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Previous studies have shown that stock returns bear a premium for downside risk versus upside potential. We develop a new risk measure which scales the traditional CAPM beta by the ratio of the upside beta to the downside beta, thereby incorporating the effects of both upside potential and downside risk. This “modified” beta has substantial explanatory power in standard asset pricing tests, outperforming existing measures, and it is robust to various alternative modeling and estimation techniques.

Real estate investment trust (REIT) stocks are well known for limited management discretion in investment, financing, and payout policies, implying little information asymmetry between informed and uninformed investors. Besides, due to the renowned illiquidity and complexity of physical real estate markets, investors may be heterogeneously informed. The authors aim to investigate these arguments using REIT panel data from 1993 to 2010.

The authors simultaneously investigate the effects of heterogeneous information (PSOS) and information asymmetry (ADJPIN) on REIT excess returns by estimating panel data regressions controlling for both firm- and time-fixed effects.

The results confirm that heterogeneous information (PSOS) is significantly and positively associated with REIT excess returns while information asymmetry (ADJPIN) is insignificant when controlling for other variables well known for affecting REIT excess returns.

The effects of information asymmetry (ADJPIN) and heterogeneous information (PSOS) on REITs excess returns are rarely simultaneously discussed in the related literature, especially from the perspectives of limited managerial discretions, regulated dividend policy, and underlying asset liquidity (physical real estate markets). The results confirm the heterogeneous information arguments. Besides, the heterogeneous information (PSOS) effects become stronger when leverage and dividend yield are higher. Finally, the above effects of PSOS and ADJPIN on REIT excess returns are also robust during the real estate market growth period (2001-2008).

Using a unique dataset of ownership structure for all stocks listed on the Stockholm Stock Exchange in Sweden, we examine different degrees of institutional holdings in Swedish firms during the bear market of 2000 to 2002. We find that examination by institutional investor domicile reveals that both Swedish and foreign institutions increase their equity holdings, although the increase by foreign institutions is proportionately higher, (individuals reduce their equity holdings). We find evidence that foreign and domestic institutional investors exhibit different preferences for excess returns and standard deviations in excess returns when we control for firm size; excess return is associated with changes in foreign institutional holdings while higher standard deviation in excess return is associated with the change in domestic institutional holdings. Both types of institutions are sensitive to liquidity and trading factors, causing portfolio realignment.

The purpose of this paper is to provide an analysis of the relationship between expected risk premia on property stocks and some major macroeconomic risk factors as reflected in the general business and financial conditions

Employs a three‐step estimation strategy (principal component analysis, GARCH (1,1) and GMM) to model the macroeconomic risk variables (GDP growth, INDP growth, unexpected inflation, money supply, interest rate and exchange rate) and relate them to the first and second moments on property stock excess returns of four major markets, namely, Singapore, Hong Kong, Japan and the UK. Macroeconomic risk is measured by the conditional volatility of macroeconomic variables.

The expected risk premia and the conditional volatilities of the risk premia on property stocks are time‐varying and dynamically linked to the conditional volatilities of the macroeconomic risk factors. However there are some disparities in the significance, as well as direction of impact in the macroeconomic risk factors across the property stock markets. Consequently there are opportunities for risk diversification in international property stock markets.

Results help international investors and portfolio managers deepen their understanding of the risk‐return relationship, pricing of macroeconomic risk as well as diversification implications in major Asia‐Pacific and UK property stock markets. Additionally, policy makers may play a role in influencing the expected risk premia and volatility on property stock markets through the use of macroeconomic policy.

From the early 1980s until the late 1990s the term structure of interest rates in Chile was usually downward sloping, particularly for long maturities. We postulate that the explanation is behind liquidity premium of the term structure of interest rates. Based upon a parsimonious theoretical model, we show that the sign of liquidity premium depends on both expected return and risk.

For our sample period 1983–1999, investors were willing to hold long-term assets even though their return was relatively lower. This appears to be a consequence of indexation, which reduced risk of long-term bonds as their return was linked to past inflation.

This study aims to investigate whether the zero-investment portfolio strategy generates higher excess returns for all listed companies in the Stock Exchange of Thailand (SET) or ESG100 stocks. The study period is from January 2016 to December 2020, a total of 60 months. The dividend yield is employed for categorizing the stock into value and growth stocks. The strategy of buying value stocks and short-selling growth stocks is then applied. The results show that investing using the zero-investment portfolio strategy can generate higher returns in an investment portfolio that consists of ESG100 stocks than in an investment portfolio that consists of all stocks in the SET. The optimal holding periods for investing in portfolios that consist of stocks in the SET are 6 months, 9 months, and 12 months, and the optimal holding periods for a portfolio that consists of ESG100 stocks is 6 months. To explain excess returns of stocks in the SET, the Fama and French (2015) five-factor model is employed. There is no relation between risk factors and excess returns for the holding period of 6 months and 12 months. However, excess return is found to have a negative relation with the market risk premium factor for a 9-month holding period. The excess returns of ESG100 stocks are also inversely correlated with investment factors for a holding period of 6 months.

