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This paper aims to analyse the weekday effect on the Nifty Shariah indices as per the Islamic calendar. The study is intended to know about the return and volatility of these indices during Ramadhan and non-Ramadhan days.

The study focuses on analysing the Nifty Shariah indices and Sensex daily returns collected from NSE India and BSE India, respectively, during the period of 1 August 2016 to 31 July 2022. Descriptive statistics are used to analyse the data, while the Ordinary Least Square method is used to determine the impact of weekdays on the Nifty Shariah indices. Additionally, the study applies the GARCH statistical model to examine the influence of Ramadhan on the returns and volatility of the Nifty Shariah indices.

All of the Nifty Shariah indices produced positive returns during the overall sample period. According to the study, Tuesday index returns outperform other weekdays. The GARCH model indicated that the coefficient values for the Nifty 50 Shariah and Nifty 500 Shariah indices were negative. Ramadhan has a strong negative effect on volatility, according to this study.

The outcomes of the research are beneficial for investors aiming to exploit daily or weekly price fluctuations, rather than pursuing extended investment periods. Furthermore, fund managers can employ these findings to shape trading strategies, and academics can examine the performance of Shariah indices in the Indian context. This enables devout investors to make significant financial choices, thus advancing ethical values in society and upholding standards of both public and private morality.

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

We show that our extended model yields a Pareto efficient outcome.

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Long-term modelling and sustainability can be modelled in our setting.

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

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.

This study examines the impact of debt maturity structure on stock price crash risk (SPCR) in Asian economies and the moderating effect of firm age on this relationship.

The study utilized annual data from 432 nonfinancial firms publicly listed in six Asian countries: China, Hong Kong, Japan, Singapore, Pakistan and India. The observation period covers 14 years, from 2007 to 2020. The sample was categorized into three groups: the entire sample and one group each for developing and developed Asian economies. A generalized least squares panel regression method was employed to test the research hypotheses.

The results suggest that long-term debt has a significant negative influence on SPCR in Asian economies, indicating that firms with high long-term debt experience lower future SPCR. Moreover, firm age negatively moderates this relationship, implying that older firms may experience a more pronounced reduction in SPCR due to high long-term debt. Finally, firms in developed Asian economies with high long-term debt are more effective in mitigating the risk of a significant drop in their stock prices than firms in developing Asian economies.

This study contributes to the literature in several ways. To the best of the researcher’s knowledge, this is the first of such efforts to investigate the relationship between debt maturity structure and crash risk in Asia. Additionally, it reveals that long-term debt influences SPCR directly and indirectly in Asia through the moderating role of firm age. Lastly, it is likely one of the first studies by a research team in Asia to compare the nonfinancial markets of developed and developing Asian countries.

Sub-Saharan African (SSA) region has been battling illegal outflow of capital over the years, with little success recorded so far. Without adequate attention, unemployment, infrastructure deficiencies and inefficient capital might be worse in the future. The purpose of this study is to investigate if institutional quality mitigates the effect of capital flight (CF) on economic growth.

The panel data from 26 SSA countries spanning 1998 to 2018 are used. The analysis of this study was carried out through a two-step generalized method of moments technique. The principal component index is used to group the institutional quality/governance indicators into three categories: political governance, economic governance and institutional governance.

The study found that CF is harmful to the economic growth of the SSA region. The study also found that, among the indicators of institutional quality, only the rule of law and control of corruption stimulate economic growth. Contrary to expectation, the finding indicates that institutional quality does mitigate the effect of CF on economic growth in the SSA region.

This study provides an insight into the relevance of institutional quality in mitigating CF in sub-Saharan African region.

Magnet effect entails a hypothesis in market microstructure entailing a systemic likelihood of prices being sucked toward the theoretical threshold. The purpose of this paper is to investigate the existence of magnet effect in Bursa Malaysia via overnight returns.

This study investigates the existence of magnet effect via overnight returns in Bursa Malaysia by utilizing historical daily price data from 1994 to 2017 by probabilistic regression approaches. The authors divide the study period into three distinct regimes based on regulatory limit mechanisms.

Based on demarcated regimes, the authors find evidence of magnet effect in Bursa Malaysia throughout all regimes, with a heightened magnitude detected between 2002 and 2013. Moreover, upper limit scenarios exhibit a greater propensity for magnet effect. The authors end the paper with implications of the findings for portfolio managers, intraday traders, and policymakers.

The research is the first of its kind in attempting to measure the magnet effect in Malaysia via overnight jumps.

The article deals with the imperatives of functioning of the financial market of Ukraine in the global space of debt loading.

Within the Laffer debt curve model, the dependence of gross domestic product (GDP) change on the level of debt of the financial system for countries that form the economic core in the global financial space and well control the level of the indicator, as well as new member states that have a different level of secure debt loading and affect the portion of the financial market that forms a portfolio of securities to cover the cost of nonperforming government securities is mentioned.

It has been shown that stock indices, as constituent indicators of changes in the price environment of a certain group of securities in time space, allow to estimate the general direction of the market movement even when prices within the index basket change in different directions.

