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The purpose of this study is to investigate the presence of psychological barriers both in the main stock market indices of the Baltic states and the most actively traded individual stocks. A psychological barrier refers to a specific price point, often at round numbers (i.e. powers of 10), that investors believe is challenging to breach, influencing their behavior and trading decisions.

We conduct uniformity tests and barrier tests, such as barrier proximity tests and barrier hump tests, to evaluate the presence of psychological barriers. Additionally, we explore variations in means and variances near these potential barriers using regression and GARCH analysis.

The findings reveal that psychological barriers do exist in the Baltic stock markets, particularly within market indices. The Estonian market index stands out with the most pronounced indications of psychological barriers. Individual stocks also display significant changes in means and variances related to potential barriers, albeit with less uniformity.

Collectively, our findings challenge the traditional assumption of random returns within the Baltic stock markets. For practitioners, the finding that psychological barriers exist opens up opportunities for investment strategies that can capitalize on them.

This study is the first to comprehensively investigate psychological barriers in the Baltic stock markets. Our results provide a valuable contribution to understanding the impact of that phenomenon on pricing dynamics, which is particularly pertinent in less-researched frontier markets like the Baltic states.

The authors investigate the impact of the US stock market on the economies of the BRICS and major industrialized economies (G7).

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. Global vector autoregressive (GVAR) empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The authors summarize the results in four points: (1) financial integration variables increase the effect of the US stock market on the BRICS and G7, (2) the US shock produces similar responses in these groups regarding industrial production, stock markets and confidence but different responses regarding domestic currencies: in the BRICS, the authors detect appreciation of the currencies, while in the G7, the authors find depreciation, (3) G7 stock markets and policy rates are more sensitive to the US shock than the BRICS and (4) the estimates point out to heterogeneities such as the importance of industrial production to the transmission shock in Japan and China, the exchange rate to India, Japan and the UK, the interest rates to the Eurozone and the UK and confidence to Brazil, South Africa and Canada.

The results reinforce the importance of taking into account different levels of economic development.

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. GVAR empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

In the verge of assessing Muslims’ participation in stock market, present study delved into evaluating the influence of Islamic religiosity (IR) on Muslim investor’s financial engagement factors with respect to stock market (i.e. financial literacy [FL], Islamic financial literacy [IFL], behavioural factors [BF], Shariah compliance [SC], technology adoption [TA] and institutional support [IS]), stock market participation (SMP) and financial well-being (FWB). Further, this study aims to examine the mediating role of IFL, TA and SMP and moderating role of IS.

Using a mixed-methods approach, a structured survey questionnaire was administered and responses have been collected from 319 Muslim investors from South India using stratified random sampling. Further, data was analysed using SPSS 20.0 and AMOS 20.0 by implementing one-way ANOVA, measurement model and structural equation model to assess the differences, mediating and moderating roles.

In this study, it is discovered that IR significantly impacts Muslim investor’s financial engagement factors, SMP and FWB. Further, it is explored that IFL accelerates the impact of FL and SC on SMP. The results also demonstrated the intervening role of TA in enhancing SMP through BF and the mediating role of SMP among Muslim investors with strong IR to attain and enjoy FWB. Interestingly, our study also argued that when the IS is more, the effect of IR on SMP is high.

Geographical boundaries are restricted to India, where the study proposes future studies in Islamic countries to better understand the religious belief system of the investors, as SC may vary in different countries.

In accordance with the results, it is recommended that the regulatory bodies and institutions intervene, support and incorporate IFL and also provide user-friendly Tec platforms to monitor and filter stocks and financial products for SC.

The present study intends to tackle the misconception of Islamic values with respect to participating in the stock market and recommends to undertake policy and regulatory framework to ensure the inclusive development of this community.

To the best of the authors’ knowledge, no studies so far have pondered on the mediating role of SMP in enhancing the effectiveness of IR on their FWB. Further, this study collectively examines the influence of IR on various financial engagement factors affecting SMP leading to FWB.

This paper investigates potential safe haven assets for Middle East and North Africa (MENA) stock markets during the uncertainty period of the COVID-19 pandemic.

This study applies the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic (DCC-GARCH) model and the Diebold–Yilmaz spillover index for ten MENA stock markets, three precious metals and Bitcoin for the period 2013–2021.

