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In this paper, the authors study the phenomenon of price clustering in the Pakistan Stock Exchange (PSX), a market viewed as one of the best-performing stock markets in the world during 2014–2017. The authors study the effect of stock-level variables on price clustering and analyze the determinants of the cross-sectional patterns of price clustering in the PSX, in particular the causal link between price clustering and political instability.

The authors' dataset comprises daily observations on 100 PSX stocks spanning from January 1, 2009 to June 30, 2019. The authors use multivariate regression and spectral analysis to shed light on the dynamics of stock price clustering in PSX.

The authors document abnormally high levels of stock price clustering, particularly on integer increments, in PSX. The nature of stock price clustering in PSX is consistent with the negotiation hypothesis of Harris (1991). The levels of stock price clustering on PSX are persistent and contain a cyclical component. Furthermore, the authors find that political uncertainty in Pakistan is a significant contributor to the high levels of price clustering on PSX. The authors' conclusions are robust to alternative econometric specifications and different measures of price clustering and political uncertainty.

The authors' findings are of interest to investors and policymakers. Since price clustering decreases market quality and degrades the information content of stock prices, the authors' study shows that price efficiency in PSX has not improved despite major reforms over the last decade. One practical implication of the authors' results is that investors should be cautious while rebalancing portfolios around political events such as general elections because stock price clustering increases in the PSX during these periods. As a result, stock prices are likely to deviate from their intrinsic values.

Research on price clustering is limited to developed markets, and emerging/frontier markets have been largely overlooked. The phenomenon of price clustering in the PSX has yet to be studied, despite the relevance of the PSX for emerging/frontier market investors.

This study aims to investigate the market reaction in the real estate market to the announcement of Russia’s invasion of Ukraine.

This study uses the event study method to assess the market reaction to the announcement that Russia is invading Ukraine. The sample in this study comprises 2,325 companies in the real estate market. We also conduct a cross-sectional analysis to determine the influence of the North Atlantic Treaty Organization (NATO) members and company characteristics on market reactions during the invasion.

The global market reacts significantly negative toward Russia’s invasion of Ukraine. This indicates that the war poses a high geopolitical risk that prompts financial markets down. The authors also demonstrate that emerging and frontier markets react significantly negative to the invasion before and after its announcement. Meanwhile, developed markets tend to react only before the invasion is announced. Furthermore, we find that the NATO members react more strongly than other markets.

This result implies that war prompts investors to flee from the stock exchange, while the deeper the country’s involvement, the more investors worry about the risks.

This study is the first to discuss the market reaction to the Russian invasion of Ukrainian, specifically in the real estate market.

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.

The authors investigate how foreign investment in securities market informs about the future firm performance in emerging markets.

The authors define the independent variable, abnormal foreign investment (AFI) as the residuals of the foreign ownership equation. The authors regress foreign ownership on its first lag and factors and define the residuals as the AFI. The AFI is the over- or under-investment reflecting foreign conscious (clear-purpose) investment, thus better indicating how foreign investment affects firm performance. The dependent variable is Tobin’s q (Q), which represents the firm performance. Then, the authors regress the Tobin’s q next quarters (Qt + k) on the AFI current quarter (AFIt). The authors use a two-step generalized method of moments (GMM) and check endogeneity with the D-GMM model for the regression.

The results show that the current AFI is positively correlated with the firm performance in each of the next four quarters (the following one year). This positive relationship is pronounced for large firms, firms with no large foreign investors, liquid firms and firms listed in the active market. The results suggest that foreign investment might choose well-productive firms already. Also, the current AFI is significantly positively correlated with stock returns in each of the next three quarters. These results suggest that the AFI is informative up to one-year period.

The results suggest that foreign investors (most of them are small) in the Vietnamese market might choose well-productive firms already. However, if the large investors have long-term investment in tangible, intangible, human capital and so on, and lead to a significant increase in firms’ performance is still the limitation of this paper.

The results of this paper may guide investors whose portfolios are composed of stocks with foreign investment.

This paper adds to the literature to enrich the conclusion of a positive relationship between foreign ownership and firm performance.

The priority of this study is to contribute to the literature by examining herding behavior at different periods of the COVID-19 pandemic. Furthermore, this study aims to investigate the herding behavior conditioned on market liquidity and information demand.

This study investigates herding behavior in Vietnam's stock exchanges (Ha Noi Stock Exchange and Ho Chi Minh Stock Exchange) on a sample of daily stock closing prices of 425 firms from 2018 to the first half of 2022.

The research confirms the existence of herding behavior not only for the whole but also during and post-COVID periods. These results are robust in both bull and bear markets, further confirming the influence of COVID-19 on herding in Vietnamese background. Moreover, when the authors condition exogenous factors for each period, the herding tendency is more evident at the medium market liquidity level than at high and low levels. Besides, the pandemic causes herding behavior of investors with low and medium information demand.

