Security Returns During Ex-Dividend Period

AbstractThis paper examines the security returns during ex-dividend period for firms listed on the Muscat Securities Market (MSM). We find stock dividends elicit a significant stock market response. In addition, the abnormal return seems not to be confined to the ex-day in Oman. In particular, the positive abnormal return extends for seven days after the stock dividend ex-day. We also find that larger firms in Oman prefer a higher trading range

THE EFFECTS OF WORK STRESS ON JOB SATISFACTION OF HEALTHCARE WORKERS IN A PUBLIC SECTOR HOSPITAL IN ALDAKHLIYA, OMAN

The role of healthcare workers is central to the modern healthcare system and was further highlighted during the COVID-19 pandemic situation. However, the healthcare workers did face a lot of work pressure during the pandemic which also had some negative consequences. In the present study, we investigated the effects of work stress and its five dimensions including the availability of resources, work environment, reward and incentive, functional relationship, and fear of catching COVID-19 on employee job satisfaction in the context of the public healthcare system in Oman. The sample is selected from a selected healthcare unit and data is collected using the survey-based method. The findings show that there are significant effects of two dimensions including functional relationships and work environments on healthcare job satisfaction. Based on the findings, it can be concluded that healthcare workers facing a lot of stress and this issue need greater managerial attention. Keywords: Work Stress, Job Satisfaction, Healthcare Workers, COVID-19 Pandemic

Dividend stability in a unique environment

Purpose – This paper aims to examine the stability of dividend policy using a unique data set. Design/methodology/approach – The paper is based on the Lintner model that is used to test the dividend smoothing behavior. The specific econometric method used for panel data is Tobit regression. Findings – The evidence shows that Omani firms adopt a policy of smoothing dividends. This stability of dividends does not support the predictions suggested by the high bank leverage, absence of taxes, and the variability of dividend payments in Oman. Research limitations/implications – This study highlights the need for further research in order to examine whether these results have any effect on dividend initiations and omissions in Oman. Practical implications – The findings of this study show that there are differences in dividend policies between the Omani companies and those in developed markets. Potential investors in the Omani market should be aware about these differences in making their investment decisions. Originality/value – This paper examines stability of dividend policy in a unique environment where firms distribute almost 100 percent of their profits in dividends, firms are highly levered mainly through bank loans, there are no taxes on dividends and capital gains, and there is variability in cash dividend payments. These factors suggest a diminished role of dividend stability in Oman. It is an empirical issue to examine whether this is indeed true. The authors are not aware of any other study on dividend stability using data with these unique factors.Dividends, Financial economics, Oman, Taxes

Tail dependence risk exposure and diversification potential of Islamic and conventional banks

International audienceThis paper undertakes a rolling window comparative analysis of risks for portfolios consisting of GCC Islamic and conventional bank indices. We draw our empirical results by employing canonical, drawable and regular vine copula models, as well as by implementing a portfolio optimization method with a conditional Value-at-Risk constraint. We find evidence of higher riskiness in the group of Islamic banks relative to the group of conventional banks across each of the financial rolling window scenarios under consideration. Specifically, a greater negative (nonlinear) tail asymmetric dependence is observed in the pairs of Islamic banks’ relationships. The results also show that the optimal portfolio model supports a clear preference towards the group of conventional banks in regard to risk minimization and diversification benefits

Can uncertainty indices predict Bitcoin prices? A revisited analysis using partial and multivariate wavelet approaches

This paper uses bivariate and multivariate wavelet approaches to revisit the co-movements between the Volatility Uncertainty Index (VIX) and Bitcoin (BTC). This is achieved by accounting for the impacts of the three major global factors, namely the U.S. Economic Policy Uncertainty Index (EPU), the Crude Oil Volatility Index (OVX), and the Geopolitical Risk Index (GPR). To do this, we use Wavelet Coherence (WC), Cross Wavelet Transform (CWT), Power Wavelet Coherence (PWC), and Multiple Wavelet Coherence (MWC) approaches. The results show that the BTC-VIX relationship varies across time and at high and low frequencies. Moreover, we find positive (or in-phase) co-movements between both variables while a negative co-movement (out-of-phase) is observed at both high and low frequencies. VIX news has a prediction power on BTC price returns over different frequencies. The results of PWC and MWC show that OVX, EPU, and GPR factors affect the BTC-VIX nexus under different frequencies. Finally, correlations between BTC-uncertainty indices are dependent upon investment horizons. The results of our research are of interest and importance to investors, portfolio managers, and policy-makers, as the results have practical applications to inform their decision-making. - 2019 Elsevier Inc.Scopu

Volatility forecasting, downside risk, and diversification benefits of Bitcoin and oil and international commodity markets: A comparative analysis with yellow metal

This study examines the diversification and hedging properties of Bitcoin (BTC) and gold assets for oil and S&P GSCI investors. We model and forecast the volatility performance of the pairs BTC–oil, gold–oil, BTC–S&P GSCI, and gold–GSCI using five bivariate DCC-GARCH family models, two popular forecasting measures (MSE and MAE), the Diebold and Mariano (1995) test, and different risk measures (value-at-risk, expected shortfall, semivariance, and regret) for different portfolios. We find that BTC and gold provide diversification benefits for oil and S&P GSCI. Moreover, by comparing the fitting and forecast performances of the five GARCH models, we find that the standard GARCH model is the best for the gold–oil and BTC–S&P GSCI pairs, while the HYGARCH model is the best for the BTC–oil and gold–S&P GSCI pairs regardless of the time horizon. Finally, we find strong evidence of hedging effectiveness and downside risk reductions, confirming the importance of BTC and gold in oil and S&P GSCI portfolio management.The last author acknowledges financial support from the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF- 2017S1A5A8019204 ). Appendix AScopu

Dynamic volatility transmission and portfolio management across major cryptocurrencies: Evidence from hourly data

This study used hourly data to examine the dynamic conditional correlations and hedging strategies in the main cryptocurrency markets: Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and Ripple (XRP). Multivariate generalized autoregressive conditional heteroskedasticity family models provided evidence of significant positive dynamic conditional correlations among these markets. A weaker conditional correlation was observed for the LCT-XRP portfolio than for the BTC-ETH portfolio, which had the highest correlation value. The dynamic correlations intensified after the cryptocurrency crisis. The results of a portfolio risk analysis suggested that investors should hold less BTC than LTC, ETH, and XRP to minimize risk while maintaining consistent expected portfolio returns. Investors should hold less BTC than the other cryptocurrencies during a crisis. In addition, the cheapest hedge strategy is to hold long BTC and short XRP regardless of the period. Holding long BTC and short LTC was found to be the most expensive hedge strategy. Finally, the study showed that an optimally weighted diversified portfolio provides the greatest reduction in risk and downside risk for ETH and LTC. For XRP, portfolio hedging is the best mechanism for reducing risk. 2020 Elsevier Inc.The last author (Sang Hoon Kang) achnowledges the financial support by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea ( NRF-2020S1A5B8103268 ).Scopu