Journal of International Financial Markets Institutions & Money最新文献

Developed economies like the EU advocate imposing carbon tariffs on exports from countries lacking equivalent emission reduction measures, with energy-intensive sectors being the most susceptible. This study establishes five specific policy scenarios aligned with the potential criteria for carbon tariffs by developed economies. Utilizing the GTAP-E model, we quantitatively analyze the impact on energy-intensive sectors in major developing and developed economies. The results highlight the disadvantaged position of affected economies compared to the imposing ones. Lastly, the paper delves into effective strategies for relevant countries and outlines the transition pathways for energy-intensive sectors.

This paper analyzes the relationship between price jumps and news sentiment in cryptocurrencies. We detect jumps at the intraday level and correlate their occurrence with sentiment-related events through logistic regressions. We show that the release of information increases the probability of price jumps. By examining the content of news stories, we find that sentiment dimensions limited to emotions or related to market fundamentals have more potential to result in price jumps than others, suggesting that “words are not all created equal”. Jump sensitivity to news sentiment varies across different coin characteristics.

As a result of information asymmetry, banks have generated many non-performing loans, jeopardizing financial stability. This paper investigates the relationship between digital transformation and credit risk and whether financial inclusion plays an interactive role. The paper employs the Generalized Method of Moments (GMM) and data from 116 Chinese banks from 2014 to 2021 to investigate the issue. The results show that digital transformation significantly and dynamically reduces bank credit risks, and inclusive finance plays an interactive role. As financial inclusion increases, this risk-reducing effect will increase, meaning that banks need to combine financial inclusion to promote bank risk reduction better and maximize risk assessment accuracy.

We study whether environmental engagement of banks mitigates the effects of natural disasters and climate-change related events on financial stability. Employing an extensive global dataset with quarterly data (2003–2019; 5,317 observations), our analysis reveals that environmental innovation financing, product responsibility, and resource reduction policies are able to curtail the repercussions on stability of economic costs due to environmental events. We also find that the lending function of banks is a relevant mediating channel for this relationship. Since borrowers’ vulnerability to climate issues may be reflected in non-performing loans, banks’ environmental engagement provides protection against future related credit losses. Moreover, by capitalizing on global disasters as quasi-natural experiments, we provide empirical evidence confirming that a stronger environmental engagement of banks enhances their post-event financial resilience. Taken together, our results convey several key implications: i) bank executives can improve financial stability by embracing environmental policies, ii) stronger regulatory actions towards environmental sensitivity in the banking sector is supported, and iii) environmentally engaged banking systems can mitigate the economic costs associated with climate change and environmental disasters.

We illustrate the concept of using a Turing complete consortium blockchain (TCCB) to facilitate international countertrade. Physical goods and services would be linked to the blockchain by associating them with corresponding non-fungible tokens (NFTs). TCCBs could help small or new companies, particularly those in less developed countries, reduce the counterparty risk and transaction costs related to logistic chain management and contract arbitration. They could also supplement trade financing that often requires a mature banking system and developed financial market. We analyze the concept using a hypothetical example to illustrate the potential efficiencies over traditional countertrade transactions.

We examine extreme connectedness between the artificial intelligence (AI) tokens, artificial intelligence ETFs, and other asset classes, using the quantile VAR approach of Ando et al., (2022). We find moderate connectedness levels at mean and median quantiles, with AI ETFs (AI tokens) acting as strong (weak) net emitters (receivers) of return spillovers. Findings, confirmed by alternative testing, suggest that, during normal market conditions, AI tokens may offer utility as diversifiers for portfolios of traditional assets. However, at both lower and upper quantiles, connectedness levels increase, consistent with AI tokens and ETFs being sensitive to extreme shocks. Results suggest that AI tokens and ETFs do not diversify the risk of other assets during extreme market conditions. Finally, AI tokens, especially, may offer effective hedging at low cost for traditional assets (gold, equity, real estate, bonds, and currency), except for the oil and cryptocurrency market. Investors including AI assets in portfolios need to diligently monitor for changing market conditions.

Studies have highlighted the important role of financial technology (fintech) in enhancing socio-economic conditions of nations. However, despite the efforts of governments to improve the latter, the rating of African countries still remains manifestly inadequate. Given that access to electricity is imperative for fintech, and fundamental to improving socioeconomic conditions, we provide novel evidence by investigating the degree to which the prevailing energy poverty in Africa mediates the relationship between the duo. Our baseline results confirm that fintech has a significant positive impact on socioeconomic conditions, proxied by human development, and the impact becomes increasingly significant in the face of constant energy supply. However, when we split our sample based on regions and income classification proposed by the World Bank, our results show that the impact of fintech on human development, in the absence of access to electricity, is notably limited to some African regions. Considering the current state of human development in Africa, our study advocates for more investment in energy infrastructure for the rapid realization of the gains of fintech.

This paper constructs a global tail risk (GTR) index and investigates the role of GTR in predicting the volatility of international stock markets. The results emphasize that GTR contains valuable information to predict the stock volatility of group (7) (G7) countries. In addition, accounting for the information of GTR and regime switching together can further improve the forecasting accuracy of international stock market volatility, especially considering the time-varying regime switching. The results are robust in different robustness checks and even during the global financial crisis period. Our paper tries to provide new evidence for tail risk in international stock market volatility prediction.

We analyze the effect of bilateral investment treaties (BITs) on bilateral foreign portfolio investment in equity and debt securities. We find that expropriation risk and the level of a BIT’s investor protection are complementary. Applying a Poisson Pseudo-Maximum-Likelihood model to a panel of 60 home and 39 host countries from 2002 to 2017, we find that host countries receive 40% more bilateral equity investment when they protect foreign investors with a BIT. This effect almost doubles when investment protection of BITs is strong, and the political risk of the host country is high.

This paper investigates the relationship between firms' engagement in environmental, social, and governance (ESG) activities and corporate investment efficiency, using 1,094 firms from 21 countries in Europe, covering the years 2002–2019. We conduct our estimations using fixed effects panel data techniques and address potential endogeneity with instrumental variables (IV) estimations. We provide evidence that overall ESG engagement is positively and significantly associated with investment efficiency. Analyzing overinvestment and underinvestment scenarios shows that ESG engagement decreases only overinvestment problems. Within the underinvestment scenario, we observe that ESG engagement is beneficial only for firms with higher information asymmetries. Thus, information asymmetry matters in the underinvestment case. We next show that four firm-level channels—information asymmetry, financial constraints, cash flows, and risk—link ESG performance to investment inefficiency. Additional analysis shows that firms with extreme ESG scores (i.e., very low and very high) do not experience significant reductions in investment inefficiency. Altogether, our findings draw attention to the critical role of ESG performance and information asymmetry in determining corporate investment efficiency.