Empirical results show, on the one hand, that the COVID-19 crisis risk has been transmitted to MENA stock markets through volatility spillover across markets. This has increased the conditional volatility for all markets. On the other hand, findings point out that the dynamic correlation between the precious metals/Bitcoin and stock markets is not stable and switches between low positive and negative values during the period under studies. Extending analysis to portfolio management, results reveal that investors should include precious metals/Bitcoin in their portfolio of stocks in order to reduce the risk of the portfolio. Finally, for the period of COVID-19, the analysis concludes that gold preserves its traditional role as a safe haven for MENA stock markets during the pandemic, while Bitcoin fails to provide this property.

These results have several implications for international investors, risk managers and financial analysts in terms of portfolio diversifications and hedging strategies. Indeed, the exploration of the volatility connectedness between financial, commodity and cryptocurrency markets becomes an essential task for all market participants during the COVID-19 outbreak. Such analysis can help investors and portfolio managers to evaluate the risk of investments in the MENA stock markets during the crisis period and to achieve the optimal diversification strategy and hedging instruments.

The paper interests MENA stock markets that experienced the last decade a substantial development in terms of market capitalization and number of listed firms. To the author’s knowledge, this is the first study that investigates the dynamic correlation between MENA stock markets and four potential safe haven assets, including three precious metals and Bitcoin. In addition, the paper employs two types of models, namely the DCC-GARCH model and the Diebold-Yilmaz spillover index.

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

This research aims to investigate the relationship between environmental, social and governance (ESG) factors and the performance of real estate companies before and after the COVID-19 pandemic. By conducting a comprehensive case study analysis, we will explore how real estate companies' adoption of ESG practices has influenced their financial performance, market value and resilience during these uncertain times. The findings of this study will contribute to the existing body of knowledge on the relationship between ESG factors and company performance, specifically within the real estate sector. Moreover, the research outcomes will offer practical implications for real estate companies, investors, policymakers and other stakeholders, aiding them in making informed decisions regarding ESG integration and its potential benefits in uncertain times. Overall, this research aims to shed light on whether ESG factors truly enhance the performance of real estate companies, considering the unique challenges posed by the COVID-19 pandemic and sanctions. By examining the case study before and during uncertain times including COVID-19 pandemic and sanctions, we provide valuable insights into the role of ESG practices in shaping the future of the real estate industry.

The study focuses on the selection process and main model used to investigate the relationship between ESG factors and firm performance. The data is divided into four groups based on ESG quartiles to analyze differences between firms with high and low ESG scores. The Difference-in-Differences (DID) model is employed to assess anomalous returns and stock volatility across different ESG quartiles before and after the COVID-19 pandemic. Panel data models are utilized to study the association between ESG and firm performance, with random effects and fixed effects estimators considered. The study builds a model to analyze the impact of ESG on financial performance indicators, incorporating various factors and control variables. Additionally, the Average Treatment Effect on the Treated (ATET) analysis and DID model are explored to evaluate the causal impact of ESG on firm performance. The study emphasizes the importance of testing for parallel trends to ensure the validity of the ATET analysis and it presents a generalized DID model to examine the relationship between ESG scores and company performance outcomes.

Our study's main conclusions show that, in a world with some degree of stability, ESG not only does not improve but, in some situations, also hurts firms' success. On the other hand, at times of notable worldwide unrest, like the COVID-19 pandemic, firms with better ESG ratings demonstrate exceptional stock market success and a noteworthy ability to rebound from a crisis. Moreover, we note that investors truly prioritize sustainable investments as a risk mitigation strategy in addition to their environmental and social duties only when companies face sufficiently significant risks. The results will highlight the significance of sustainable and responsible investment for investors and provide management with more knowledge to create effective ESG strategies for their companies.

By incorporating sustainability and responsibility into their operations, businesses may reduce risk, perform better over the long run and benefit society and the environment. As investors come to understand the importance of ESG issues in their decision-making, the global landscape is experiencing a transformation. Therefore, in the era when stakeholders, such as consumers, workers and shareholders, want more responsibility and transparency when it comes to ESG practises, it is crucial that companies should devote their priority to their ESG performance in order to reduce the danger of slipping behind, especially in light of the increasing importance of sustainability issues and changing laws. However, in the case of small-sized firms, investment policies to improve companies’ governance need to be controlled in moderation during the period of stability because it will create financial pressure and leave them without enough resources to cope with negative impacts during uncertain period. In sum, sustainable and ethical investment is not only a fad; rather, it is a vital and unavoidable route for companies looking to prosper in an unpredictable and complicated global environment.

