the length of the holding period of the investor and their position on the efficient frontier.

The study examines the attractiveness of direct real estate in the context of mixed‐asset portfolio.

A stylized fact in finance literature is the belief in positive relationship between ex ante return and risk. Hence, a rational investor, by utility preference axiom can only consider committing fund in asset which promises commensurate higher return for higher risk. Questions have been asked as to whether this holds true across securities, sectors and markets. Empirical evidence appears less convincing, especially in developing markets. Accordingly, the author investigates the nature of reward for taking risk in the Nigerian Capital Market within the context of individual assets and markets.

The author employed ex post design to collect weekly stock prices of firms listed on the Premium Board of Nigerian Stock Exchange for period 2014–2022 to attempt to answer research questions. Data were analyzed using a unique M Vec TGarch-in-Mean model considered to be robust in handling many assets, and hence portfolio management.

The study found that idea of risk-expected return trade-off is perhaps more general than as depicted by traditional finance literature. The regression revealed that conditional variance and covariance risks reveal minimal or no differences in sign and sizes of coefficients. However, standard errors were also found to be large suggesting somewhat inconclusive evidence of existence of defined incentive structure for taking additional risk in the market.

In terms of choice of methodology and outcomes, this research adds substantial value to body of knowledge. The adapted multivariate model used in this paper is a rare approach especially for management of portfolios in developing markets. Remarkably, the research found empirical evidence that positive risk-expected return trade-off, as known in mainstream literature, is not supported especially using a typical developing country data.

Stock selection models often use momentum and analysts’ expectation data. We find that earnings forecast revisions and direction of forecast revisions are more important than analysts’ forecasts in identifying mispriced securities. Investing with expectations data and momentum variables is consistent with maximizing the geometric mean and Sharpe ratio over the long run. Additional evidence is revealed that supports the use of multifactor models for portfolio construction and risk control. The anomalies literature can be applied in real-world portfolio construction in the U.S., international, and global equity markets during the 1998–2009 time period. Support exists for the use of tracking error at risk estimation procedures.

While perfection cannot be achieved in portfolio creation and modeling, the estimated model returns pass the Markowitz and Xu data mining corrections test and are statistically different from an average financial model that could have been used to select stocks and form portfolios. We found additional evidence to support the use of Arbitrage Pricing Theory (APT) and statistically-based and fundamentally-based multifactor models for portfolio construction and risk control. Markets are neither efficient nor grossly inefficient; statistically significant excess returns can be earned.

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.

As cryptocurrencies continue to gain viability as an asset class, institutional investors and publicly traded firms have started taking investment positions in digital currencies. What firms may not be considering, however, is the effect these assets may have on their risk profiles. This study aims to (1) measure the effect of cryptocurrencies on the risk and return characteristics of publicly traded companies; (2) decipher the motives behind holding cryptocurrencies as an asset class; and (3) determine whether one reason for holding is more effective than another. To conduct this research, the four largest publicly traded holders of cryptocurrency as well as four of the most prominent cryptocurrencies are explored.

The cross-sectional analysis approach has been used to analyze the daily returns, volatility, betas and Sharpe Ratios of firms during periods without cryptocurrency strategies and during periods with cryptocurrency strategies.

The impact of the cryptocurrency asset class on common stock performance and corporate disclosures are documented. The importance of risk disclosures on cryptocurrency holdings is emphasized: Firms must better inform their stakeholders through comprehensive disclosures in financial statements. Firms utilize cryptocurrencies for various reasons such as treasury management tools or as direct sources of income. Consequently, the impact on returns and risks varies substantially.

To the best of the authors’ knowledge, this is one of the first studies on cryptocurrency investments in the treasury departments of publicly traded companies. The study contributes to the literature by extracting relevant information regarding company risk reporting and cryptocurrency risk at firms. The conclusions also promote firm transparency with detailed reporting of cryptocurrency holding risks.

Many studies have shown that from a theoretical and empirical point of view, downside risk-based measures of risk are better than the traditional ones. Despite academic appeal and practical implications, downside risk has not been thoroughly examined in markets outside developed country markets. Using downside beta as a measure of downside risk, this study examines the relationship between downside beta and stock returns in Indian equity market, an emerging market with unique investor, asset and market characteristics.

This is an empirical study done by using ranked portfolio return analysis and regression analysis methodologies.

The study results show that downside risk, as measured by downside beta, is distinctly priced in the Indian equity market. There is a direct positive relationship between downside beta and contemporaneous realized returns, indicating a premium for downside risk. Downside risk carries a higher weightage than upside potential in the aggregate return of the stock portfolios. Downside beta is a better measure of systematic risk than conventional market beta and downside coskewness.

The empirical results support the adoption of downside beta in practice and provide a case for replacing traditional beta with downside beta in asset pricing applications, trading and investment strategies, and capital allocation decision-making.

This is one of the first in-depth studies examining downside beta in Indian equity markets using a broad sample of individual stock returns covering a wide time range of 22 years. To the best of our knowledge, this study is the first one to compare downside beta and downside coskewness using individual stock data from the Indian equity market.

The purpose of this paper is to investigate whether downside-risk measures help to explain why households largely refrain from investing in Exchange Traded Funds that replicate broad and internationally diversified market indices, so-called XTFs, although studies frequently recommend to do so.

The paper analyzes whether evaluating risk in terms of downside-risk measures which reflect households' interpretation of risk closer than the standard deviation (SD) of returns, yields less risk-return-enhancements, and thus, fewer incentives for households to invest in XTFs. Household portfolios are compiled by combining stylized portfolio compositions that involve multiple asset classes and German households' security holdings. The data set covers the period from January 2014 to December 2016 and includes 47,388 securities.

The results indicate that none of the downside-risk measures can help to explain the reluctance of households to invest in XTFs. On the flip side, the results show that all stylized household portfolios can enhance the risk-return position from employing XTFs, regardless of the underlying risk measure. This supports the advice to invest in XTFs and extends it upon households that evaluate risk in terms of downside-risk.

To the best of the authors' knowledge, this study is the first to investigate risk-return-enhancements from XTFs while simultaneously considering various downside-risk measures and multiple asset classes of household portfolios.