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• This study uses the PSY method to track Bitcoin and its forked coins ' price bubbles. • Bitcoin price bubbles are more common and last longer, while some forked coins do not have bubbles. • The correlation between the price bubble of Bitcoin and several forked coins is significant. • BCH and BTC are the closest, while BSV is the farthest from BTC. This study employs the PSY method to detect the price bubble of Bitcoin (BTC) and its forked coins. The statistical relationship between BTC and its forked coins is then calculated using Pearson correlation coefficients and six distance measurement methods. The findings indicate that (1) BTC has more bubbles with longer periods. In contrast, certain forked coins do not have bubbles; (2) The correlation between the price bubble of BTC and several forked coins is significant; (3) From the distance of binary time series, Bitcoin Cash and BTC are the closest, while Bitcoin SV is the farthest from BTC. [ABSTRACT FROM AUTHOR]

• This paper proposes a distributed neural network model for credit card fraud detection. • We design an optimization algorithm to achieve convergence of the model of the distributed neural network model. • The distributed neural network model proposed outperforms a variety of machine learning models on real credit card transaction data. • Our proposed model can avoid privacy leakage and reduce data handling costs. This paper develops a distributed neural network model (DDNN) for detecting credit card fraud to federate credit card transaction data among different financial institutions. In addition, the convergence of the DDNN model is achieved by introducing a model optimization algorithm. The results demonstrate that (1) The use of a distributed model can avoid privacy leakage and data handling costs; (2) The DDNN model accelerates the convergence of the model through simultaneous computation of multiple clients; (3) The DDNN model detects credit card fraud better than multiple types of centralized models. [ABSTRACT FROM AUTHOR]

• We employ an integrated CiteSpace and natural language processing strategy to develop bibliometric analysis. • We conduct a bibliometric study of the explainable artificial intelligence (XAI) literature in finance. • XAI's transparency improvement and potential risk assessment will be permanent study subjects. • The increasing integration between finance and XAI has resulted in diverse financial capabilities. This study focuses on explainable artificial intelligence (XAI) in finance. We collected 2,733 articles published between 2013 and 2023 from the Web of Science Core Collection and analyzed trends in literature development and future prospects using an integrated CiteSpace and Natural Language Processing (NLP) bibliometric approach. Our analysis reveals an increase in publication after 2013. Early XAI research had a significant and lasting impact, shifting research focus from traditional finance research to inclusive finance. XAI has diversified financial capabilities, and non-XAI pursues interpretable solutions for improvement. We conclude with a list of prospective subjects for further study. [ABSTRACT FROM AUTHOR]

Highlights • The relative export competitiveness (REC) for India and her competitors is developed. • The REC covers exports of sugar, rice, wheat, and cotton, each relative to other exports. • India's rice, cotton, and sugar are competitively advantaged but not wheat. • The REC is time varying and is mainly lower for India than her competitors. • An attempt is made to explain the determinants of the REC. Abstract In this paper, we derive time-varying relative export competitiveness (REC) of India's top agricultural exports (rice, wheat, cotton and sugar) against India's share of world agricultural exports (REC_WA) and world exports (REC_WE) from 1961 to 2012. We reveal that India's exports of all four commodities became relatively competitive over time but these were not as competitive as the top, or selected emerging, exporters of the four commodities. We also examine the determinants of REC in these four commodities focusing on factors including crop-specific and aggregate factor endowments, domestic price, export prices, and GDP per capital, preferential trade agreements, export restrictions and bans, and India's Green Revolution. The regression analysis was mainly confined to the 1981–2012, due to data constraints. We find that the time series regression results are similar in sign and significance for REC_WE and REC_WA. Our key findings suggest the REC in wheat, rice, and cotton deteriorated as a result of export restrictions. Capital had negative effects on cotton REC. Labor and farm size did not influence the REC in the commodities. The Green Revolution improved the REC in rice and cotton (in Phase 3). The WTO had a positive effect on the REC in rice. The South Asian Free Trade Area (SAFTA) Agreement adversely affected the REC in wheat and rice but strengthened the REC in cotton and sugar. Higher domestic price reduced the REC in cotton. Higher per capita income strengthens the REC in wheat with a lag. We explain these results and suggest policy implications. [ABSTRACT FROM AUTHOR]

We show a stable long-run relationship between three developed and ten emerging frontier Asian (EFA) equity markets over the period 2000 to 2013 using daily, weekly, and monthly data. Across the three frequencies, DJIA returns are good predictors of EFA markets but the predictive power of Nikkei225 and S&P 500 differ. Further, during the GFC, the DJIA and Nikkei225 (not S&P 500) are influential. Non-GFC periods see all three important but S&P 500 was more persistent. We also reveal that the developed markets may be more important than other emerging market predictors, such as exchange rates and oil price shocks. [ABSTRACT FROM AUTHOR]

