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The purpose of this study is to investigate the relationship between selected board characteristics and ownership elements and the performance of firms listed in the Muscat Securities Market (MSM30). The examination focused on how the firm financial performance was affected by the board size, the number of board meetings and the ratio of the independent board of directors along to the ownership concentration types (i.e. institutional, state and concentrated individual ownership).

Data were extracted from the annual reports available online on the MSM30 website over a period of seven years (2009–2015). The sample consisted of 14 firms belonging to the non-financial sector. The data were of a balanced type and there were 98 observations. The analysis was conducted using the ordinary least square in STATA with the use of the robustness technique of standard error.

The findings of this study provide evidence that the selected elements for board characteristics and ownership influence firm performance. Nevertheless, such influence has its interpretation that differs to some extent from other securities markets in the developing countries. For instance, the ratio of the independent board of directors, the number of board director’s meetings, state ownership and concentrated individual ownership were inversely affecting the firm performance. However, institutional ownership and board size were found to have a positive effect on firm performance.

Studies on the influence of corporate governance and ownership structures in the context of Oman are still scarce. MSM30 received little attention, even though such an index encompasses the most liquid and the most profitable firms. MSM30 is an important index for investors in Oman looking for capital gains. Accordingly, this present study contributes to the knowledge body by providing new findings related to Oman and compares it with the other markets within Gulf Council Countries (GCC) and around the world. This will provide more understanding of the Omani context. Moreover, the authors anticipate that the outcomes of this research, which so far is the most comprehensive study in the Omani context in terms of the impact of corporate governance and ownership structure on firm financial performance can significantly shape corporate governance discourse, practices and policies in Oman, in particular, and in other GCC countries in general, to improve financial performance and corporate sustainability.

Given the rising need for measuring and controlling of financial risk as proposed in Basel II and Basel III Capital Adequacy Accords, trading risk assessment under illiquid market conditions plays an increasing role in banking and financial sectors, particularly in emerging financial markets. The purpose of this chapter is to investigate asset liquidity risk and to obtain a Liquidity-Adjusted Value at Risk (L-VaR) estimation for various equity portfolios. The assessment of L-VaR is performed by implementing three different asset liquidity models within a multivariate context along with GARCH-M method (to estimate expected returns and conditional volatility) and by applying meaningful financial and operational constraints. Using more than six years of daily return dataset of emerging Gulf Cooperation Council (GCC) stock markets, we find that under certain trading strategies, such as short selling of stocks, the sensitivity of L-VaR statistics are rather critical to the selected internal liquidity model in addition to the degree of correlation factors among trading assets. As such, the effects of extreme correlations (plus or minus unity) are crucial aspects to consider in selecting the most adequate internal liquidity model for economic capital allocation, especially under crisis condition and/or when correlations tend to switch sings. This chapter bridges the gap in risk management literatures by providing real-world asset allocation tactics that can be used for trading portfolios under adverse markets’ conditions. The approach to computing L-VaR has been arrived at through the application of three distinct liquidity models and the obtained results are used to draw conclusions about the relative liquidity of the diverse equity portfolios.

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.

The purpose of this paper is to originate a proactive approach for the quantification and analysis of liquidity risk for trading portfolios that consist of multiple equity assets.

The paper presents a coherent modeling method whereby the holding periods are adjusted according to the specific needs of each trading portfolio. This adjustment can be attained for the entire portfolio or for any specific asset within the equity trading portfolio. This paper extends previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple‐assets' liquidity‐adjusted value‐at‐risk matrix. The key methodological contribution is a different and less conservative liquidity scaling factor than the conventional root‐t multiplier.

The proposed coherent liquidity multiplier is a function of a predetermined liquidity threshold, defined as the maximum position which can be unwound without disturbing market prices during one trading day, and is quite straightforward to put into practice even by very large financial institutions and institutional portfolio managers. Furthermore, it is designed to accommodate all types of trading assets held and its simplicity stems from the fact that it focuses on the time‐volatility dimension of liquidity risk instead of the cost spread (bid‐ask margin) as most researchers have done heretofore.

