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Given the growing importance of cryptocurrencies and the technique called “SegWit” that allows to compile more transactions in a mined block, the electricity consumed per block might potentially decrease. The purpose of this study is to consider that the difficulty to mine a block might be a better indicator of the Bitcoin\Ether’s electricity consumption.

This study applies the vector error correction model to investigate data related to primary energy consumption and electricity production, supply and consumption for Bitcoin and Ether hashrates from 2016M1 to 2021M5.

The hashrate (difficulty of solving the cryptographic problem related to the validation of a transaction) is found to have a positive cointegration with energy and electricity consumption. Despite the launch of the Segregation Witness (SegWit) mechanism allowing blocks to handle a higher number of transactions per block, this Bitcoin and Ether growing need in electricity has significantly been increasing since October 2019.

The major contribution of this study is to investigate a more relevant indicator, namely, hashrate (computational difficulty to solve cryptographic enigma associated with cryptocurrencies-related transaction). The approach of this study can be justified by the fact that there exists a technical solution consisting in increasing the number of transactions per blocks so that less electricity might be required to validate a transaction.

How a micro-founded discipline such as economics could deal with the increasing global economic reality? This question has been asked frequently since the last economic crisis that appeared in 2008. In this challenging context, some commentators have turned their attention to a new area of knowledge coming from physics: econophysics which mainly focuses on a macro-analysis of economic systems. By showing that concepts used by econophysicists are consistent with an existing economic knowledge (developed by J.S. Mill), the purpose of this paper is to claim that an interdisciplinary perspective is possible between these two communities.

The authors propose a historical and conceptual analysis of the key concept of emergence to emphasize the potential bridge between econophysics and economics.

Six methodological arguments will be developed in order to show the existence of conceptual bridges as a necessary condition for the elaboration of a common language between economists and econophysics which would not be superfluous, in this challenging context, to clarify the growing complexity of economic phenomena.

Although the economics and econophysics study same the complex economic phenomena, very few collaborations exist between them. This paper paves a conceptual/methodological path for more collaboration between the two fields.

This paper aims to contribute to recent debates about financial knowledge by opening the black box of its algorithmization to understand how information systems can address the major challenges related to interactions between algorithmic trading and financial markets.

The paper analyses financial algorithms in three steps. First, the authors introduce the phenomenon of flash crash; second, the authors conduct an epistemological analysis of algorithmization and identify three epistemological regimes – epistemic, operational and authority – which differ in terms of how they deal with financial information. Third, the authors demonstrate that a flash crash emerges when there is a disconnection between these three regimes.

The authors open the black box of financial algorithms to understand why flash crashes occur and how information technology research can address the problem. A flash crash is a very rapid and deep fall in security prices in a very short time due to an algorithmic misunderstanding of the market. Thus, the authors investigate the problem and propose an interdisciplinary approach to clarify the scope of algorithmization of financial markets.

To manage the misalignment of information and potential disconnection between the three regimes, the authors suggest that information technology can embrace the complexity of the algorithmization of financial knowledge by diversifying its implementation through the development of a multi-sensorial platform. The authors propose sonification as a new mechanism for capturing and understanding financial information. This approach is then presented as a new research area that can contribute to the way financial innovations interact with information technology.

This paper aims to offer an empirical study of the impact of institutional quality on the banking system risk and credit risk.

Applying cross-sectional dependent tests and stationary tests to check the property of our sample, the panel corrected standard errors model is recruited as the main estimator, while feasible generalized least squares, pool ordinary least squares (OLS), robust pool OLS and other estimators are used as a robustness check for an unbalanced panel data for 56 economies divided into three subsamples between 2002 and 2015.