The dynamics of changing the debt loading of the financial system of Ukraine in the current, medium-term perspective is analyzed. The amount of the fixed and floating rate debt of the government internal securities is determined to ensure the diversification of interest rate risk. Using the parameters of the model of approximation functions of dimensionless quantities, the corridor of a safe level of general government debt in the country was determined.

The purpose of this paper is to study the following: short-run and long-run associations between the terror-affected country’s stock market index and other global countries’ equity indices and gold; the volatility of stock market indices when one of the countries is affected by a terrorist attack; and the linkages between terrorism and the returns in the selected stock markets.

To study the impact of the Taj attack on other global indices, the authors selected top five countries’ stock market indices, namely, FTSE, DJI, NIKKEI, SSEC and DAX. The short-run and long-run associations are also compared with gold. The authors used the autoregressive distributed lag model, LM test and bounds test for analyzing the short-run and long-run impact; ARCH family models to study the volatility impact; and the MAR model to study the impact on returns.

The authors found that all the global indices had a short-run association with the terror-affected country’s benchmark index, i.e. BSE. Gold moved as expected, with it having a short-run impact on the terror-affected country. All the global indices except DJI have volatility of share price movement either positively or negatively. As the benchmark of the terror-affected country fell, NIKKEI, HSI, IXIC, DAX and CAC also fell; that is, it had a positive influence on the terror-affected country’s index. Post the Mumbai attacks, DJI, NIKKEI, SSEC, DAX, BSE and CAC performed well in performance measure returns compared with the pre-attack period. Whereas, FTSE and GOLD performed well in performance measure returns in the pre-attack period compared with the post-attack period. GOLD proved that it is the best avenue to invest in, as it has only a short-term association with the terror-affected country’s index.

The authors studied the short-run and long-run associations with only five countries’ benchmark indices.

The authors found that all the global indices had long- and short-run associations with the terror-affected country’s benchmark index, i.e. BSE. Global indices like DJI, NIKKEI, SSEC, DAX and FTSE had a short-term association with the affected country’s index. Gold moved as expected, with it having a short-run impact on the terror-affected country. All the global indices except DJI have volatility of share price movement either positively or negatively. As the benchmark of the terror-affected country fell, NIKKEI, HSI, IXIC, DAX, TSX, BVSP and CAC also fell; i.e., it had a positive influence on the terror-affected country’s index. Post the Mumbai attacks, DJI, NIKKEI, SSEC, DAX, BSE and CAC performed well in performance measure returns compared with the pre-attack period. Whereas, FTSE and GOLD performed well in performance measure returns in the pre-attack period compared with the post-attack period. GOLD proved that it is the best avenue to invest in, as it has only a short-term association with the terror-affected country’s index. In all the relationships were mixed with respect to terror attacks, and GOLD took the lead run out of all the associations it had in the 16-year time span from 2000 to 2016.

The research has got an important implication to the investors. It shows that patience is the key, as all the indices had only short-term associations with the BSE. It implies that investors’ returns will be negative in the short run, but if they continue investing, in the long run, the impact of terrorism tapers out and the returns will increase.

There is a lot of research done on the impact of the US attacks on the stock markets of other countries, but on the impact of the Taj attack in India, there is hardly any research.

The stock market has shown fluctuating degrees of volatility because of the recent COVID-19 pandemic in India. The present research aims to investigate the effect of the COVID-19 on the stock market volatility, and whether the economic package can control the market volatility or not, measured by a set of certain sector-level economic features and factors such as resilience variables.

We examine the correlation matrix, basic volatility model and robustness tests to determine the sector-level economic features and macroeconomic factors helpful in diminishing the volatility rising because of the COVID-19.

The outcomes of this study are significant as policymakers and financial analysts can apply these economic factors to set policy replies to handle the unexpected fluctuation in the stock market in sequence to circumvent any thinkable future financial crisis.

The originality of the paper is to measure the variables affecting the stock market volatility due to COVID-19, and understand the impact of capital market macroeconomic variables and dummy variables to theoretically explain the COVID-19 impact on stock market volatility.

The study aims to pose the question: Has lending to small businesses been a source of increased risk in microfinance institutions (MFIs)? This question is pertinent given the higher levels of perceived riskiness of lending to small business operators owing to their opacity.

The study accommodates panel bias by using system generalised method of moments (GMM) estimators on micro-level data from 2004 to 2014.

Study findings indicate that lending to small businesses by MFIs does not affect credit and insolvency risk in these institutions. However, using disaggregated data, there is evidence that lending to small businesses by cooperatives significantly reduces their insolvency risk exposure. Conversely, lending to small business by micro-banks, cooperatives, non-bank financial institutions and non-governmental organizations does not significantly affect their risk exposure.

These findings imply that the technologies that have been used by MFIs in lending to small enterprises have helped them mitigate the problems of adverse selection and moral hazard.

Information economics theory postulates that small firms are excluded from formal financial markets owing to their opacity. The hypothesis has not attracted much empirical research interest; hence, this study aims to bridge this gap in knowledge.