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This study aims to empirically investigate the linkages between digital trails of social signals (content and profile features of bitcoin-related tweets) and bitcoin price return using a VAR-BEKK-GARCH model.

Bitcoin-related tweets were collected every hour for six months from September 1, 2020, to February 29, 2021. The analysis involved two steps: first, examining tweet content, profiles, sentiment and emotions; and second, investigating the relationship between social signal volatility and hourly bitcoin price return.

Results indicate that bitcoin price changes can impact the sentiment expressed in tweets about bitcoin, and vice versa. While sadness exhibits a bidirectional volatility spillover with bitcoin, fear and anger display a one-period lag. Quartile analyses reveal that only fear in the second quartile shows a bidirectional spillover effect with bitcoin, while all other emotions except sadness demonstrate a unidirectional spillover effect in all remaining quartiles.

The study uses a novel two-step approach to analyze volatility spillovers between social signals and bitcoin price returns. Findings can guide investors and portfolio managers in making better allocation decisions and assist policymakers and regulators in reducing the adverse effects of bitcoin’s volatility on financial system stability.

With a substantial return and volatility characteristic of Bitcoin, which may be seen as a new category of investment assets, better understanding of the nature of return and volatility spillover can help investors and regulators in achieving the potential goal from portfolio diversification. The paper aims to discuss these issues.

This paper explores the return and volatility transmission between the Bitcoin, as the largest cryptocurrency, and other traditional asset classes, namely stock, bond and currencies from the standpoint of Turkey over the period July, 2010–June, 2018 using the newly developed multivariate econometric technique, VAR–GARCH, in mean framework with the BEKK representation.

The empirical results reveal the existence of the positive unilateral return spillovers from the bond market to Bitcoin market. Regarding the results of shock and volatility spillovers, there exists strong evidence of bidirectional cross-market shock and volatility spillover effects between Bitcoin and all other financial asset classes, except US Dollar exchange rate.

The important extention is the adoption of a newly developed multivariate econometric technique, VAR–GARCH, in mean framework with the BEKK representation, proposed by Engle and Kroner (1995), which is employed for the first time specifically to examine the extent of integration in terms of volatility and return between Bitcoin and key asset classes. Second, Bitcoin has experienced a rapid growth since around a decade and a number of investors are showing interest in its potential as an integrative part of portfolio diversification. The information provided by empirical results gives empirical bases from which to address topics concerning hedging purposes and optimal portfolio allocation. It is also increasingly important to analyze the current behavior of Bitcoin in relation to other assets to provide policy makers and regulatory bodies with guidance on the role of the Bitcoin as an investment asset in Turkey. Thus, this is the first serious attempt at exploring the potential for Bitcoin to offer diversification opportunities in the context of Turkey.

Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018.

After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches.

The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance.

The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

The development of green economy is of academic and policy importance to governments and policymakers worldwide. In the light of the necessity of renewable energy to sustain green economic growth, this study aims to examine the relationship between renewable energy consumption and green economic growth, controlling for the impact of trade openness for Organization for Economic Co-operation and Development countries over the period 1990-2015, within a multivariate panel data framework.

To investigate the long-run relationship between variables, panel cointegration tests are performed. Panel Granger causality based on vector error correction models is adopted to understand the short- and long-run dynamics of the data. Furthermore, ordinary least square (OLS), dynamic OLS and fully modified OLS methods are used to confirm the long-run elasticity of green growth for renewable energy consumption and trade openness. Moreover, system generalized method of moment is applied to eliminate serial correlation, heteroscedasticity and endogeneity problems. The authors used the panel Granger causality test developed by Dumitrescu and Hurlin (2012) to infer the directionality of the causal relationship, allowing for both the cross-sectional dependence and heterogeneity.

The results suggest that renewable energy consumption and trade openness exert positive effects on green economic growth. The results of long-run estimates of green economic growth reveal that the long-run elasticity of green economic growth for trade openness is much greater than for renewable energy consumption. The estimated results of the Dumitrescu and Hurlin (2012) test reveal bidirectional causality between green economic growth and renewable energy consumption, providing support for the feedback hypothesis.

This paper provides strong evidence of the contribution of renewable energy consumption on green economy for a wide range of countries. Despite the costs of establishing renewable energy facilities, it is evident that these facilities contribute to the green growth of an economy. Governments and public authorities should promote the consumption of renewable energy and should have a support policy to promote an active renewable energy market. Furthermore, the regulators must constitute an efficient regulatory framework to favor the renewable energy consumption.

Many countries focus on increasing their GDP without taking the environmental impacts of the growth process into account. This paper shows that renewable energy consumption points to the fact that countries can still increase their economic growth with minimal damage to environment. Despite the costs of adopting renewable energy technologies, there is still room for economic growth.

This paper provides evidence on the contribution of renewable energy consumption on green economic growth for a wide range of countries. The paper focuses on the impact of renewable energy on economic growth by taking environmental degradation into consideration on a wide scale of countries.

The existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach.

Applying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed.

Interestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market.

Overall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.

This study investigates possible shock transmission and volatility spillover effects among the exchange rate changes and international portfolio flows for United States vis-à-vis two fast-growing emerging country groups: the BRICS (Brazil, Russia, India, China and South Africa) and MINT (Mexico, Indonesia, Nigeria and Turkey).

Applying VAR-BEKK-GARCH model, the evidence indicates that exchange rate fluctuations have a negative impact on net equity flows in Brazil, Russia, India and Turkey; thus, supporting the view that exchange rate uncertainty is an important driver of equity home bias.

As for the comparison of the pre- and post-crisis period, the findings support the evidence that the post-crisis period witnessed a greater number of cases of significant shock and volatility spillovers among exchange rate uncertainty and portfolio flows.

Overall, the empirical results provide fresh insights and policy implications for domestic and international investors through investment activities, and for policymakers through maintaining economic and financial stability.