The empirical results show several significant contributions. First, an improvement in institutional quality is an important factor to reduce the banking system risk. This effect of the institutions is less important in well-capitalized, highly profitable and in high-economic growth countries. This effect is also stronger in highly liquid banking systems. Notably, a better institutional quality helps to reduce the banking system risk in the highly concentrated banking system. Second, institutional quality has a significant negative relationship with the banking credit risk, especially in highly concentrated banking systems and in high-growth countries. This influence is weaker in highly liquid and well-capitalized banking systems. Finally, better institutions reduce the positive effect of trade openness, but it induces a higher credit risk for the banking system from the trade openness. Notably, a better institutional quality enhances the negative effect of foreign direct investment (FDI) inflow on both banking system risk and credit risk. These findings are documented for a global sample and three subsamples: low and lower-middle-income economies, upper-middle-income economies and high-income economies.

This study provides some recommendations, for policymakers, on the roles of institutions in the banking system and financial stability.

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

There are four categories of ABM in economics.

This paper suggests a methodological categorization of ABM works in economics.

Even though Bitcoin has been often labelled as a safe haven asset class in the literature, the influence of economic policy uncertainty (EPU) on the diversifying opportunities offered by Bitcoin in relation to other assets needs to be investigated. This paper aims to investigate how the EPU affects diversification of commodity, conventional, Islamic and sustainable equity returns in relation to its impact on Bitcoin returns.

The authors use advanced time-series econometrics, namely, multivariate generalized autoregressive conditional heteroscedastic-dynamic conditional correlation and continuous wavelet transformation, for the analysis of the daily returns for the aforementioned assets between 01 August 2011 and 01 September 2019.

First, the authors found a strong evidence of Bitcoin’s mean reverting trend in the long run while its volatility has decreased significantly since 2013. After separating the EPU into two regimes (high and low), diversification opportunities with Bitcoin seems to disappear in a high EPU period, while the hedging opportunity tends to prevail in a low EPU period for all classes of assets. Importantly, the findings indicate that Bitcoin offers short-term diversification for sustainable and Islamic equity as well as energy stocks during a low uncertainty period. Consequently, in relation to the policy uncertainty, Bitcoin provides similar hedging opportunities than commodities like Gold and Silver. Overall, the study shows that EPU is remarkably important in explaining the average portfolio returns of Bitcoin, suggesting that this indicator can be perceived as a decent explanatory factor for portfolio diversification.

The study significantly extends the empirical literature of Bitcoin’s portfolio diversification by taking EPU into consideration. To the best of authors’ knowledge, this is one of the few studies to investigate the asymmetric effects of US EPU on Bitcoin’s hedging capabilities by taking into account major conventional equity, sustainable equity, Islamic equity, gold, silver and oil.

This study aims to examine the spillover effects of trans-Atlantic macroeconomic uncertainties on the local stock market returns in the USA and eight selected European countries, namely, Germany, France, Spain, Italy, Greece, Ireland, Sweden and the UK, during the 2000-2019 period.

This paper applies the dynamic conditional correlation multivariate GARCH model (i.e. multivariate generalized autoregressive conditional heteroskedasticity model or DCC MGARCH) to examine the potential existence of the spillover from the uncertainty of the USA to EU stock markets and vice versa. To capture different dynamic relationships between multiple time-series variables following different regimes, this paper applies the Markov switching model to the stock returns of both the USA and the eight major stock markets.

The increases in US uncertainty have significant negative impacts on all EU stock returns, whereas only the increases in the uncertainties of Spain, Ireland, Sweden and the UK have significant negative impacts on US stock returns. Notably, the economic policy uncertainty (EPU) in the USA has a dynamic effect on the European stock markets. In a bear market (State 1), the increases in the EPU of the USA and EU have significant negative impacts on EU stock returns in most cases. However, only the increase in US EPU has significant negative impacts on EU stock returns in bull markets (State 2). Reciprocally, the increases in the EU EPUs of Germany, Spain and the UK have significant impacts on US stock returns in bear market.

The observations challenge the conventional wisdom according to which only larger economies can lead the smaller counterparts. The findings also highlight the stronger dependence of the US stock market on international macroeconomic uncertainty.

This study investigates the effect of global and domestic uncertainty on the dynamics of portfolio investment in 21 economies (mostly advanced and larger emerging economies) from 2001–2016.