The purpose of this paper is to examine long‐term return of new China collectible stamps after their issuance and how stamp characteristics affect the return.

The authors construct a model to analyze the determinants of stamps' long‐term return and test their hypotheses empirically in a sample of 1,201 sets of Chinese collectible stamps issued between 1949 and 2008.

The paper finds Chinese stamps provide decent returns for collectors in terms of exceeding comparable one‐year savings rates. Among factors affecting annual excess returns of Chinese stamps, variables related to usage are the most important; quantity issued has significantly negative impact on returns of early stamps, but its coefficient has weak economic implications and it is not significant for BianNian stamps issued in more recent years. In general, variables related to topic have weak influence on stamp returns, but the topics about the most significant events of China in recent years have huge impact on stamp returns; in addition, variables related to design and printing can influence stamp returns to some extent.

Overall, the results reveal that variables related to usage are the most important determinants of long‐term stamp return.

There have been fierce disputes among stamp collectors about how stamp features affect returns. Nevertheless, no systematic empirical studies exist about the issue. This paper sheds light on the disputes by providing the first piece of empirical evidence.

Moreover, existing studies of stamps treat them as one asset, but often ignore different characteristics within the group. This paper systematically investigates the influence of stamp characteristics to stamp return, and thus fills the caveat in the literature.

This paper aims to address the question: What is the distribution of value (in pounds) created in a sample of domestic takeovers in the United Kingdom from 2013 to 2020 among acquirer and target stockholders?

The author employs a traditional event study methodology to calculate the percentage excess returns of companies on the announcement date. These returns are then converted into pound-denominated excess returns using the companies' market capitalizations. This allows the author to estimate the synergies of the mergers and acquisitions (M&As) and how they are allocated between acquirers and targets. This innovative transformation from percentage to pound excess returns establishes a new ratio methodology for addressing the paper's objective.

This paper reveals that in UK takeovers, 40 percent of the synergies in pounds are allocated to the stockholders of acquiring companies, while 60 percent go to the stockholders of target companies. In other words, acquirers retain a significant portion—more than half—of the synergies generated in these domestic deals. This original finding is statistically significant at the one percent level and strongly contradicts the hypothesis that acquirers, at best, merely break even.

The evidence that UK takeovers distribute value gains nearly equally between domestic deal parties challenges the enduring conventional insight in the M&A literature. This conventional wisdom suggests that the value created by business combinations is entirely distributed to target company stockholders. Consequently, this reexamination may have broader implications, offering an alternative perspective on the motives behind business combinations. This perspective differs from the “managerial hubris hypothesis,” which aligns with the prevailing conventional insight but receives limited support in the original finding reported here.

The purpose of this paper is to examine the sources of direct real estate portfolio returns and their relative performance against Investment Property Databank (IPD) benchmark returns. Active property management consists of the concepts of property transaction execution and operational management, which can be classified as the main drivers of excess return sources.

Using a sample of three different portfolios managed by two institutional investors, the paper is able to estimate the relevant factors of active property management on annual excess returns for commercial and residential property sectors via a panel regression technique.

Empirical evidence shows that property‐specific effects exhibit significant sources of excess returns, but property management cannot be identified as their main driver. Furthermore, the sources of excess returns do not differ significantly across sectors; when controlled for property age and size, it is found that their influence is rather limited.

Information about the drivers of excess returns and their variations among property types may lead to superior investment decisions during portfolio rebalancing, and thus promote more efficient capital allocation. Information about return factors, i.e. about property and operational management, can substantially improve property selection and market timing in the asset allocation process. Hence, investors basing their property investment strategies on the impact of selected return factors could enhance the risk‐adjusted performance of their property portfolios.

This paper aims to contribute to the existing literature by identifying and quantifying the excess return sources of a given property portfolio over a predefined benchmark. Due to the lack of property‐related data, there is only limited research on the sources of direct property returns, such as property characteristics or active property management. The authors explore three main questions in this paper. First, they examine sources of excess returns over a benchmark index for several property sectors. Second, they analyze whether the drivers of excess returns vary significantly across these sectors. Third, they determine to what extent excess property returns are influenced by the “economic age” and “rentable area” of a building.

We address an interesting case – the predictability of excess US asset returns from macroeconomic factors within a flexible regime-switching VAR framework – in which the presence of regimes may lead to superior forecasting performance from forecast combinations. After documenting that forecast combinations provide gains in predictive accuracy and that these gains are statistically significant, we show that forecast combinations may substantially improve portfolio selection. We find that the best-performing forecast combinations are those that either avoid estimating the pooling weights or that minimize the need for estimation. In practice, we report that the best-performing combination schemes are based on the principle of relative past forecasting performance. The economic gains from combining forecasts in portfolio management applications appear to be large, stable over time, and robust to the introduction of realistic transaction costs.