Using more than six years of daily return data, for the period 2004‐2009, of emerging Gulf Cooperation Council (GCC) stock markets, the paper analyzes different structured and optimum trading portfolios and determine coherent risk exposure and liquidity risk premium under different illiquid and adverse market conditions and under the notion of different correlation factors.

This paper fills a main gap in market and liquidity risk management literatures by putting forward a thorough modeling of liquidity risk under the supposition of illiquid and adverse market settings. The empirical results are interesting in terms of theory as well as practical applications to trading units, asset management service entities and other financial institutions. This coherent modeling technique and empirical tests can aid the GCC financial markets and other emerging economies in devising contemporary internal risk models, particularly in light of the aftermaths of the recent sub‐prime financial crisis.

This paper aims to empirically test, from a regulatory portfolio management standpoint, the application of liquidity-adjusted risk techniques in the process of getting optimum and investable economic-capital structures in the Gulf Cooperation Council financial markets, subject to applying various operational and financial optimization restrictions under crisis outlooks.

The author implements a robust methodology to assess regulatory economic-capital allocation in a liquidity-adjusted value at risk (LVaR) context, mostly from the standpoint of investable portfolios analytics that have long- and short-sales asset allocation or for those portfolios that contain long-only asset allocation. The optimization route is accomplished by controlling the nonlinear quadratic objective risk function with certain regulatory constraints along with LVaR-GARCH-M (1,1) procedure to forecast conditional risk parameters and expected returns for multiple asset classes.

The author’s conclusions emphasize that the attained investable economic-capital portfolios lie-off the efficient frontier, yet those long-only portfolios seem to lie near the efficient frontier than portfolios with long- and short-sales assets allocation. In effect, the newly observed market microstructures forms and derived deductions were not apparent in prior research studies (Al Janabi, 2013).

The attained empirical results are quite interesting for practical portfolio optimization, within the environments of big data analytics, reinforcement machine learning, expert systems and smart financial applications. Furthermore, it is quite promising for multiple-asset portfolio management techniques, performance measurement and improvement analytics, reinforcement machine learning and operations research algorithms in financial institutions operations, above all after the consequences of the 2007–2009 financial crisis.

While this paper builds on Al Janabi’s (2013) optimization algorithms and modeling techniques, it varies in the sense that it covers the outcomes of a multi-asset portfolio optimization method under severe event market scenarios and by allowing for both long-only and combinations of long-/short-sales multiple asset. The achieved empirical results, optimization parameters and efficient and investable economic-capital figures were not apparent in Al Janabi’s (2013) paper because the prior evaluation were performed under normal market circumstances and without bearing in mind the impacts of the 2007–2009 global financial crunch.

The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance with their purpose. The aim of this study is to show whether there is a relationship between transparency and market efficiency.

Correlation analysis has been conducted between prediction accuracy rates, which are obtained by seven different machine learning algorithms and Corruption Perception Index (CPI) levels.

It has been statistically shown that the indices of countries with low corruption levels are harder to predict, which, in turn, can be interpreted as having higher weak-form market efficiency. According to that, an intermediate negative correlation has been found between CPI scores and predictability levels of stock indices. Considering the findings, it can be interpreted that the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency.

The study can be extended with cutting-edge machine learning and deep learning techniques in future studies. There are very few studies which try to explain factors related to market efficiency. Thus, the authors claim that there is still room for further research in order to determine the factors related to market efficiency, implying that current literature is still far from explaining the causation behind the inefficiencies.

According to findings, the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency. Based on these findings, in practice, it can be said that more successful predictions can be made using machine learning algorithms in countries with relatively lower CPI scores.

In literature, the factors related to market efficiency are still far from explaining the causation behind the inefficiencies. Thus, it has been investigated whether transparent and well-functioning public institutions and organizations have any relation with market efficiency.

The study aims to examine how the information disclosed by the managers in the management discussion and analysis (MD&A) reports varies at the different levels of corporate performance.

To understand this quantile effect, first OLS technique was adopted and then, the quantile regression method was applied to explore the impact of MD&A disclosures on the firm performance across the lower and upper quantiles. The sample size for the study is 490 firms’ year observations for the period 2016–2022.

