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This paper investigates the relationship between the sustainable finance disclosure regulation (SFDR) and the performance of unlisted real estate funds.

While existing literature has primarily focused on the impact of voluntary sustainability disclosure, such as certifications or reporting standards, this study addresses a significant research gap by constructing and analyzing the financial J-Curve of 40 funds under the SFDR. The authors employ a panel regression analysis to examine the effects of different SFDR categories on fund performance.

The findings reveal that funds categorized under Article 8 of the SFDR do not exhibit significantly poorer performance compared to funds categorized under Article 6 during the initial phase after launch. On average, Article 8 funds even demonstrate positive returns earlier than their peers. However, the panel regression analysis suggests that Article 8 funds slightly underperform when compared to Article 6 funds over time.

While investors may not anticipate lower initial returns when opting for higher SFDR categories, they should nevertheless be aware of the limitations inherent in the existing SFDR labeling system within the unlisted real estate sector.

To the best of our knowledge, this study represents the first quantitative examination of unlisted real estate fund performance under the SFDR. By providing unique insights into the J-Curves of funds, our research contributes to the existing body of knowledge on the impact of sustainability regulations in the financial sector.

This paper evaluates the performance of actively managed conventional and Islamic equity funds in a developing economy with a focus to assess the performance-growth puzzle posited by Gruber (1993) (a.k.a Gruber’s puzzle). Under the context of an emerging market of Pakistan, this study explores if actively managed equity fund (AMEF) managers have been able to add value by outperforming the market in terms of stock-selection and market-timing abilities; and the comparative performance analysis of Islamic versus conventional AMEFs is also carried out.

We employ Sharpe and Treynor ratios, Capital asset pricing model, Fama–French three factors model (1993), Carhart four-factor model (1997) and Hendrickson (1981) market timing models on 45 equity funds comprising of 23 conventional and 22 Islamic equity funds operating in Pakistan for a period of 10 years. The overall sample period (2008–2018) is divided into two 5 years sub-periods (i.e. 2009–2013 and 2014–2018) and three 3 years sub-periods (2009–2011, 2012–2014 and 2015–2017) to be viewed in conjunction with the country's macro-economic condition.

We report that the actively managed equity funds (AMEFs) were unable to beat the market index with their stock selection or market timing capabilities. However, AMEFs depicted improved performance in the post-global financial crisis period where both conventional and Islamic AMEFs generated substantial rewards for the given amount of risk. Also, conventional AMEFs outperformed Islamic AMEFs potentially due to their holdings in highly leveraged value and large-cap stocks, while Islamic AMEFS invest more cautiously in small-cap and value firms. Analysis of market timing skills revealed that the funds have not been able to select the undervalued stocks and adopted a defensive strategy in the post-global financial crisis recovery period.

Our findings shed some interesting insights and raise some pertinent questions for research, policy, and practice – specifically for developing countries’ context. The no ‘return-growth’ configuration defies its fit with the ‘Gruber puzzle’ and somewhat presents a case of what we call the ‘Inverse Grubber puzzle’. This novel notion of the ‘Inverse Grubber puzzle’ should inform policy and practice to reflect on their practices, institutional arrangement, regulatory framework and policy design in developing economies characterized by lacklustre performance and growth of AMEFs. For example, the regulatory design may consider focusing on stimulating financial inclusion and deepening by motivating low-cost Index tracker funds (ITFs) – with lower fund management costs, while allocating the avoided cost to flow towards effective marketing campaigns driving greater awareness, financial deepening, and investor base diversification. For future research, financial development researchers may explore the implications and appropriateness of AMEFs versus ITFs in other developing economies.

The work reported in this paper is original and constitutes a valuable asset for ethno-religious-sensitive investors. The research has not been published in any capacity and is not under consideration for publication elsewhere.

This study aims to determine whether the stock holdings of equity mutual funds are informative for predicting future stock performance in the Chinese market. It is a puzzle that actively managed mutual funds underperform passive benchmarks, whereas retail investors still delegate investment decisions to the fund managers. The present study sheds light on whether mutual fund managers possess security selection skills in their top ten holdings.

By regression analysis and portfolio sorting, this study focuses on 830 Chinese A-share stocks in the industry research reports from the Guotai Junan Securities Company. It collects mutual fund's top ten holdings data from the Wind Financial Terminal between 2019Q1 and 2021Q1. As robustness checks, the result holds for the fixed-effect model, an additional measure of ranks in the top ten holdings, the predictability test based on the confusion matrix and two stage least square (2SLS) regression.

