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The current study immerses itself in the realm of diversification prospects within a select group of preeminent global stock exchanges. Specifically, the study casts its discerning gaze upon the financial hubs of the United States, Hong Kong, Germany, France, Amsterdam and India. In this expansive vista of international financial markets, the present analytical study aims to unravel the multifaceted opportunities that lie therein for astute portfolio management and strategic investment decisions.

The study encompasses daily time series data spanning from 2019 to 2022. To assess the interconnectedness among these stock indices, advanced statistical techniques, including Johansen cointegration methods and vector autoregressive (VAR) models, have been applied.

The research outcomes reveal both unidirectional and bidirectional relationships between the Indian, Hong Kong and US stock exchanges, encompassing both short-term and long-term time frames. Interestingly, the empirical findings indicate the presence of diversification opportunities between the Indian stock exchange and the stock exchanges of Germany, France and Amsterdam.

These insights hold significant value for both Indian and international investors, including foreign institutional investors (FIIs), domestic institutional investors (DIIs) and retail investors, as they can utilize this knowledge to construct more effective and diversified investment portfolios by understanding the intricate interconnections between these prominent global stock exchanges.

This research undertaking aspires to bring coherence to a landscape rife with divergent interpretations and methodological divergences. We are poised to offer a comprehensive analysis, a beacon of clarity amidst the murkiness, to shed light on the intricate web of interconnections that underpin the world's stock exchanges. In so doing, we seek to contribute a seminal piece of scholarship that transcends the existing ambiguities and thus empowers the field with a deeper understanding of the multifaceted dynamics governing international stock markets.

The price clustering behavior is becoming a core part of the market efficiency theory especially with the development of trading strategies and the occurrence of major and unprecedented shocks which have led to severe inquiry regarding asset price dynamics and their distribution. However, research on emerging stock market is scant. The study contributes to the literature on price clustering by investigating an active emerging stock market, the Muscat stock market one of the Arabian Gulf Markets.

This research adopts the artificial intelligence technique and other statistical estimation procedure in understanding the price clustering patterns in Muscat stock market and their main determinants.

The findings reveal that stock prices are marked by clustering behavior as commonly highlighted in the previous studies. However, we found strong evidence of price preferences to cluster on numbers closer to zero than to one. We also show that the nature of firm’s activity matters for price clustering behavior. In addition, firms with traded bonds in Oman market experienced a substantial less stock price clustering than other firms. Clustered stock prices are more likely to have higher prices and higher volatility of price. Finally, clustering raised when the market became highly uncertain during the Covid-19 crisis especially for the financial firms.

This study provides novel results on price clustering literature especially for an active emerging market and during the Covid-19 pandemic crisis.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This study aims to provide empirical evidence on the impact of foreign share ownership on the liquidity of the Tunisian Stock Exchange (TSE).

The authors hypothesize in the first strand that stock liquidity could be positively affected by foreign ownership based on the real friction channel. The authors then hypothesize in the second strand, based on the information friction channel, that foreign ownership's impact on stock liquidity could be insignificant or negative and that foreign investors raise the level of information asymmetry. A sample of 318 firm-year observations from Tunisia over the 2012–2017 period and a random-effects estimation were used. Moreover, using the 2SLS estimator, a robustness check framework was applied in order to address any potential reverse causality concerns.

The authors find strong evidence that higher foreign ownership improves stock liquidity. More specifically, firms with higher foreign ownership engender a lower bid-ask spread, a better stock ability to absorb a large amount of trading volume, and a larger depth. These findings are still valid when reverse causality concerns are addressed through the use of the 2SLS estimator.

The paper contributes to the existing literature by focusing on the ownership–liquidity relationship on a frontier market. It provides further empirical support that higher corporate governance quality reduces the information asymmetry problem and enhances stock market liquidity.

The current research aims to investigate the impact of coronavirus 2019 (COVID-19) evolution, government stringency measures and economic resilience on stock market volatility in the Middle East and North African (MENA) emerging markets. Other macroeconomic factors were also taken into account.

Based on financial data from 10 selected MENA countries, we tested an integrated framework that has not yet been explored in prior research. The exponential generalized autoregressive conditional heteroskedasticity (E-GARCH) was adopted to analyze data from March 2020 to February 2022.

Our research illustrates the direct and indirect effects of the virus outbreak on stock market stability and reports that economic resilience could alleviate the volatility shock. This finding is robust across the various proxies of economic resilience used in this study. We also argue that the negative impact of the pandemic on equity market variation gets more pronounced in countries with higher level of stringency scores.

Policymakers ought to strengthen their economic structures and reinforce the economic governance at the national level to gain existing and potential investors’ trust and ensure lower stock market volatilities in times of crisis. Our study also recommends some key economic factors to consider while establishing efficient policies to tackle unexpected shocks and prevent financial meltdowns.

Our findings add to the evolving literature on the reaction of economic and financial markets to the sanitary crisis, particularly in developing countries where research is still scarce. This study is the first of its kind to investigate the stock market reaction to stringency measures in the understudied MENA region.

This paper examines the reaction of the Egyptian stock market to two substantial devaluations of the Egyptian pound (EGP) in 2022 and tests the informational efficiency of the Egyptian market.

The paper uses the event study framework to analyze the significance and direction of abnormal returns of the leading index of the Egyptian stock market (EGX30) on and around the devaluation days. It employs both the constant mean model and the market model to estimate the normal returns of the EGX30. Additionally, the paper uses data on two equity indices, one global and one for emerging markets, as benchmarks for normal returns.

The paper finds that the Egyptian stock market experienced significant positive abnormal returns on the devaluation days of the EGP in March and October of 2022, indicating a positive market reaction to the devaluation. Furthermore, evidence suggests that the Egyptian market may not be informationally efficient as significant positive abnormal returns were observed two weeks before and two weeks after the devaluation day, suggesting news leaks and delayed reactions, respectively.

This study is the first to examine the impact of the recent two devaluations of the EGP in 2022 on the Egyptian stock market. It complements existing literature by analyzing the immediate market reaction to two consecutive devaluations in an African country. Furthermore, the paper evaluates the efficiency of the Egyptian market in processing information related to exchange rates.

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

Introduction: Political stability is an essential source of stock market dynamics. Investors are confident about countries that have higher political stability. Political stability in an economy enables investors to develop their ability to predict the future and thus to tend towards longer-term and permanent economic and financial activities.

Purpose: The study aimed to investigate the impact of political instability in BRICS countries and Türkiye on their stock market volatilities.

Methodology: The study analysed the univariate exponential generalised autoregressive conditional heteroskedasticity (EGARCH) Model. The model employed the credit default swap (CDS) 5-year USD Bond data of the BRICS countries and Türkiye to represent political instability. The daily stock exchange index return data from 1 January 2015 to 15 January 2023 was used for model estimation.

Findings: The results of the EGARCH model indicate that political instability is a crucial factor in stock market volatility. The coefficients suggest that when CDS increases in BRICS countries and Türkiye, the volatility of stock returns also increases. The analysis shows that the impact of political instability on the stock market of BRICS countries and Türkiye is not uniform. However, the significant effect of political instability on volatility is higher for Türkiye than for BRICS countries. This indicates that investors perceive the political risk of Türkiye to be greater than that of BRICS countries when investing in the stock market of Türkiye.

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

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.