These findings imply some recommendations that facilitate investors, policymakers and researchers in the context of the COVID-19 crisis.

The study contributes to the herding literature by examining herd behavior during the post-COVID period, suggesting the long-term impact of the health crisis. Furthermore, the research provides new evidence of herding behavior conditioned on market liquidity and information demand during different COVID sub-periods.

Neuromarketing is a marketing communication field that applies neuroscience and physiological research tools to study consumer behavior toward stimuli, viz., ads and brands. This study aims to assess research trends in the neuromarketing field on the most influential journals, authorships, countries, citations and co-occurrences. The Scopus database is used to analyze identified articles from 2013 to 2022 and for the eligible research articles, a “systematic methodological review” (SMR) on consumer behavior through neuromarketing approach was done. “Visualization of Science (VOS)” viewer and “Biblioshiny” by R-studio software have been used for mapping the keyword analysis, co-citation analysis and author occurrence analysis. It was further found that of the top 10 academic institutions, the list is dominated by the six Asian institutions. It was further witnessed that journal “Physiology and Behavior” is trending as the most dedicated and emerging journals on neuromarketing and consumer behavior. Asian nations such as Bangladesh, China, India, Indonesia, etc., are turning out to be an emerging collaborators and publishers in this niche area of research, thereby giving tough competition to most developed countries. The findings of the thematic mapping show that neuromarketing is itself a very novel and newest area of study and topics such as “human marketing,” “neuromarketing,” “consumer behavior” and “electroencephalography” are new dimensions that can be looked upon in future.

This study systematically reviewed existing literature on the impact of economic uncertainty on property performance to highlight focus areas and spur future research amid unprecedented global uncertainty levels. Conceptually, uncertainty levels and environmental dynamism are related to investors' risk judgement and decision-making.

Peer-reviewed journal articles published from 2007 to 2022 were assembled and arranged through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The initial search produced 2,028 results from the Web of Science and Scopus databases, which were rigorously purified for a final dataset of 70 articles. These records were subsequently assessed through content analysis, bibliographic modelling, topic modelling and thematic analysis. Recurring themes were visualised using the VOSviewer software.

The existing literature suggests that economic uncertainty negatively impacts investment volumes, returns and performance. Research has also increased since 2018, with a strong emphasis on the housing sector and developed property markets. Commercial property and emerging markets account for only 10 and 8% of previous research, respectively.

These findings highlight the negative impact of economic uncertainties on property performance and investment volumes, which necessitate careful risk assessment. Given the high susceptibility of emerging and commercial property markets to uncertainty, these markets warrant further research amid ongoing uncertainty concerns across the globe.

Given current unprecedented levels of global uncertainty, the effects of economic uncertainty have received renewed interest. This study synthesised the current understanding of how different property markets respond to increased uncertainty and outlined future research directions to enhance understanding. Themes and relationships were also integrated into a conceptual map summarising the reported effects of economic uncertainty on housing, commercial property, investment and behaviour in the property market.

Service robots present a new frontier in the provision of services, with far-reaching implications for customers and managers alike. The purpose of this chapter is to examine how service robots impact service providers' current marketing strategies. For this, the authors perform an integrative, nonsystematic review of international gray and academic literature to understand how both practitioners and academics perceive the impacts of the technology. Based on this analysis, the present work identifies three key themes that emerge from the current state of practitioner and academic research, namely (1) service robots demand new core business capabilities and competencies, (2) service robots offer new value propositions, and (3) service robots impact not only service providers' cost structures but also revenue streams. These insights are combined into the Service Robot Innovation Canvas, a visual tool for service providers to identify the impact of service robot implementations on a company's marketing strategy. In addition, based on the analyzed literature, the most pressing questions for researchers are laid out in a research agenda.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

Exchange rate volatility is an important factor affecting investors and policymakers. This study aims to examine the impact of uncertainties, in terms of changes in economic policy, monetary policy and global financial markets, on exchange rate volatility.

The study uses the GARCH (1,1) univariate model to calculate exchange rate volatility. Economic and monetary policy uncertainties are measured using news-based indices, while global financial market volatility is measured using the implied volatility index. Panel autoregressive distributed lag modeling is used to analyze the impact of uncertainty on exchange rate volatility in the short and long run. The sample consists of 26 developed and emerging markets from 2005 to 2020.

The study finds that economic policy uncertainty significantly increases exchange rate volatility. Similarly, global financial market uncertainty leads to increased exchange rate volatility. The effect of US monetary policy uncertainty reduces exchange rate volatility.

This research contributes to the existing literature on exchange rate fluctuations by examining the impact of uncertainties on exchange rate volatility. The study uses novel news-based indices for measuring economic and monetary policy uncertainties and includes a broader sample of emerging and advanced markets. The findings have important implications for investors and policymakers.