The authors find that the top ten holdings by equity mutual funds are informative for predicting stock performance and can provide valuable information for investors to support their decision-making.

The findings of this study provide insightful guidance for retail investors in making investment decisions and support the hypothesis that active fund management adds value.

Firstly, the authors find that the top ten holdings of Chinese mutual funds show significantly positive signals for future stock excess returns, indicating the selection skills of fund managers. Secondly, the above positive relationship exhibits a diminishing marginal effect with more funds holding this stock. Thirdly, the authors find that the predictability horizon of the number of overweighing funds is up to three quarters and then diminishes in the fourth quarter. Finally, investors have a 59% prediction accuracy for the whole stock sample and an 85% precision conditional on the predicted positive subsample to outperform the market. The authors also address the endogeneity and reverse causality issues.

This article analyses the recent inverse transition from goodwill impairment to goodwill amortisation implemented in Spain in 2016. The authors contribute to the existing literature by describing their differing impact over goodwill and impairment figures and testing the impact of goodwill on balances over stock prices.

First, using a database with all Spanish non-financial firms with positive goodwill on their balance sheets, the authors describe the impact of the regulatory change over goodwill and impairment figures. Second, focussing on listed firms only, the authors study the impact of financial reporting of goodwill and impairment on stock prices.

Average goodwill per company and the share of goodwill over total assets significantly reduced after 2016, but the results cannot be easily extrapolated to listed firms due to lack of data. When testing the impact of potentially inflated goodwill balances on prices, the authors find that investors kept overvaluing firms with inflated goodwill balances also with the amortisation method.

The lack of data for listed firms with goodwill in Spain makes it difficult to obtain statistically sound evidence, the results could be biased by the cultural traits of the country and related to the intensity of enforcement and monitoring.

This might suggest that the effects of the impairment method linger, so the authors conform to the interpretation that the systematic amortisation paired with a periodic impairment test may lead to accounting that better reflects the underlying economics of goodwill.

To the best of the authors' knowledge, there are no recent articles that analyse this new “turn-around” requiring again the systematic amortisation of goodwill.

This paper aims to investigate not only the performance of Portuguese mutual funds investing in domestic and international equities but also which fund characteristics, such as age, size, family size, expense ratios and flows, influence future performance.

Fund performance is evaluated over the 2005–2022 period by a robust six-factor model, while the impact of fund characteristics on performance is assessed by a set of fixed-effects panel data regressions with two-way cluster-robust standard errors.

The results show that, while funds investing in domestic equities predominantly exhibit neutral performance, most international equity funds have significantly negative alphas. The authors document a negative and statistically significant relationship between fund age and performance for all fund categories. Total expense ratios have an inverse relationship with domestic equity fund performance but do not impact the performance of international equity funds significantly. Though fund flows have a neutral effect on performance across the overall period, they are important determinants of both domestic and international funds’ performance in more recent years.

The authors contribute to the literature by carrying out a comprehensive analysis, based on recent and robust methodologies, of the impact of mutual fund characteristics on the future performance of Portuguese equity funds. The research findings serve as a premise for advising investors on how to choose the top-performing funds.

The purpose of this study is to investigate the factors affecting behaviour intention (BI) to use and actual usages of investment-related FinTech services among the zoomers (Gen Z) and millennials (Gen M) retail investors of India.

The study explores the predictive relevance of actual adoption behaviour among the two different age categories of Indian retail investors. It uses the Unified Theory of Acceptance and Use of Technology-2 and the prospect theory framework as guiding frameworks. Data has been collected from 294 retail investors, actively engaged in the investment-related FinTech services. The multi-group analysis using variance-based partial least square structured equation modelling has been used to compare the two groups. The invariance between the two groups was achieved through measurement invariance assessment.

The study reveals distinct factors significantly affecting BI to use investment-related FinTech services among Gen Z and Gen M retail investors are performance expectancy (PE) to BI, perceived risk (PR) to BI, price value (PV) to BI and PR to service trust (ST).

This study provides insights for financial providers and policymakers, emphasizing different factors influencing BI to use investment-related FinTech services in both age groups. Notably, habit emerges as a common factor influencing the actual usage of investment-related FinTech services across Gen M and Gen Z retail investors in India.

This study explores the heterogeneous behaviour of the heterogenous population in the domain of technological adoption of investment-related FinTech services in India.

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders.

This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further.