This research study significantly enhances the existing academic discourse surrounding the relationship between ESG factors and firm performance, particularly, in periods of uncertainty. The findings underscore the critical importance for real estate companies to place a greater emphasis on ESG practices in order to not only benefit themselves but also to improve their overall performance and sustainability in the long term. By shedding light on the positive outcomes associated with prioritizing ESG considerations, this study offers valuable insights for real estate firms seeking to enhance their competitive advantage and stakeholder value in today's dynamic business landscape.

The study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.

The study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.

Incorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.

The study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.

Governments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.

Studies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

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 sporting performance and the market value of European football clubs, with a particular focus on the moderating effect of player transfers, fan engagement and coaching changes.

Using a Cross-Sectional Augmented Auto Regressive Distributed Lagged Model (CS-ARDL), we analyze a decade of data (2013–2023) from fourteen prominent clubs across ten European leagues.

Our findings confirm a strong positive correlation between sporting performance and market value in European football clubs. Furthermore, the research reveals that strategic player transfers and high fan engagement significantly amplify the positive impact of on-field success on a club's valuation. Interestingly, coaching changes do not exhibit a significant moderating effect on this relationship.

These findings carry significant economic implications for the football industry, underscoring sporting success as not only a driver of economic growth and social development but also a vital source of funding for clubs seeking to further invest in talent, infrastructure and fan engagement initiatives.

This study makes a novel contribution to the existing literature by providing a comprehensive analysis of the intricate relationship between sporting performance, market value and the moderating roles of player transfers, fan engagement and coaching changes within the European football landscape. Moreover, the research offers unique insights into investor behavior and the factors influencing investment decisions, enriching our understanding of the complex dynamics driving the football market.

This study aims to examine the effect of CEO compensation risk, as measured by the proportion of equity-based pay (option and stock awards) relative to total compensation and pay sensitivity to stock volatility, on CEO pay for luck asymmetry. This paper also empirically examines CEO compensation risk as a mediating variable between the regulatory changes and CEO pay for luck asymmetry.

This paper test the proposed two hypothesis that CEO compensation risk is positively associated with the degree of CEO pay for luck asymmetry; and the pay related regulations implemented around 2006 could mitigate the degree of CEO pay for luck asymmetry using the fixed-effects regression models.

Consistent with the managerial talent retention hypothesis, this paper finds that CEO compensation risk, as measured by the equity-based pay as a proportion of CEO total compensation and CEO pay sensitivity to stock volatility, is positively associated with the degree of CEO pay for luck asymmetry. In addition, this paper find that CEO pay for luck asymmetry is significantly reduced by the major regulatory changes on executive compensation implemented around 2006.

This study is among the very few studies exploring the impact of CEO compensation risk on pay for luck asymmetry in the literature. While the major purpose of the widely used stock options is to align executive interests and shareholder values, it also tends to increase the risk level of CEO compensation. So, a well-designed CEO pay package should protect risk-averse CEOs from bad luck for the retention purpose, which is also beneficial to shareholder wealth maximization. Therefore, future research on executive compensation needs to examine the issue from various perspectives.

For board of directors who is responsible for the compensation of CEOs, it is necessary to consider a broad range of factors when designing an optimal CEO pay package.

The findings on the impact of regulations on CEO pay for luck asymmetry suggest that the executive-pay-related regulations around 2006 have indeed achieved some of their intended goals to significantly lower pay for nonperformance asymmetry, whereby CEO pay sensitivity to stock volatility has been identified as a major mediating variable.

This study contributes to the literature on executive pay for luck asymmetry in several perspectives. First, this paper finds that CEO compensation risk has a positive impact on the degree of CEO pay for luck asymmetry. Second, this paper finds that the CEO pay for luck asymmetry has been mitigated after 2006 when various regulatory changes on executive compensation began to be implemented in the USA. To the best of the authors’ knowledge, this study is among the very few studies investigating these issues in the literature.