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Stock market performance is paramount to every country, as it signifies economic growth, business performance, wealth maximization, savings deployment and consumer confidence. This study investigates the disparities in the market performance of listed firms in Romania. This study also examines whether the COVID-19 crisis affected market performance.

The data were collected from 69 firms listed on the Bucharest Stock Exchange (BSE) from 2018 to 2022, belonging to 11 sectors. This study used several methods to achieve its objectives. Difference tests were considered to analyze the performance of Romanian companies before and during the COVID-19 crisis, as well as across sectors. Regression analysis was also conducted to estimate the effect of the COVID-19 crisis and classification type on Romanian companies' performance. Additional analyses were performed to verify the findings of the present study.

The study’s findings indicate a clear difference in market performance between the pre-crisis and crisis periods. The COVID-19 pandemic had an adverse and significant impact on market performance. However, after the market contraction in the early stage of the COVID-19 pandemic outbreak, the stock market outperformed the pre-pandemic capitalization levels and the regional and global indices evolution. Furthermore, there was a difference in market performance across sectors. In particular, the communication services sector has specifically demonstrated accelerated growth.

This research examines the variation in the market performance of companies before and during the COVID-19 pandemic and across different sectors. It also provides evidence of the potential impact of COVID-19 on firms' market performance. This research contributes to a better understanding of how sectors perform during times of crisis.

The purpose of this paper is to test the existence of stylized facts, such as the volatility clustering, heavy tails seen on financial series, long-term dependence and multifractality on the returns of four real estate indexes using different types of indexes: conventional and Islamic by comparing pre and during COVID-19 pandemic.

Firstly, the authors examined the characteristics of the indexes. Secondly, the authors estimated the parameters of the stable distribution. Then, the long memory is detected via the estimation of the Hurst exponents. Afterwards, the authors determine the graphs of the multifractal detrended fluctuation analysis (MF-DFA). Finally, the authors apply the WTMM method.

The results suggest that the real estate indexes are far from being efficient and that the lowest level of multifractality was observed for Islamic indexes.

The inefficiency behavior of real estate indexes gives us an idea about the prediction of the behavior of future returns in these markets on the basis of past informations. Similarly, market participants would do well to reassess their investment and risk management framework to mitigate new and somewhat higher levels of risk of their exposures during the turbulent period.

To the authors’ knowledge, this is the first real estate market study employing STL decomposition before applying the MF-DFA in the context of the COVID-19 crisis. Likewise, the study is the first investigation that focuses on these four indexes.

This study aims to systematically review the literature in the fields of liquidity, informational efficiency and default risk. The authors outline the key research streams and provide possible pathways for future research.

The study adopts bibliographic mapping to identify the most influential studies in the research fields of liquidity, informational efficiency and default risk from 1984 to 2021.

The study identifies four key research themes that include efficiency and transparency of markets; corporate yield spreads; market interactions: bonds, stocks and cryptocurrencies; and corporate governance. By assessing publications published from 2018 to 2021, the authors also document seven key emerging research trends: cross markets, managerial learning and corporate governance, state ownership and government subsidies, international evidence, machine learning (FinTech approaches), environmental themes and financial crisis. Drawing on these emerging trends, the authors highlight the opportunities for future research.

Keyword searches have limitations since some studies might be overlooked if they do not match the specified search criteria, even though their relevance to the topic is under investigation. Adopt the R project to expand this review by incorporating more literature from other databases, such as the Scopus database could be a possible solution.

The four key research streams contribute to a comprehensive understanding of liquidity, informational efficiency and default risk. The emerging trends integrate existing knowledge and leave the chance for innovative research to expand the research frontier.

This study fulfills the systematic literature review streams in the fields of liquidity, informational efficiency and default risk, and provides fruitful opportunities for future research.

This paper investigates the stock market reaction to three different events related to the UEFA Champions League – the announcements of draws, odds and match results. The aim of the paper is to test whether these events are informative for stock market operators, i.e. whether they produce abnormal returns.

