Search results

This study investigates the dynamic interdependence between Islamic and conventional stock markets in the Gulf Cooperation Council (GCC) economies and the influence of global financial uncertainties on this interconnection.

The study employs the time-varying parameter vector autoregressions (TVP-VAR) technique and analyzes daily data from December 1, 2008 to July 14, 2021.

The research reveals robust interconnectedness within individual countries between Islamic and conventional stock markets, particularly during crises. Islamic stock markets exhibit greater susceptibility to spillover effects compared to conventional stocks. The UAE and Kingdom of Saudi Arabia (KSA) stock markets are identified as net transmitters of spillovers, while Oman, Bahrain and Kuwait receive more spillovers than they transmit. Global financial uncertainty measures (GVZ, USEPU and UKEPU) positively influence financial market interconnectedness, with EVZ exhibiting a negative impact while VIX and OVX remain statistically insignificant.

Investors and portfolio managers in Oman, Bahrain and Kuwait should carefully evaluate the UAE and KSA markets before making investment decisions due to the latter's role as net transmitters in the region. Additionally, it is emphasized that Islamic and conventional stocks should not be considered interchangeable asset classes for risk hedging.

Investors must be aware that Islamic and conventional stocks cannot be used as an alternative asset class to hedge risk.

The present article offers valuable insights for practitioners and researchers delving into the comparative analysis of Islamic and conventional stock markets within the GCC context. It enhances our comprehension of the dynamic interdependence between Islamic and conventional stock markets in the GCC economies and the impact of global financial uncertainties on this intricate relationship.

This study aims to elucidate the volatility spillovers among commodities, equities and socially responsible investments, underpinning their dynamic correlations during the economic instability wrought by the COVID-19 pandemic and associated financial crises.

This research quantitatively analyzes volatility transmission across various financial assets from January 2005 to October 2020 by employing the Diebold and Yilmaz (2012) spillover index. The methodology incorporates a temporal examination to capture the evolution of volatility dependencies pre and post the emergence of COVID-19.

The findings indicate substantial volatility spillovers among the assets in question, aligning with the current financialisation of commodity markets and a rise in financial market integration. These spillovers also show variation over time. Notably, the interconnectedness among the assets intensifies during periods of stress. For instance, the total spillover index significantly surpassed 80% toward the end of January 2020, following the onset of the COVID-19 crisis. Furthermore, the results imply that financial markets appear to be segmented.

The findings afford investors a more comprehensive insight into both the character and scale of the interdependencies across a broad array of financial markets. Indeed, grasping the extent to which financial markets are segmented or integrated during times of stress and stability is crucial for investors. Such understanding is key to more accurately evaluating risks, diversifying investment portfolios and devising more efficient hedging strategies.

This study contributes to financial literature by offering a comprehensive investigation into the spillover effects across a diverse set of asset classes during an unprecedented global health crisis, filling a gap in existing research on market behavior against the backdrop of a pandemic-induced financial crisis.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

The authors compare sentiment level with sentiment shock from different angles to determine which measure better captures the relationship between sentiment and stock returns.

This paper examines the relationship between investor sentiment and contemporaneous stock returns. It also proposes a model of systems science to explain the empirical findings.

The authors find that sentiment shock has a higher explanatory power on stock returns than sentiment itself, and sentiment shock beta exhibits a much higher statistical significance than sentiment beta. Compared with sentiment level, sentiment shock has a more robust linkage to the market factors and the sentiment shock is more responsive to stock returns.

This is the first study to compare sentiment level and sentiment shock. It concludes that sentiment shock is a better indicator of the relationship between investor sentiment and contemporary stock returns.

This study examines the extreme quantile connectedness and spillovers between West Texas Intermediate (WTI) crude oil futures and ten Vietnamese stock market sectors. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors employ the extreme quantile connectedness methodology of Ando et al. (2022).

Initial results show that the size of spillovers is higher during bearish markets than bullish markets and under major financial, political, energy and pandemic events. The oil market is a net receiver of spillovers during downward markets and net contributors during upward markets. The banking sector is a net contributor of spillovers, whereas consumer discretionary and consumer staples are net receivers for different quantiles. The role of the remaining sectors as net receivers/contributors is sensitive to the quantiles. Oil has a large spillover effect on the electricity sector for all quantiles. Comparing all crises, oil offers the best hedging effectiveness to the Vietnamese sector during the coronavirus disease 2019 (COVID-19) crisis. Moreover, oil was a cheap hedge asset during oil crises. Finally, oil provides the highest hedging effectiveness for healthcare during the global financial crisis (GFC) and consumer staples during the European debt crisis (EDC), oil crisis and COVID-19.

Acknowledging the presence of heterogeneity in the relation between oil and economic sectors under different market conditions, this study is the first to examine the extreme quantile connectedness between oil and Vietnamese sectors.

To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia and Ukraine.

The study utilizes the “dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH)” approach of Gabauer (2020). The volatility of the markets is calculated following the approach of Parkinson (1980). The sample dataset comprises the daily volatility of the stock and exchange markets for 35 months, from November 2019 to September 2022.

The study confirms the existence of contagion effects among member countries. Volatility spillover between exchange and stock markets is low within the country but substantial across borders. Russian contribution increased significantly during the conflict with Ukraine, and other countries also witnessed a surge in the spillover index during the pandemic and war.

It adds to the body of literature by emphasizing the necessity of comprehending the economies' behavior and interdependence. Offers insightful information to decision-makers who must be more watchful regarding the financial crisis and its regional spillover.

The study is the first to explore the contagion of volatility among the BRICS countries during the two biggest crisis periods of the decade.

The aim of this paper is threefold: (1) to develop a new measure of investor sentiment rational (ISR) of developing countries by applying principal component analysis (PCA), (2) to investigate co-movements between the ten developing stock markets, the sentiment investor's, exchange rates and geopolitical risk (GPR) during Russian invasion of Ukraine in 2022, (3) to explore the key factors that might affect exchange market and capital market before and mainly during Russia–Ukraine war period.

The wavelet approach and the multivariate wavelet coherence (MWC) are applied to detect the co-movements on daily data from August 2019 to December 2022. Value-at-risk (VaR) and conditional value-at-risk (CVaR) are used to assess the systemic risks of exchange rate market and stock market return in the developing market.

Results of this study reveal (1) strong interdependence between GPR, investor sentiment rational (ISR), stock market index and exchange rate in short- and long-terms in most countries, as inferred from (WTC) analysis. (2) There is evidence of strong short-term co-movements between ISR and exchange rates, with ISR leading. (3) Multivariate coherency shows strong contributions of ISR and GPR index to stock market index and exchange rate returns. The findings signal the attractiveness of the Vietnamese dong, Malaysian ringgits and Tunisian dinar as a hedge for currency portfolios against GPR. The authors detect a positive connectedness in the short term between all pairs of the variables analyzed in most countries. (4) Both foreign exchange and equity markets are exposed to higher levels of systemic risk in the period of the Russian invasion of Ukraine.

This study provides information that supports investors, regulators and executive managers in developing countries. The impact of sentiment investor with GPR intensified the co-movements of stocks market and exchange market during 2021–2022, which overlaps with period of the Russian invasion of Ukraine.

The existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach.

Applying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed.

Interestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market.

Overall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

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.