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This study aims to investigate the association of FinTech innovation (FinTechINN) and firm performance (FP) by considering the role of knowledge assets (KA) as a causal mechanism underlying the FinTechINN – FP association.

In this study, the authors consider panel data of 1,049 Chinese A-listed firm and construct a structural model for corporate FinTech innovation, knowledge assets and firm performance while considering endogeneity issues in analyses over the period of 2014–2022. The modified value added intellectual capital (VAIC) and research and development (R&D) expenses are used as a proxy measure for knowledge assets, considering governance and corporate performance measures.

According to the findings of this study FinTech innovation (FinTechINN) has a positive significant effect on firm performance. Particularly; the findings disclose that FinTech innovations has a link with knowledge assets, FinTech innovations indirectly affects firm performance, and the association between FinTech innovation and firm performance is partially mediated by knowledge assets (MVAIC and R&D expenses).

Rooted in the dynamic capability and resource-based view, this study pioneers an empirical exploration of the association of FinTech innovation with firm performance. Moreover, it introduces the novel dimension of knowledge assets (on firm-level), acting as a mediating factor with in this relationship.

The purpose of this research is to primarily understand how crypto traders can use the Bitcoin as a hedge or safe haven asset to reduce their losses from crypto trading. The study also aims to provide insights to crypto investors (portfolio managers) who wish to maintain a crypto portfolio for the medium term and can use the Bitcoin to minimize their losses. The findings of this research can also be used by policymakers and regulators for accommodating the Bitcoin as a medium of exchange, considering its safe haven nature.

This study applies the cross-quantilogram (CQ) approach introduced by Han et al. (2016) to examine the safe-haven property of the Bitcoin against the other selected crypto assets. This method is robust for estimating bivariate volatility spillover between two markets given unusual distributions and extreme observations. The CQ method is capable of calculating the magnitude of the shock from one market to another under different quantiles. Additionally, this method is suitable for fat-tailed distributions. Finally, the method allows anticipating long lags to evaluate the strength of the relationship between two variables in terms of durations and directions simultaneously.

The Bitcoin acts as a weak safe haven asset for a majority of new crypto assets for the entire study period. These results hold even during greed and fear sentiments in the crypto market. The Bitcoin has the ability to protect crypto assets from sharp downturns in the crypto market and hence gives crypto traders some respite when trading in a highly volatile asset class.

This study is the first attempt to show how the Bitcoin can act as a true matriarch/patriarch for crypto assets and protect them during market turmoil. This study presents a clear and concise representation of this relationship via heatmaps constructed from CQ analysis, depicting the quantile dependence association between the Bitcoin and other crypto assets. The uniqueness of this study also lies in the fact that it assesses the protective properties of the Bitcoin not only for the entire sample period but also specifically during periods of greed and fear in the crypto market.

This paper aims to determine the types of legal mechanisms that authorities can use to recover stolen assets for and from China.

Newspaper articles and books are examined as are relevant reports by various regulatory authorities and academic institutions.

The effectiveness of legal mechanisms in the recovery of stolen assets may be affected by issues such as the difficulties in tracing illicit funds, the ambiguous nature of “value” as well as the rise in technology.

There are limited data available in relation to the prevalence of corrupt officials along the Belt and Road Initiative and the statistical success in the recovery of stolen assets. Any discussions within this paper are based on the impressionistic observations of this author, which may not reflect the true state of affairs of the Belt and Road Initiative.

Those who are interested in examining how authorities could recover stolen assets from and for China will have an interest in this topic.

The value of the paper is to demonstrate the difficulties in recovering stolen assets for and from China.

The purpose of this study is twofold. On the one hand, it studies the impact of IFRS 9 adoption on the firm value; and on the other hand, it investigates the impact of the classification of financial assets on the firm value.

The study covers a sample of 55 listed banks in the Middle Eastern and North African (MENA) region. Data is collected for three years (2017–2019).

The findings show that banks’ value is not impacted by IFRS 9 adoption but by financial assets’ classification. Firm value is positively affected by fair value through other comprehensive income assets, while it is negatively affected by amortized cost and fair value through profit or loss assets. The results of the additional analysis show consistent outcomes.

This research reveals important managerial implications. Priority should be given to the financial assets’ classification strategy following the adoption of IFRS 9 to boost the market valuation of banks. It may be useful for investors, managers and regulators in their decision-making.

This study enriches previous research as IFRS 9 is a new standard, and its adoption consequences need to be investigated. A few recent studies have focused on IFRS 9 as a whole or on other parts of IFRS 9, namely, the impairment regime and hedge accounting and concern developed contexts. However, this research adds to the knowledge of capital market studies by investigating the application of IFRS 9 in terms of classification in the MENA region.