The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy.

One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics.

The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools.

Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision.

Based on the theoretical framework, this paper analyzes the sentiment-herding relationship in emerging stock markets (ESMs). First, it aims to examine the effect of investor sentiment on herding. Second, it seeks the direction of causality between sentiment and herding time series.

The present study applies the Exponential Generalized Auto_Regressive Conditional Heteroskedasticity (EGARCH) model to capture the volatility clustering of herding on the financial market and to investigate the role of the investor sentiment on herding behaviour. Then the vector autoregression (VAR) estimation uses the Granger causality test to determine the direction of causality between the investor sentiment and herding. This study uses a sample consisting of stocks listed on the Shanghai Composite index (SSE) (348 stocks), the Jakarta composite index (JKSE) (118 stocks), the Mexico IPC index (14 stocks), the Russian Trading System index (RTS) (12 stocks), the Warsaw stock exchange General index (WGI) (106 stocks) and the FTSE/JSE Africa all-share index (76 stocks). The sample includes 5,020 daily observations from February 1, 2002, to March 31, 2021.

The research findings show that the sentiment has a significant negative impact on the herding behaviour pointing out that the higher the investor sentiment, the lower the herding. However, the results of the present study indicate that a higher investor sentiment conducts a higher herding behaviour during market downturns. Then the outcomes suggest that during the crisis period, the direction is one-way, from the investor sentiment to the herding behaviour.

The findings may have implications for universal policies of financial regulators in EMs. We have found evidence that the Emerging investor sentiment contributes to the investor herding behaviour. Therefore, the irrational investor herding behaviour can increase the stock market volatility, and in extreme cases, it may lead to bubbles and crashes. Market regulators could implement mechanisms that can supervise the investor sentiment and predict the investor herding behaviour, so they make policies helping stabilise stock markets.

The originality of this paper lies in investigate the sentiment-herding relationship during the Surprime crisis and the Covid-19 epidemic in the EMs.

Online employee reviews have a substantial impact on employee recruitment, retention and the overall perception of a company’s image, making them a crucial element of its online reputation. Consequently, these reviews play a vital role in shaping the company’s competitiveness in the talent market. This study aims to investigate the role of employee loyalty in online reputation in the tourism and hospitality sector.

This study collected online reviews posted by 334,428 employees across 173 companies in the tourism and hospitality sector. Then, this study proposed a method for measuring employee loyalty toward the company through text comments. Furthermore, the role of employee loyalty in online reputation through regression models was analyzed.

Employee loyalty is positively associated with the closed-form evaluations, and the length and readability of open-ended comments is directly and positively associated with review helpfulness and is indirectly associated with review helpfulness through employee online reviews. Employees’ perception of job instability has a significant moderating effect on the above relationships.

This study contributes to the literature on loyalty in the tourism and hospitality industry, online reputation and employee risk perception. These findings offer a more profound understanding of the extra-role behaviors demonstrated by loyal employees, provide a theoretical foundation for the formation of a company’s online reputation and contribute to helping the tourism and service industry better address risk events. These conclusions provide valuable insights for companies in the fields of human resource management and online reputation management.

To the best of the authors’ knowledge, this study is the first to reveal the impact of employee loyalty on the company’s online reputation and provides important theoretical and practical implications for management.

The purpose of this study is to examine the post-event perceptions of Rio de Janeiro residents regarding the legacies left to them from hosting the 2016 Olympic Games. Additionally, this study examines how perceptions of Olympic legacies differed amongst demographic groups.

Utilizing a mixed-methods approach, participants were asked to complete a survey questionnaire and answer three open-ended questions. An adapted version of Fredline et al. (2003)'s General Scale to Measure Social Impacts (GSMSI) was selected for this study. In total, 156 useable responses were collected. An exploratory factor analysis was utilized for the survey items while the three open-ended questions were coded abductively as positive, negative or mixed feelings.

The quantitative results shows that Rio residents believe that hosting the 2016 Olympic Games had a mostly negative impact on their perception of legacies. Through reading open-ended responses, participants expressed disappointment over the legacies left to them. These findings suggest that hosting the Olympic Games may not have been beneficial to the life of Rio de Janeiro residents, and it may have been particularly worse for members of the middle class.

Due to the recency of the Rio 2016 Olympic Games, a few studies have explored the long-term legacies left to the local population. However, the uniqueness of this study lays on the perceptions of legacies from hosting the Rio 2016 after a full Olympic cycle has passed.