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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.

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 study aims to test mutual fund superiority, comparing the performance of 646 Islamic mutual funds with 475 ethical funds and conventional proxies.

This study uses statistical methods including paired t-statistics of independent samples, one-way Bonferroni test–analysis of variance–F-statistic for testing means equality, the chi-squared test for median equality and regression models corrected for heteroscedasticity. These methods are used to identify superiority of mutual funds and to validate the significance of the results.

The findings confirm the superiority of conventional funds over ethical funds and ethical funds over Islamic funds. Both ethical and Islamic funds, however, outperform conventional proxies during some recessionary periods. Moreover, stronger performance is recorded for Islamic funds in Europe and North America regions and across age and asset allocation categories, but limited support for reversal fund size, composition focus and reversed price effect.

These findings should assist investors when deciding to invest and motivate Islamic and ethical funds to improve their portfolio formation and asset allocation strategies set by their professional managers.

The originality of this study is in its comprehensive approach in that it compares the performance of funds after accounting for such characteristics as fund objectives, size, age, asset allocation, geographical investment focus, fund composition focus, share price levels and the effect of global crises. This study approach is not only original and productive in documenting Islamic funds’ performance for the past three decades (1990–2022) but can also update the literature on these characteristics collectively and individually.

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

This study aims to analyze the causes and implications of legal uncertainty in the issuance of conventional municipal bonds in Indonesia and to draw lessons from Vietnam’s approach in providing better legal certainty.

This study adopts a normative legal method with a legislative approach and applies a comparative approach. Data sources involve primary and secondary legal materials from both Indonesia and Vietnam.

The legal uncertainty is caused by a lack of coherence and consistency in legislation. Based on Vietnam’s experience, Indonesia can gain valuable insights related to providing strong legal certainty for parties involved in issuing or investing through conventional municipal bonds.

This study focuses on the comparative legal analysis of conventional municipal bonds in Indonesia with Vietnam.

This research provides recommendations for the refinement of legislation regarding conventional municipal bonds to the government.

This study is related to legal certainty as a strategy to attract investment through municipal bonds and to ensure the municipal bond issuance process is transparent and efficient.

This study provides a comparative perspective on the issuance of municipal bonds in Indonesia, with a special focus on Vietnam, emphasizing the urgency of harmonization in legal regulation and the sustainability of legal certainty.

This study examines the connection between investor sentiment and corporate innovation in the United States, considering the magnitude of corporate information asymmetry, the implied cost of capital and the financial constraints.

The authors employ a two-step GMM framework to examine the hypotheses of this study by utilizing annual data from 2001 to 2021 for US corporations.

The empirical evidence demonstrates a significant impact of investor sentiment on corporate innovation for firms with a lower information asymmetry and implied cost of capital than those with a higher information asymmetry and cost of capital. Although the financial constraint channel remained positive, it had little impact on the innovations of US corporations. Overall, the study's results show that companies make more valuable and high-quality patents when investors are optimistic.

This research has policy implications for all managers, investors, analysts and state officers, particularly in the USA and other developed countries. Managers and investors of all types should predict the role of corporate innovation in increasing shareholder wealth.

To the authors' knowledge, this is the first study to examine the relationship between investor sentiment and corporate innovation in the United States, considering the extent of corporate information asymmetry, the implied cost of capital and the financial limitations. The study's empirical findings uniquely contribute to the existing literature on corporate innovation and investor sentiment in the current context.

Driven by the anticipated global stagflation, this straightforward yet novel study examines the cost of inflation as a macroeconomic factor by investigating its influence on stock market growth. Thus, this paper aims to examine the impact of inflation on the probability of initial public offering (IPO) withdrawal decision.

The paper employs a large dataset that covers the period January 1995–December 2019 and comprises 33,536 successful or withdrawn IPOs from 22 nations with various legal and cultural systems. This study applies a probit model utilizing version 15 of Stata statistical software.

This study finds that inflation is substantially and positively correlated with the likelihood of IPO withdrawal. Results of this study show that the IPO withdrawal decision increases up to 90% when the inflation rate climbs by 10%. Multiple robustness tests provide consistent findings.

This study's implications are important for researchers, investment banks, underwriters, issuers, regulators and stock exchanges. When processing IPO proposals, investment banks, underwriters and issuers must consider inflation projections to avoid negative effects, as demonstrated by the findings. In addition, regulators and stock exchanges must be aware of the detrimental impact of inflation on competitiveness in attracting new listings.

To the best of the authors’ knowledge, this study is the first to present convincing evidence of a major relationship between IPO withdrawal decision and inflation.

The purpose of this paper is to propose a novel and new direct measurement of small investor sentiment in the equity market. The sentiment is based on the individual investors’ internet search activity.

The author measures unexpected changes in the small investor sentiment with AR (1) process, where the residuals capture the unexpected changes in small investor sentiment. The author employs vector autoregressive, Granger causality and linear regression models to estimate the association between the unexpected changes in small investor sentiment and future equity market returns.

An unexpected increase in the search popularity of the term bear market is negatively associated with the following week’s equity market returns. An unexpected increase in the spread (the difference in popularities between a bull market and a bear market) is positively associated with the following week’s equity market returns. The author finds that these effects are stronger for small-sized companies.

By author’s knowledge, the paper is the first that measures the small investor sentiment that is based on the internet search activity for keywords used in the American Association of Individual Investor’s (AAII) survey questions. The paper proposes an alternative small investor sentiment measure that captures the changes in small investor sentiment in more timely fashion than the AAII survey.

Valuers should independently assess market value. The purpose of this article is to analyze whether the valuation behavior remains independent when commissioned by publicly listed companies in Taiwan.

This study used both quantitative and qualitative methods. Quantitative data analysis was used to examine the estimated premium ratio and estimated divergent ratio with the independent sample t test and Wilcoxon-Mann-Whitney test. To complement and validate the quantitative analysis, open-ended questionnaires were conducted, providing additional insights into the research findings.

The results showed that there is a significant difference in estimated valuations commissioned by representatives of buyers and sellers, and the estimated premium ratios commissioned by representatives of buyers were higher than those of sellers. Furthermore, the open-ended questionnaires results indicate that these findings may be influenced by clients for less experienced appraisers. However, for senior appraisers, this is seen as an action to gain a better understanding of the valuation purpose and always within a reasonable price range. In addition, client influence is not a static factor; it may transform into the valuer's behavior as the appraiser's experience grows and deepens.

It is difficult to obtain valuation reports commissioned by representatives of both buyers and sellers for the same property transactions. In this study, data were obtained from the Market Observation Post-System (MOPS) in Taiwan. As valuation reports could not be obtained, estimated valuations and transaction prices are used to calculate estimated premium ratio and estimated divergent ratios.

Previous investigations of the client effect have been conducted using qualitative methods including questionnaire surveys, in-depth interviews and experimental design. However, these studies are subject to moral hazard. This study may be the first study that has access to data on valuations for both buyers and sellers in such a formal setting.

Stirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study.

Methodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022.

The results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions.

In the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered.

While limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.