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This study aims to investigate connections between the development of robotic and artificial intelligence (AI) and green crypto investments. The author also explores the influences of global uncertainty shocks like the COVID-19 pandemic and international conflicts on the role of each channel.

In this research, the author uses a cutting-edge model-free connectedness approach to investigate the relationships between the development of Global X Robotics and AI (BOTZ) and the volatility of green crypto investments from November 9, 2017 to March 24, 2023.

In the sample duration, the findings reveal a two-way link between AI and green/nongreen cryptocurrencies. Throughout the examined period, BOTZ has been a net receiver of shocks as determined by the net total connectedness. Among the main spillover shock carriers in the system, green cryptocurrencies are the most significant. The net pairwise directional connectivity reveals that green cryptocurrencies controlled BOTZ throughout the analyzed time, particularly during the COVID-19 era as well as the Ukraine–Russia crisis. According to the findings, the proposed system is vulnerable to a high level of indication influence.

The results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.

To the best of the authors’ knowledge, this paper is the first to look at the link between AI, technological advancement and green cryptocurrency investing. Second, this study developed a methodology for examining instability links between various factors that is more appropriate for investigating these linkages. This study investigates the links between AI, technical advancement and green digital currencies using a cutting-edge model-free connectivity method. This work is also the first to examine the interconnection between volatility derived from AI, technological development and green cryptocurrency investments in light of unknown events, such as the COVID-19 pandemic and the Ukrainian–Russian conflict. Finally, this study includes a daily database from the BOTZ fund, which attempts to invest in firms that stand to gain from rising robotics and AI use. Cardano (ADA), IOTA, NANO (XNO), Stellar Lumens and Tron are examples of green cryptocurrencies, whereas Bitcoin is an example of a nongreen cryptocurrency. These virtual currencies are being used to investigate the relationship between investor mood and green and nongreen digital currencies. The data set spans the period from November 9, 2017 to March 24, 2023.

This paper aims to better jointly estimate Value at Risk (VaR) and expected shortfall (ES) by using the joint regression combined forecasting (JRCF) model.

Combining different forecasting models in financial risk measurement can improve their prediction accuracy by integrating the individual models’ information. This paper applies the JRCF model to measure VaR and ES at 5%, 2.5% and 1% probability levels in the Chinese stock market. While ES is not elicitable on its own, the joint elicitability property of VaR and ES is established by the joint consistent scoring functions, which further refines the ES’s backtest. In addition, a variety of backtesting and evaluation methods are used to analyze and compare the alternative risk measurement models.

The empirical results show that the JRCF model outperforms the competing models. Based on the evaluation results of the joint scoring functions, the proposed model obtains the minimum scoring function value compared to the individual forecasting models and the average combined forecasting model overall. Moreover, Murphy diagrams’ results further reveal that this model has consistent comparative advantages among all considered models.

The JRCF model of risk measures is proposed, and the application of the joint scoring functions of VaR and ES is expanded. Additionally, this paper comprehensively backtests and evaluates the competing risk models and examines the characteristics of Chinese financial market risks.

This study aims to investigate the moderating role of corporate governance (CG) on the relationship between credit risk (CRs) and financial performance (FP) of banks listed in the Palestine Securities’ Exchange (PEX) and Amman Securities’ Exchange (ASE).

This study used a hypothesis-testing research design to collect data from the annual reports of 21 banks listed on (PEX) and (ASE). Secondary data, annual reports and disclosures were used between from 2009 to 2019. Descriptive and inferential statistics were used, along with correlation analysis to evaluate linear relationships between variables. Data was collected based on panel data, the VIF was used to test multicollinearity and binary logistic regression was used to develop the research model.

The regression results showed the association between CR and firm performance depends on the measurement of each factor applied. The results showed mixed results between loans to total assets (LTA) and nonperforming loans to total loans (NPLs) with FP. LTA has a significant and positive effect on TOBINSQ and return on equity (ROE), but an insignificant and positive effect on return on assets (ROA). On the other hand, NPLs have a significant and negative effect on ROA, whereas NPLs have a weak and positive effect on TOBINSQ. However, there is an insignificant and positive effect of NPLs on ROE. Moreover, the results demonstrated that CG moderated the relationship between CRs and FP of banks. The practical contribution of this paper, for bank policymakers and authorities, the study’s implications are noteworthy. Understanding the varied impacts of different CR measures on FP can help regulators and policymakers design more tailored and effective risk management frameworks for banks.

This study had limitations that future research might be able to address. First, the small size of the sample used in the study included 21 banks listed on the PEX and ASE. Likewise, the ASE and PEX are considered developing stock exchanges, so the results of this study may differ from those of other stock exchanges. Second, only CRs were considered in this study when examining the association between the profitability of Palestinian banks and ASE. Other studies can be undertaken on other nonfinancial risks, such as operational risk, to measure the differences between them and examine their effects on the profitability of Palestinian and Jordanian banks. Other studies might be performed to compare CRs and its impact on profitability in Palestinian and Jordanian banks with those in other Western and Eastern banks. Furthermore, in addition to TOBINSQ, ROA and ROE, researchers can use other financial indicators to measure profitability. This will contribute to substantiating the present study’s findings.