Applying the event study methodology, the authors investigate the stock market reaction before (at two events: the draw date and on the release of betting odds) and after the matches of 11 listed soccer teams in the period 2003–2019. The authors also conduct OLS regression analyses in order to disentangle the impact of firm specific variables and match characteristics on cumulative abnormal returns.

This paper finds that match outcomes affect the stock market performance of listed teams, while the announcements of draws and odds do not. More specifically, the market does not consider match outcomes involving wins and ties as informative events, while it penalizes losing teams. Moreover, investor reactions to events related to the UCL competition depend more on match characteristics than on company specific variables.

The study enriches the ongoing debate about the impact of soccer team results on stock market performance in several ways: using the widest time span ever adopted in this area; focusing on UCL, which is the most important soccer competition played by private clubs; disentangling for the first time the effects of draws, odds release and sporting outcome on stock returns of listed soccer clubs.

This paper aims to establish a service efficiency-oriented framework for training design and evaluation as a pivotal service procedure in the workplace to fill the gap between training and organizational performance in a service context.

A semi-structured interview was first employed to confirm the primary indicator for training programs and criteria design as the pivotal factor for operational efficiency. An observation experiment was subsequently conducted to reveal that the training program can be redesigned according to the concrete operation effects and influencing factors for operational efficiency in the workplace.

The proposed service efficiency-oriented training model is suggested to underline and guide the activities for training requirements, training methods, training criteria and training evaluation for the service sector. Training auditing, analyzing and redesigning based on service efficiency could help to integrate service efficiency so that service organizations can readjust their specific training needs and concise the training program in the human resource management practice.

This study only conducted an on-site observational experiment on one of the casinos in Macau. An observational method assessed the conceptual model in the context of table game operations. More quantitative approaches like AI-assisted systems may be employed in the future. The representativeness of the sample is somewhat limited. In addition, the service efficiency-oriented training concept model is an open system that any organization could extend by incorporating more elements in each part that can be developed to meet their human resource management needs. Finally, other service-oriented organizations like airlines and banks can learn from the theoretical model proposed in this article. It is suggested that non-profit organizations would be a better research area.

The finding can provide organizations and practitioners with insights and tools on how to provide and evaluate service efficiency and assess employee performance.

The proposed service efficiency-oriented training model provides a theoretical foundation for training and organizational performance for service organizations.

This study is the first to develop a service efficiency-oriented training framework with training needs, methods, criteria and evaluation. A service industry sample was used to verify the framework in the context of casino game pace and dealer training for table games. Suggestions for a combination of management are provided for casino operators to redesign and evaluate the dealer training program for service improvement.

House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.

We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.

Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.

We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.

To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.

The study examines the relationship between news intensity, media sentiment and market microstructure invariance-implied measures of trading activity and liquidity of Chinese property developer stocks during the 2020–2022 Chinese property sector crisis.

The authors adopt the extension of the news article invariance hypothesis, which is a generalization of the market microstructure invariance conjecture, from January 2020 to January 2022 to test specific quantitative relationships between the arrival rate of public information, trading activity and a nonlinear function of a proxy for the probability of informed trading. Empirical tests are based on a dataset of 22,412 firm-day observations and two count-data models to correct for overdispersion and the excess number of zeros. Seventy-five stocks of Chinese companies from the property development industry (including the China Evergrande Group) were included in the sample.

The authors reject the news article invariance hypothesis but document a positive and significant relationship between the flow of public information and risk liquidity. Additionally, the authors find that the proxy for informed trading activity is positively related to the arrival rates of public information from October 2021 to January 2022.

The findings support the hypothesis that negative (positive) media sentiment induces significant deterioration (insignificant improvement) in stock liquidity. The authors find that an increase in the number of news articles about a company corresponds to a higher liquidity of Chinese property developers' stocks after controlling for media sentiment.

