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The recent financial crisis provides an opportunity to examine the management of local government investment pools (LGIPs). This study examines asset concentration of current LGIPs to find if investment practices of LGIPs are consistent with the objective of prudent management of public funds. Using cross-sectional data of 72 LGIP portfolios, exploratory factor analysis was conducted. Findings suggest that there are five underlying factors that describe the investment practices of current LGIP portfolios. The findings also suggest that LGIP investment managers considered return on investment when they chose investment instruments. However, LGIP managers put more focus on the safety of investment when they allocated assets in their portfolio.

This paper aims to examine the Chinese investment anomaly and dissect it from a perspective of rational expectation framework.

Characteristic-based sorting and Fama–MacBeth two-stage cross-sectional regression are adopted to test the relationship between corporate investment and expected returns in both portfolio and individual stock levels. Under the framework of pricing kernels, an investment-based common risk factor is constructed to test the role of risk played in the negative investment-return relationship. Moreover, a Markov regime switching model is adopted to investigate the time-varying risk premium across market regimes.

Empirical results provide ample evidence showing that there is a negative relationship between investment and expected returns in the Chinese stock market. The new investment-based risk factor is found to capture the return differences across characteristic-based portfolios. In addition, risk premium of the new risk factor is not only statistically positive throughout the sample period, but also has an asymmetry that is higher during market downturn but lower under bull market.

This paper merely tests the hypotheses derived from rational school.

Investment strategies based on characteristic-sorted portfolios should be adjusted to different market regimes.

First, this paper provides comprehensive empirical results by adopting different methodologies for investigating the investment anomaly in China. Second, an investment-based factor is constructed specifically for the Chinese stock market for the first time. Finally, this is the first paper to investigate the asymmetric risk premium across the Chinese bear and bull regimes by using a multivariate Markov regime switching model.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

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.

Referring to “behavioural finance” and “normative model” theories, this study explores the relative significance of behavioural heuristic biases in the investment decisions of real estate investment trusts (REITs) when compared with the conventional normative decision factors, with an ultimate aim to identify the significant behavioural factors that should be avoided to ensure rational asset acquisitions and market efficiency.

A triangulation approach was adopted. Qualitative multiple case studies were conducted, with four cases selected from Australian and New Zealand REITs across the industry, to identify what normative and behavioural finance factors are involved in investment decisions. This formed the basis for the subsequent expert review survey to explore how significant the behavioural factors were manifested in the judgement when compared with the normative factors.

Three out of four theoretical behavioural factors manifested themselves in the investment decisions: investor sentiment, anchoring factors and overconfidence. The overall impact of these three behavioural factors was that they were as significant as normative factors in investment decisions. The heuristic availability of information was found to have no significant effect on experienced REIT fund managers.

The findings were based on four multiple cases and an expert review survey of six frontline fund managers, which form a baseline upon which further research can be conducted to widen the scope of research to cover all REITs in Australasia so that the results can become more robust to benefit the entire market in the region.

As behavioural factors are significant in the decision-making process, REIT fund managers should raise awareness to avoid the significant behavioural factors identified, in particular investor sentiment, which was found to be the most significant one.

This study confirms the relative significance of behavioural factors in property investment decisions within the context of Australasian REITs and alerts fund managers to the ways they should follow to ensure rational investments and market efficiency. It also extends the scale of existing studies to cover not only Australia but also New Zealand for the benefit of the entire Australasian market.

The primary objective of the study is to discover the most prominent criteria and sub-criteria among environmental issues, social dimensions and corporate governance factors that may impact individual equity investors' investment decisions.

The present study collected data from 438 individual equity investors from the North Indian region. To achieve the objectives of the study, a fuzzy analytic hierarchy process (Fuzzy AHP) was applied. The key considerations of the study were environmental, social and governance (ESG) factors.

The governance criterion was discovered to be the most significant factor influencing individual equity investors' investment decisions among the three ESG factors, followed by environmental criteria, while social criteria were shown to be the least influential.