Although several studies have examined the relationship between CRs and FP in developed and developing countries, the results have been mixed. However, this study is one of the few studies that examined the moderating role of CG in association with CRs and FP, especially on Palestinian and Jordanian contexts. Finally, the findings offer policymakers and practitioners of Palestinian and Jordanian contexts.

The purpose of this study is to investigate how the price delay of cryptocurrencies to market news affects the herding behavior of investors, particularly during turbulent events such as the COVID-19 period.

The paper investigates the presence of herding behavior by using Cross-Sectional Absolute Deviation (CSAD) measures. We also investigate the herding activity in the crypto traders’ behavior during up and down-market movements periods and under investor extreme sentiment conditions. The speed of cryptocurrencies’ price response to the information embedded in the market is assessed based on the price delay measure proposed by Hou and Moskowitz (2005).

Our findings suggest that cryptocurrencies characterized by high price delays exhibit more herding among investors, thereby highlighting higher degrees of market inefficiencies. This is also apparent during periods of extreme investor sentiment. We also document an asymmetric herding behavior across cryptocurrencies that present different levels of price speed adjustments to market news during bullish and bearish market conditions. Our results are consistent and robust across different sub-periods, various market return estimations and different price delay frequencies.

The study provides crucial guidelines for investors’ asset allocation and risk management strategies. This study is also valuable to regulators and policymakers, particularly in light of the increasing importance of financial reforms aimed at mitigating market distortions and enhancing the resilience of the cryptocurrency market. More specifically, regulations that improve the market’s information efficiency should be prioritized to speed up the response time of cryptocurrency prices to market information, which can help reduce the investors' herding behavior.

This paper makes a novel contribution to the academic literature by investigating the unexplored relationship between cryptocurrency price delays and the presence of herding behavior among investors, especially in times of uncertainty such as the COVID-19 pandemic.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

This study systematically explores the literature on global niche market strategies within the fashion industry to allow the mapping of niche practices and examine the benefits, success factors and characteristics of a niche strategy. Additionally, it identifies data gaps and necessitates a detailed examination to uncover areas with inadequate information.

This study utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020) method for systematic review and included 70 studies to analyze their findings.

This systematic literature review pinpoints niche strategies shaping the future of the fashion industry while developing sectors of the textile and apparel industry, fashion technology, fashion retail business, fashion media and communication, luxury fashion, sustainable fashion, adaptive clothing and transgender fashion within the fashion supply chain. A niche market strategy utilizes both pull and push marketing in the fashion industry. Scholarly literature commonly underscores the understanding of the consumer as a pivotal factor in the success of fashion niche market strategy.

This review offers a comprehensive overview of fashion niche strategy practices, aiming to inspire fashion industry professionals. It also serves as a guide for fashion industry professionals, summarizing best practices across various fashion industry sectors to help develop effective niche strategy competencies for firms.

This review thoroughly analyzes niche strategy implementation in the fashion industry, presenting an important resource for individuals new to this sector. It highlights the significance of niche strategies in improving the comprehension of emerging participants in the fashion business.

While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.

This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.

The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).

The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.

This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.

Poor indoor air quality (IAQ) contributing to occupants’ health symptoms is a universal, typically ventilation-related, problem in schools. In cold climates, low-cost strategies to improve IAQ in a naturally ventilated school are rare since conventional methods, such as window opening, are often inappropriate. This paper aims to present an investigation of strategies to relieve health symptoms among school occupants in naturally ventilated school in Finland.

A case study approach is adopted to thoroughly investigate the process of generating the alternatives of ventilation redesign in a naturally ventilated school where there have been complaints of health symptoms. First, the potential sources of the occupants’ symptoms are identified. Then, the strategies aiming to reduce the symptoms are compared and evaluated.

In a naturally ventilated school, health symptoms that are significantly caused by insufficient ventilation can be potentially reduced by implementing a supply and exhaust ventilation system. Alternatively, it is possible to retain the natural ventilation with reduced number of occupants. The selected strategy would depend considerably on the desired number of users, the budget and the possibilities to combine the redesign of ventilation with other refurbishment actions. Furthermore, the risk of poorer indoor air caused by the refurbishment actions must also be addressed and considered.

This study may assist municipal authorities and school directors in decisions concerning improvement of classroom IAQ and elimination of building-related symptoms. This research provides economic aspects of alternative strategies and points out the risks related to major refurbishment actions.

Since this study presents a set of features related to indoor air that contribute to occupants’ health as well as matters to be considered when aiming to decrease occupants’ symptoms, it may be of assistance to municipal authorities and practitioners in providing a healthier indoor environment for pupils and teachers.