The rapid rise of Islamic crypto assets, underpinned by blockchain technology, has introduced a novel dimension to the Islamic financial landscape, raising questions about their potential as safe havens within emerging Islamic economies. However, the opportunities and challenges associated with this phenomenon remain insufficiently explored. In this context, this study aims to empirically investigate the extent to which blockchain technology can establish Islamic crypto assets as safe havens in equity markets within Islamic economies.

This study addresses the need for rigorous empirical analysis to understand the dynamics between Islamic crypto assets and stock markets in emerging Islamic economies, focusing on the transmission of volatility. While the evolving nature of the Islamic financial sector demands reliable data, the reliance on the most available data offers insights into the expected future trends in this emerging field. The research specifically focuses on three essential assets in the Islamic financial portfolio: OneGram Coin and X8XToken, both backed by gold and MRHB DeFi, an Islamic DeFi asset lacking gold backing. These crypto assets are compared with corresponding assets in seven stock markets of emerging Islamic economies. Using daily log returns of the Islamic crypto assets from various sources and seven Islamic stock indices. The data covers the period from December 27, 2021, to December 28, 2022, capturing the fluctuations in Islamic stocks and cryptocurrency markets during the post-COVID-19 era. This research uses advanced econometric techniques, including pairwise dynamic correlation and the DCC GARCH model.

The findings indicate that Islamic crypto assets exhibit distinct characteristics, with lower volatility and low correlations compared to their conventional counterparts in non-Islamic contexts. This outcome suggests that these Islamic crypto assets could potentially serve as safe havens within Islamic stock markets, offering valuable insights for various stakeholders, including investors, governments and policymakers.

The findings are based on a specific set of Islamic crypto assets and may vary with a different selection. Market dynamics can also influence the relationships observed. Nevertheless, the outcomes provide valuable insights for investors, policymakers and researchers interested in the intersection of Islamic finance, cryptocurrency and technology.

In essence, this research not only unveils the potential of Islamic crypto assets as stabilizing forces but also delineates a trajectory for subsequent research endeavours within the realm of emerging Islamic Fintech, elucidating the challenges, opportunities and benefits that lie therein. With a discerning eye on circumventing the pitfalls entrenched within conventional crypto finance, this study contributes to a heightened comprehension of the transformative role that Islamic crypto assets can assume, ultimately enriching the financial resilience of Islamic economies.

This study aims to reconstruct how smallholder farmers implement livelihood adaptation strategies to survive and escape poverty, thereby mitigating or eliminating potential livelihood risks by utilizing their available assets.

This research employed a qualitative approach. For the collection of primary data, the researcher conducted observations and in-depth interviews and engaged with the lives of smallholder farmers during the data collection period.

Among the various livelihood adaptation strategies, only migration and profit-sharing strategies enable smallholder farmers to escape poverty. However, migration is an unsustainable adaptation strategy. When farmers move to new locations, they often resort to slash-and-burn methods for clearing land, which can lead to forest degradation and deforestation. Profit sharing is a sustainable livelihood adaptation strategy that falls into a different category. This approach can lift farmers out of poverty, increase their income and have no negative environmental impact. Other adaptation strategies include adjustments to traditional agriculture, both on and off-farm diversification, involving the family in income generation, reducing farming costs, practicing frugality in post-harvest processes, converting land from coffee cultivation to other crops and borrowing money and selling owned assets. Smallholder farmers implement these strategies to survive the existing economic conditions.

The profit-sharing strategy was a novel livelihood adaptation approach that previous studies had yet to uncover at the research site. In this strategy, farmers assume the roles of both managers and laborers simultaneously during farming, while toke (the capital owners) play the role of farming funders. The generated profit is then shared between farmers and toke based on the agreement established at the outset of their collaboration.

This study investigates the diversification benefits of multiple cryptocurrencies and their usefulness as investment assets, individually or combined, in enhancing the performance of a well-diversified portfolio of traditional assets before and during the pandemic COVID-19.

This paper uses two optimization techniques, namely the mean-variance and the maximum Sharpe ratio. The naïve diversification rules are used for comparison. Besides, the Sharpe and the Sortino ratios are used as performance measures.