The present study solely looked at ESG issues as drivers of stock investors' investment decisions. In the current world, however, many other factors, including behavioral biases, accounting information, ownership structure and fundamental analysis, can have a substantial influence on investors' investment decisions.

The study's findings widen the theoretical contribution in the field of responsible investment by asserting how ESG factors influence investors' investment decisions in the equity market. From a practical standpoint, this study applies to retail and institutional investors, portfolio managers, financial advisors, market regulators, corporations and society at large.

To the best of authors knowledge, no attempt has been made to prioritize the ESG issues that impact the investment decisions of individual equity investors. Ergo, this study contributes to the existing literature on socially responsible investment.

This study aims to address research gaps by constructing critical success factors (CSFs) in the context of green hotel investment in Taiwan. It contributes to the domain knowledge to cultivate Taiwan’s green hotel development in the future.

The authors secured 20 prominent green hotel management/owners/architects as crucial informants. The first stage used the Delphi method to collect expert opinions (i.e. CSFs) and the second stage applied the analytic hierarchy process to analyze the importance of CSFs.

The results show that the “financial investment benefits” is considered the most crucial success factor for the green hotel investment. However, to balance long-term economic development with environmental impact, green hotel investors should consider other aspects of the research to sustain future financial performance returns.

Further studies should consider regional characteristics to accommodate geographic/social differences and hotel types to explore possible CSFs for the green hotel investment. The authors suggest including panel experts from government officials and prominent scholars to represent a broader but different view on subject matters. They also offer implications for investors’ governmental policies, hotelier cognition and customer-related aspects in green hotel investment.

This study built a hierarchical framework based on the CSF concept by evaluating priority differences between hotel management and hotel owners/architects. Such findings help investors’ effective decision-making through considering factors’ relative importance for green hotel investments.

This paper aims to investigate the explanatory power of the Fama-French five-factor model and compares it to the other asset pricing models. In addition, the paper examines the contributions of two additional factors: profitability and investment factor. The authors test the alternative four-factor models.

The authors use stock returns data of BSE-500 listed firms for the Indian market, an emerging market, from 1999 to 2020, thus covering the post-Asian crisis and pre- and post-financial crisis (2007–2008) periods. The authors employ 75 and 96 portfolios based on different factors. To check the performance of asset pricing models, the authors also used the GRS F-statistics and factor spanning tests.

The authors find that the five-factor model and alternative four-factor model outperform the three-factor model. Contrary to the findings for the US, but similar to the Chinese stock market, the value factor is significant for the Indian stock market. Simultaneously, the authors also find that the investment factor has no explanatory power in the presence of the profitability factor in their sample.

To the best of the authors' knowledge, this is the most comprehensive study using data more than two decades. These results are based on 75 (25 × 3) portfolios based on size, value, profitability and investment. The authors also tested these results based on 96 (32 × 3) portfolios to check robustness, and these results still hold. Furthermore, the authors find that factors based on 2 × 3 sorting have higher explanatory power than those based on 2 × 2 and 2 × 2 × 2 × 2 sorting.

This study examines the five-factor model of Fama and French (2015) on the French stock market by comparing it to the Fama and French (1993)’s base model. The new Fama and French five-factor model directed at capturing two new factors, profitability and investment in addition to the market, size and book to market premiums. The pricing models are tested using a time-series regression and the Fama and Macbeth (1973) methodology. The regularities in the factor’s behavior related to market conditions and to the sovereign debt crisis in Europe are also examined. The findings of Fama and French (2015) for the US market are confirmed on the Paris Bourse. The results show that both models help to explain some of the stock returns. However, the five-factor model is better since it has a marginal improvement over the widely used three-factor model of Fama and French (1993). In addition, the investment risk premium seems to be better priced in the French stock market than the profitability factor. The results are robust to the Fama and Macbeth (1973) methodology. Moreover, profitability and investment premiums are not affected by market conditions and the European sovereign debt crisis.