Market turbulences and their impact on the financial market, particularly on the stock market, is a financial topic that has received significant research attention recently. This study compared the characteristics of stock return and volatility in selected developed and emerging markets between the 2008 financial crisis and the 2019 worldwide pandemic. In this sense, we seek to answer two concerns. First, do the developed and emerging markets behave similarly during crisis periods? Second, does economic strength always shield markets from poor economic circumstances? For this purpose, the daily return data of E7 (Emerging 7) and G7 (Developed 7) countries for two sample periods—namely, the financial crisis period of 2007–2009 and the global pandemic period of 2019–2021—were chosen. By using univariate GARCH models, namely GARCH, EGARCH, and TGARCH, the study discovered that developing and developed markets reacted differently to these two financial crises. While emerging markets responded similarly to these two crises, developed economies acted differently, being more volatile and sensitive to the worldwide pandemic of 2019 than the financial crisis of 2008. Moreover, a country’s economic prowess does not always shield it from economic turmoil. This study will help investors identify diversification opportunities among the developed and emerging markets during a crisis period. Additionally, this will help portfolio and fund managers understand the behaviour of stock markets during times of market crisis and thus give advice to investors.

The aim of this study was to evaluate whether trading experience reduces exposure to heuristic-driven biases, namely availability bias, anchoring and adjustments bias, representativeness bias, and confirmation biases of individual investors operating in the Indian stock market, through the moderating role of the Big Five personality traits. To achieve these research objectives, primary data were collected through a structured questionnaire. The sample consisted of 408 individual investors trading on the Indian stock market, who were selected on a convenient basis. Confirmatory factor analysis and Cronbach’s alpha were used to measure the validity and reliability of the data. Further analysis was conducted using Pearson’s correlation and multiple regression. The results of this study prove that increased trading experience does not always reduce the susceptibility to heuristic biases. Increased trading experience reduces the susceptibility to availability, and anchoring and adjustment heuristics of individual investors operating on the Indian stock market. The present study has some relevant implications for investors, portfolio managers, financial advisors, and other interested persons in the stock market.

The past few years have witnessed renewed interest in modelling and forecasting asymmetry in financial time series using a variety of approaches. The most intriguing of these strategies is the “asymmetric” or “leverage” volatility model. This study aims to conduct a review of asymmetric GARCH models using bibliometric analysis to identify their key intellectual foundations and evolution, and offers thematic and methodological recommendations for future research to advance the domain. Bibliometric analysis was used to identify patterns in and perform descriptive analysis of articles, including citation, co-authorship, bibliographic coupling, and co-occurrence analysis. The study located 856 research papers from the Scopus database between 1992 and 2021 using key phrase and reference search methods. Publication trends, most influential authors, leading countries, and top journals are described, along with a systematic review of highly cited articles. The study summarises the development, application, and performance evaluation of asymmetric GARCH models, which will help researchers and academicians significantly contribute to this literature by addressing gaps.

The study examines the time-varying correlation and return spillover mechanism among developed (U.S.) and emerging (BRIC) stock markets during major crises from 2000 to 2023, namely the global financial crisis, COVID-19, and the Russia–Ukraine war. To do so, we used dynamic conditional correlation (DCC-GARCH) and time-varying parameter vector autoregression (TVP-VAR) models. This study finds that the nature of market crises plays a significant role in the interrelationship and return spillover mechanisms among the U.S. and BRIC stock markets. The interconnectedness of the stock markets was strengthened by crises such as the GFC and the COVID-19 pandemic. On the other hand, the Russia–Ukraine war temporarily disrupted the interrelationships between the markets. The study yields valuable insight to local and international investors in portfolio diversification and risk management strategies during market turbulence.