The results show that cryptocurrencies diversification benefits occur more during the COVID-19 pandemic rather than before it, with the maximum Sharpe ratio portfolio presenting its highest performance. Furthermore, the results suggest that, during COVID-19, the diversification benefits are slightly better when using a combination of cryptocurrencies to an already well-diversified portfolio of traditional assets rather than individual ones. This serves to improve the performance of the maximum Sharpe ratio portfolio, and to some extent, the naïve portfolio. Yet, cryptocurrencies, whether added individually or combined to a well-diversified portfolio of traditional assets, don't fit in the minimum variance portfolio. Besides, the efficient frontier during COVID-19 pandemic dominates the one before COVID-19 pandemic, giving the investor a better risk-return trade-off.

To the best of the author's knowledge, this is the first study that examines the diversification benefits of multiple cryptocurrencies both as individual investments and as additional asset classes, before and during COVID-19 pandemic. The paper covers all analyses performed separately in previous studies, which brings new evidence regarding the potential for cryptocurrencies in portfolio diversification under different portfolio strategies.

This paper aims to examine the performance efficiency of 56 real estate assets within the rental sector in the UAE to evaluate the relative operation efficiency in relation to revenue generation.

The data envelopment analysis (DEA) approach was used to measure the relative operational efficiency of the studied assets in relation to the revenue performance. This method could produce a more informed and balanced approach to performance measurement.

The outcomes show that scores of efficiencies ranging from 7% to 99% in some of the models. The results showed that on average buildings are 75% relatively less efficient in maintenance, in term of revenue generation, than the benchmark set. Likewise, on average, the inefficient buildings are 60% relatively less efficient in insurance. Result also shows that 95% of the building assets in the sample are by and large operating at decreasing returns to scale. This implies that managers need to considerably reduce the operational resources (input) to improve the levels of revenue.

This study recommends that the FM operational variables that were found to inefficiently contribute to the revenue should be re-examined to test the validity of the findings. This is necessary before generalising or interpolating the results that are presented in this study.

The information obtained about operational performance can help FM managers to understand which improvements in the productivity of inefficient FM resources are required, providing insight into how to reduce operating costs and increase revenue.

This paper adds value in using new FM operational parameters to evaluate the efficiency of the performance of built assets.

The study measures the total systemic risks and connectedness across commodities, stocks, exchange rates and bond markets in Africa during the Covid-19 pandemic.

The study uses the Diebold-Yilmaz spillover and connectedness measures in a generalized VAR framework. The author calculates the net transmitters or receivers of shocks between two assets and visualizes their strength using a network analysis tool.

The study found low systemic risks across all assets and countries. However, we found higher systemic risks in the forex market than in the stock and bond markets, and in South Africa than in other countries. The dynamic analysis found time-varying connectedness return shocks, which increased during the peak periods of the first and second waves of the pandemic. We found both gold and oil as net receivers of shocks. Overall, over half of all assets were net receivers, and others were net transmitters of return shocks. The network connectedness plot shows high net pairwise connectedness from Morocco to South Africa stock market.

The study has implications for policymakers to develop the capacities of local investors and markets to limit portfolio outflows during a crisis.

Previous studies have analyzed spillovers across asset classes in a single country or a single asset across countries. This paper contributes to the literature on network connectedness across assets and countries.

The study analyzes the relationship between homeownership and financial investment of households in the context of emerging markets like India. It also examines how homeownership affects the portfolio decisions of Indian households.

Using the nationally representative All-India Debt and Investment Survey of 2019 and employing an instrumental variable approach, the authors analyze the relationship between homeownership and the share of financial assets held by Indian households. The study also employs several sensitivity checks, including alternate estimation techniques and alternative definitions of the housing variables, and accounts for additional factors to ensure that the authors are able to capture the effect of homeownership on the outcome variable.

The analysis suggests homeownership crowds out financial investment in India due to high repair and maintenance costs. The negative effect is mainly observed in urban households. Further, the findings imply that homeownership leads households to reallocate their asset portfolio. Homeowners have a lower share in liquid short term deposits, indicating the high liquidity risk of their portfolios. On the other hand, homeownership increases the share of long term retirement funds along with no effect on risky asset share. The authors observe that the crowding out effect is more striking for younger households and poorer households with low income, and the effect is lower for indebted households.

The findings underscore the need for financial awareness programs so that housing does not crowd out liquid investments of households. Additionally, the results highlight that policies should first focus on young and poor households as the negative effect is more prominent for these groups. Finally, there is scope for policies to support repair and maintenance costs incurred by vulnerable households to reduce the negative effect of housing on liquid financial investments.

This paper is among the few studies that provide insights into how homeownership relates to financial investment and portfolio decisions in the context of an emerging economy. Furthermore, the heterogeneous effects based on poor economic status and age underscore the need for complementary policies.