The results of the study demonstrate the negative but significant relationship between MD&A disclosures and corporate performance, supporting the two management strategies of “competitive disadvantage” in case of good performance and “management impression strategy” in case of poor performance. Furthermore, with other corporate governance variables, both the size of the board and the number of independent directors on the board are positively significant only in the case of the upper quantile indicating the heterogeneity in the relationship between the performance and the MD&A disclosures. Therefore, the overall findings of the study support that these results contradict the agency theory and the stakeholders’ theory as managers are not acting well as agents on behalf of the investors and work well only when they are controlled by the large board having more independent directors.

To the best of the authors’ knowledge, no study so far has incorporated quantile regression to assess the effect of MD&A disclosures on company performance at various levels of the firm performance, which gives more robust insights about the viewpoint of the managers on the different level of the firm performance. In other words, this study highlights the important information as to how the information provided in the MD&A reports varies as per the good or poor performance of the companies.

This study aims to examine the influence of ownership structure and board characteristics on the performance of Indonesian Islamic rural banks (IRB) using the system generalized method of moment model.

This research uses Indonesian IRB unbalanced annual panel data from 2016 to 2022. IRB performance is measured by return on assets (ROA), return on equity (ROE) and nonperforming financing (NPF). The ownership structure is represented by controlling shareholders, ownership of the board of directors (BD) and ownership of the board of commissioners (BC). Meanwhile, board characteristics are represented by the size of the BC, the proportion of female board directors and female president directors.

The results show that the ownership structure and board characteristics play an important role in improving the IRB’s performance. Technically, the results show that the size of the BC and the ownership of the BD increase all IRB performance measures. Female president directors and controlling shareholders improve IRB’s performance as measured by ROA and ROE. Women’s boards of directors improve IRB performance as measured by NPF. Meanwhile, the ownership of the BC does not show its effect on all IRB performance measures.

This study fills a literature gap on the influence of ownership structure and board characteristics on IRB Indonesia’s performance. In addition, it adds understanding and insight for Islamic bank regulators, management and IRB depositors in Indonesia.

To the best of the authors’ knowledge, this study is one of the first to provide an empirical survey on the influence of controlling shareholders and board characteristics on IRB performance, particularly in Indonesia.

This study aims to examine the effect of social reputation on the relationship between boards and foreign ownership on the quality of sustainability disclosure.

The sample of this study consists of publicly-traded primary and secondary sector companies in Indonesia for 12 years, from 2009 to 2020. This study uses panel model regression to generate its results. The disclosure data are hand-collected data sourced from annual financial and company sustainability reports.

Higher foreign board component companies report lower quality of sustainability disclosure, whereas companies that possess foreign ownership components report a higher quality of sustainability disclosure. This result is strengthened by obtaining consistent results tested with economic, social and environmental disclosure components. In addition, if the company has a good social reputation, it will strengthen the relationship of foreign ownership to the quality of sustainability disclosure.

These findings are relevant for policymakers, professional organizations and practitioners in Indonesia and other developing countries.

The moderating effect of social reputation on the relation of the foreign board and foreign ownership-quality of sustainability disclosure as this study does remain rare in developing countries. This study complements various research conducted in developing countries, such as Indonesia, by offering a new dimension. The results indicate that social reputation has a moderating role in determining the impact of foreign ownership on the quality of sustainability disclosure.

This study aims to examine whether the age and tenure of the chair of the board of directors are related to research and development (R&D) investment in China.

This study uses A-share manufacturing firms that traded on the Shanghai and Shenzhen stock exchange between 2009 and 2018. This study uses OLS regressions, controls for self-selection bias, and uses an instrumental variable to alleviate the concern of endogeneity.

This study finds that chair tenure has a negative relationship with R&D investment. This study does not find a significant relationship between chair age and R&D investment.

This study contributes to corporate governance and strategic management literature by highlighting chair tenure as a new factor affecting R&D investments. It also adds a significant contribution to the limited literature on the chair’s role in strategic decisions. Moreover, companies that are eager to strengthen corporate governance and maintain sustained innovation may reconsider the chair tenure. Given that many proposals for board governance reform explicitly stress the importance of limiting board tenure, this study contributes to policymakers by providing evidence in support of these proposals.