Specifically, the evolution of the net portfolio equity investment inflows (FPI net inflows) and the evolution of net portfolio investment (FPI net) are investigated in a context in which the degree and the volatility of domestic economic policy uncertainty (EPU) and world uncertainty index (WUI) varied. The authors provide an empirical analysis through the sequential (two-stage) estimation of linear panel data models for unbalanced panel data.

An increase in the degree and volatility of domestic EPU has a significant negative influence on FPI net inflows, while an increase in WUI has a significant positive one. Notably, a simultaneous increase in the domestic EPU and WUI enhances the net inflows of FPI, whereas a simultaneous increase in the volatility of these indicators reduces the net inflows of FPI. An increase in the degree and volatility of both domestic EPU and WUI have a significant positive effect on the net portfolio investment, implying that a significant net portfolio investment is going out of the country.

The results of this study encourage international investors to consider uncertainty indicators (and, more specifically, their variations) in their portfolio strategy to optimize their position on the international markets. The findings of this study invite policy-makers from large countries to reduce the perceived domestic uncertainty since this parameter can influence international investors' sensitivity and willingness to diversify their position out of the country.

The authors' approach focuses on the variations of uncertainty (existing literature mainly works with the indicators). While the results confirm the role played by large markets in international portfolio investment management, it nuances the changes in the portfolio management behaviors toward other markets when facing a changing uncertainty.

This study aims to investigate the influences of global uncertainty indicators volatility on the domestic socioeconomic and environmental vulnerability in a sample of 54 developing countries.

The two-step system generalized method of moments estimator is recruited to deal with autoregression and endogeneity matter in our dynamic panel data. Seven different global uncertainty indicators (US trade uncertainty; world trade uncertainty; economic policy uncertainty; world commodities and oil prices; the geopolitical risk index and the world uncertainty index) have been mobilized and compared for their empirical impact on the economic (growth and GDP), social (the misery index and income inequality) and environmental (CO₂ emissions) vulnerabilities of nations.

Our empirical estimations suggest that the socioeconomic and environmental vulnerability cannot be solved through the same pattern: all decrease of a particular aspect will necessarily have a cost and an opposite influence on at least one of the other aspects of the nations' vulnerability.

The originality of this article is to combine these three dimensions of vulnerability in the same investigation. To our knowledge, our research is one of the few providing a joint analysis of the influence of global uncertainty on the economic and socioenvironmental countries' vulnerabilities – given the fact social, economic and environmental aspects are at the heart of the UN sustainable goals, our study can be seen as an investigation of the nations' capabilities to work proactively on meaningful sustainable goals in an increasingly uncertain world.

This study aims at determining the portfolio value at risk (VAR) and market value of Fintech firms and compare it with their counterparts.

By using on a dataset from 46 countries between 2009 and 2018, the authors use five measures of VaR to investigate their empirical dynamics in relation with the market value of Fintech and non-Fintech companies.

The empirical results indicate that Fintech firms' portfolios have a higher financial risk and a higher market value in comparison to non-fintech firms' portfolios. Furthermore, the authors also report that the Fintech firm portfolios experience more financial risk regardless of the holding period as long-term (one year) or short-term (quarter).

There are some limitations in this research. This research does not segregate Fintech firms into their different types of services, such as direct financial investment services, loan provision services, insurance services (InsurTech), etc. The authors only aggregate the Fintech firms by country and region. Future research may consider analysing Fintech firms by differentiating the kind of financial services they offer

Given the importance of their market value, the results imply that Fintech companies might contribute significantly to financial fluctuations in case of large variations of the market. In terms of policy recommendation, this observation requires a particular attention from the regulatory bodies who need to find the best economic balance between promoting innovation/financial technology and regulating the Fintech companies.

This paper is the first study clarifying the relation of financial risk and market value for the Fintech firms, using the large enough database to obtain significant results. This article implies that Fintech companies require a robust risk management framework