• This paper show that corporate innovation (research and development, patents, citations, and patent value) positively influences tangible investment. • The manner in which this effect transpires is characterized by a firm's external/internal dependence on finance, technological intensity, size, maturity, and payout policy. • We discover that corporate investment and corporate innovation follow a business cycle pattern to the extent that innovations have a greater effect on corporate investment during economic expansions than during recessions. This paper quantifies the impact of corporate innovation on corporate tangible investment for a large panel of U.S. firms. We show that corporate innovation (research and development, patents, citations, and patent value) positively influences tangible investment and the manner in which this effect transpires is characterized by a firm's external/internal dependence on finance, technological intensity, size, maturity, and payout policy. We discover that input- and output-type innovations affect corporate investment differently, with research and development (patent value) having the least (most) effect on investment. Our analysis reveals that corporate innovation moves investments more during economic expansions than during recessions. [ABSTRACT FROM AUTHOR]

We examine the adaptive market hypothesis using the Generalized Hurst exponent, derived using fixed and rolling windows. We find that the Indian stock market is moving towards efficiency. We also ascertain a positive and significant link between the Indian market's efficiency gap and financial crises, other international shocks and major domestic policy and crisis-related events. Net foreign institutional investment increases the efficiency gap, although the impact is less for international events. Foreign institutional investment and market microstructure factors do not influence efficiency in an emerging market. This evidence would benefit a stock market liberalization policy review. [ABSTRACT FROM AUTHOR]

This study examines the impact of non-renewable and renewable energy consumption on economic growth, differentiating between manufacturing and services growth. We derive our empirical model from an endogenous growth framework with expanding variety of intermediate capital goods embedding non-renewable and renewable energy inputs. Controlling for well-established growth determinants, we estimate the effects of non-renewable and renewable energy consumption, differentiated by type of use — industrial, residential, and total final energy consumption — on manufacturing and services growth. We find that renewable energy enhances growth in high-growth sectors, i.e. the services sector in high-income economies and the manufacturing sector in middle-income economies. In the case of high-income countries, renewable energy is a complement to non-renewables, whereas in the case of middle-income countries the two are substitutes. The growth effects are primarily due to industrial energy consumption. T Based on our findings, we propose that an effective renewable energy incentives policy for middle-income countries should be directed at manufacturing enterprises, and in high-income countries these incentives should be directed at the services sector. • Endogenous growth framework with expanding variety of intermediate goods for energy consumption. • We test the effects renewables and non-renewables on the growth of manufacturing and services. • Renewable energy enhances growth in high-growth sectors. • These sectors are services in high-income and manufacturing in middle-income economies. • The growth effects are due to industrial energy and not to residential energy consumption. [ABSTRACT FROM AUTHOR]

• Diversification gains of a portfolio comprising developed markets, namely, the DJIA, S&P 500, and Nikkei 225, are examined against emerging and frontier Asian markets. • Diversification gains depend on whether frontier or emerging Asian markets are used for diversification. • Diversification opportunities differs between the two periods with varying end-dates. • Diversification gains depend on the frequency at which the portfolio is rebalanced. This study examines long- and short-run diversification gains for a portfolio comprising the developed (DJIA, S&P 500, and Nikkei 225) markets and emerging or frontier Asian markets. The study covers two periods: 2000–2013 and 2000–2018. This allows for a comparison of an investment made in the year 2000 and ended in either 2013 or 2018. Long- and short-term diversification gains are examined using different data frequencies to allow for the possibilities of portfolio rebalancing on a daily, weekly, or monthly basis. The study reveals differences in both long- and short-term diversification gains under these scenarios. [ABSTRACT FROM AUTHOR]

A correction is presented to the article “Relative export competitiveness of agricultural commodities and its determinants: Some evidence from India” which appeared in the May 2019 issue.

The decentralized revolution being ushered in by blockchain, an emerging technology with the potential to bring significant innovation and benefits, has also piqued the interest of major players in the energy supply industry, financial institutions, technology developers, academia, and national governments. How the deep integration of blockchain and energy will impact energy's prospects and the energy market remains an open question. This study conducts a composite of qualitative and quantitative analyses of 622 selected articles on blockchain in the energy field. It is dedicated to identifying feasible technical paths and potential themes. The results show that (1) Research in this field follows two main approaches: engineering- and management-oriented. (2) Management-oriented research has become mainstream. (3) Research has led to new transaction systems, and the commercialization of energy blockchains has driven research iterations. Thematic predictions call for more attention to the negative impacts of technology, such as new business risks, the problem of lagging regulations, and the drawbacks of high energy consumption. This study provides research references and practical suggestions for researchers, regulators, and enterprises. • This study explores energy blockchain research trends and paths. • The compositional strategy improves robustness and validates method inferences. • Engineering and management research are the main categories promoting each other. • Management-oriented blockchain commercialization research dominates. • Discussing blockchain's detrimental influence on energy is important. [ABSTRACT FROM AUTHOR]