ABSTRACT
Purpose: This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance. Design/methodology/approach: The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic. Findings: The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP. Research limitations/implications: This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further. Practical implications: The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance. Originality/value: The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics. © 2023, Emerald Publishing Limited.
ABSTRACT
In July 2021, the European central bank (ECB) announced the application of new environmental criteria to purchase private assets as part of its Quantitative Easing (QE) program. Using a Bayesian VAR model with time varying parameters and stochastic volatility (TVP-BVAR-SV), we investigate the transmission of Green bond shocks to the stock market during the pre-and-post COVID-19 pandemic. We document a nonlinear relation between the green bonds and the green equities. Our findings suggest that the ECB's Green QE can drive investors towards green investment in the stock market through the green bond market during the non-crisis period. However, we show that the proper transmission of Green QE shocks to the stock market depends on the economic conditions and could not be effective during the crisis period. Our results also support previous findings that state the growing demand for sustainable investing after COVID-19. These findings have important implications for investment professionals, policymakers, and environmentally concerned actors. © 2022 Elsevier Inc.
ABSTRACT
Purpose: This article aims to uncover the impact of Google Trends on cryptocurrency markets beyond Bitcoin during the time of increased attention to altcoins, especially during the COVID-19 pandemic. Design/methodology/approach: This paper analyses the nexus among the Google Trends and six cryptocurrencies, namely Bitcoin, New Economy Movement (NEM), Dash, Ethereum, Ripple and Litecoin by utilizing the causality-in-quantiles technique on data comprised of the years January 2016–March 2021. Findings: The findings show that Google Trends cause the Litecoin, Bitcoin, Ripple, Ethereum and NEM prices at majority of the quantiles except for Dash. Originality/value: The findings will help investors to develop more in-depth understanding of impact of Google Trends on cryptocurrency prices and build successful trading strategies in a more matured digital assets ecosystem. © 2022, Emerald Publishing Limited.
ABSTRACT
This paper investigates the directional causal relationship and information transmission among the returns of West Texas Intermediate (WTI), Brent, major cryptocurrencies, and stablecoins by drawing on daily data from July 2019 to July 2020. Applying effective transfer entropy, a non-parametric statistic, the results show that the direction of the causal relationship and the nature of information spillovers changed after the COVID-19 pandemic. More precisely, our findings reveal that WTI and Brent are leading the prices of Bitcoin and Bitcoin Cash. Conversely, Bitcoin futures and stablecoins (TrueUSD and USD Coin) are leading WTI and Brent prices. In addition, the stablecoin Tether became a leader against Brent prices after the pandemic, although it is still following WTI prices. Moreover, Ethereum and USD coin preserved their position as leaders against Brent prices. Interestingly, our results also reveal that Ethereum, Litecoin, and Ripple preserved their position as leaders of WTI prices. The change in the nature of directional causality and the spillover effect after the COVID-19 crisis provide valuable information for practitioners, investors, and policymakers on how the ongoing pandemic influences the connection and network correlation among the energy, cryptocurrency, and stablecoin markets. © 2022 Elsevier Inc.
ABSTRACT
Purpose This paper aims to empirically investigate the extent to which interdependence in markets may be driven by COVID-19 effects. Design/methodology/approach The current global COVID-19 pandemic is adversely affecting the oil market (West Texas Intermediate) and crypto-assets markets. Findings The authors find that the dependence structure changes significantly after the global pandemic, providing valuable information on how the COVID-19 crisis affects interdependencies. The results also prove that the performance of digital gold seems to be better compared to stablecoin. Originality/value The authors fit copulas to pairs of before and after returns, analyze the observed changes in the dependence structure and discuss asymmetries on propagation of crisis. The authors also use the findings to construct portfolios possessing desirable expected behavior.
ABSTRACT
This paper examines the relationship between real economic activity and the financial and commodity markets using two approaches. First, we use the Discrete Wavelet Method to investigate the lead-lag dependence between real economic activity and these markets. Second, we use the Time-Varying Parameter VAR (TVP-VAR) model with stochastic volatility to examine the short- and long-term level of integration among these variables. Our wavelet results show that although the real economic activity shock lead co-movement with the chosen markets, it was led by these markets during periods of economic downturn as evidenced during the COVID-19 pandemic. Regarding the TVP-VAR results, we find that the connectedness between economic activity and the chosen markets is stronger during economic downturns or in the long run. © 2022