This study aims to provide empirical evidence on the impact of foreign share ownership on the liquidity of the Tunisian Stock Exchange (TSE).

The authors hypothesize in the first strand that stock liquidity could be positively affected by foreign ownership based on the real friction channel. The authors then hypothesize in the second strand, based on the information friction channel, that foreign ownership's impact on stock liquidity could be insignificant or negative and that foreign investors raise the level of information asymmetry. A sample of 318 firm-year observations from Tunisia over the 2012–2017 period and a random-effects estimation were used. Moreover, using the 2SLS estimator, a robustness check framework was applied in order to address any potential reverse causality concerns.

The authors find strong evidence that higher foreign ownership improves stock liquidity. More specifically, firms with higher foreign ownership engender a lower bid-ask spread, a better stock ability to absorb a large amount of trading volume, and a larger depth. These findings are still valid when reverse causality concerns are addressed through the use of the 2SLS estimator.

The paper contributes to the existing literature by focusing on the ownership–liquidity relationship on a frontier market. It provides further empirical support that higher corporate governance quality reduces the information asymmetry problem and enhances stock market liquidity.

This study aims to identify the problems in shariah compliance and the weak oversight of implementing Islamic crowdfunding (ICF). Shariah compliance regulation is an essential subsystem in Islamic social finance ecosystems.

This type of research is legal research. The research approaches are the statute, comparative and conceptual approaches. The study in this research examines Indonesia, the UK and Malaysia.

ICF is one of the fastest-growing sectors of Islamic financial technology (fintech). The Islamic fintech sector is showing maturity signals with a market size of $79bn in 2021, projected at $179bn in 2026. Malaysia, Saudi Arabia and Indonesia lead the Index by Global Islamic Fintech (GIFT) Index scores. However, low shariah compliance is still an issue in implementing ICF. This problem is caused by regulatory support that is still lacking and oversight of shariah compliance is not optimal. On the one hand, shariah compliance is the ICF core principle for Shariah Governance.

This study examines the regulation and oversight of ICF in Indonesia, Malaysia and the UK. Indonesia and Malaysia, a country with the highest GIFT index score in the world, and the UK, a country with an Islamic finance sector experiencing rapid growth.

The research results on shariah compliance regulation in ICF are helpful as a comprehensive approach for developing sustainable Islamic social finance ecosystems.

Shariah compliance is the core principle of ICF governance. Its implementation can increase public trust.

Crowdfunding platform and issuers in ICF must implement shariah compliance. Therefore, it is essential to consider the presence of shariah compliance requirements and a Shariah Supervisory Board (DPS).

This study examines the effect of board characteristics on the tax aggressiveness of listed companies on the Colombo Stock Exchange in Sri Lanka.

The sample consists of 264 firm-year observations of non-financial listed companies in Sri Lanka from 2014 to 2019. The dynamic panel system GMM technique was used to test the hypotheses, and further analyses were performed using the propensity score matching technique.

All four effective tax rate measures' mean values were lower than the statutory tax rate, indicating the likelihood of tax planning. Whether board attributes are likely to mitigate tax aggressiveness is uncertain because the results are inconsistent and depend on the ETR measure. Similarly, the logistic regression results derived using the PSM approach are inconsistent, suggesting that board characteristics may have a limited effect on tax aggressiveness. Hence, the corporate governance-tax aggressiveness nexus is limited in the case of Sri Lanka.

This investigation is limited to non-financial listed companies in Sri Lanka and incorporates only four tax aggressiveness measures. Findings are imperative for policymakers, regulators, and professional bodies to improve corporate governance codes and rules to enhance organisational transparency toward corporate tax payments.

Aggressive tax planning by companies will reduce government tax revenue, hinder social progress, and cause public mistrust of large corporations and institutions.

This study provides insight into the nexus between corporate governance and tax aggressiveness in a middle-income economy in South Asia hit by an economic crisis where tax revenue has fallen and tax enforcement is weak.