No abstract

The present study addresses one of the most problematic phenomena: Bitcoin price. We explore the Granger causality for two relationships (Bitcoin price and trade transactions; Bitcoin price and investors' attractiveness) from a frequency domain perspective-based on unconditional and conditional data analysis. Accurately, this research empirically assesses the causal links between these variables unconditionally on the one hand and conditioning upon relevant control variables (recorded in literature) on the other hand. The observed outcomes reveal some differences with respect to the frequencies involved, highlighting the difficulty to reach clearer insights and better paths into this nascent crypto-currency. Beyond the nuances of short-, medium- and long-run frequencies, this paper confirms the extremely speculative nature of Bitcoin without overlooking its usefulness in economic reasons. The consideration of the Chinese market index, the hash rate, the monetary velocity and the estimated output volume has led to solid and meaningful findings connecting further Bitcoin to speculation.

This paper provides an innovative perspective on the role of gold as a hedge and safe haven. We use a quantile-on-quantile regression approach to capture the dependence structure between gold returns and changes in uncertainty under different gold market conditions, while considering the nuances of uncertainty levels. To capture the core uncertainty effects on gold returns, a dynamic factor model is used. This technique allows summarizing the impact of six different indexes (namely economic, macroeconomic, microeconomic, monetary policy, financial and political uncertainties) within one aggregate measure of uncertainty. In doing so, we show that the gold's role as a hedge and safe haven cannot be assumed to hold at all times. This ability seems to be sensitive to the gold's various market states (bearish, normal or bullish) and to whether the uncertainty is low, middle or high. Interestingly, we find a positive and strong relationship between gold returns and the uncertainty composite indicator when the uncertainty attains its highest level and under normal gold market scenario. This suggests that holding a diversified portfolio composed of gold could help protecting against exposure to uncertain risks. Acknowledgement: The authors would like to thank the editor Sushanta Mallick and the two anonymous Reviewers for helpful and insightful comments and suggestions on an earlier version of this article. Highlights We examine the response of gold returns to different uncertainty indicators. We use a quantile-on-quantile regression model.  We develop an uncertainty composite indicator based on six uncertainty factors. The hedge and safe haven ability of gold is conditional on gold market states. The gold's role as a hedge and safe haven depends on the nuances of uncertainty.

No abstract

The excessive volatility generated by the COVID-19 pandemic highlights that environmental and social issues are potential elements that businesses and governments must manage effectively and swiftly. This study seeks to test whether the rising anxiety over this pandemic has affected the attitudes and choices towards environmentally and socially responsible investing. To this end, we first use machine learning tools to examine tweets related to this unprecedented and wild shock. Second, we compare the impact of these sentiments on the stock performance of companies from the S&P500 that meet environmental and social sustainability criteria for three COVID-19 phases with varying levels of anxiety, which we label incubation, fever and the increasing risk of second wave pandemic (in the absence of vaccine). Our findings reveal that the increasing uncertainty and worries over COVID-19 and its consequences has not distracted investors' attention away from environmental and social issues, but companies with responsible strategies on environmental issues that specifically address climate responsibility are likely to be more responsive to sentiments at the current situation of emergency.

Instead of analyzing the causality between two time series (unconditional analysis), as it is usually done, the present study deals with the nexus between oil price and Russia"s real exchange rate conditioning upon potential control variables at well-specified horizons and on a frequency by frequency basis. This research accounts also for the possible transient linkages and signal discontinuities. A major finding of this paper is deeply suggestive of a sharp causality running from oil price to real exchange rate in lower frequencies. This implies that Russia should better tackle with turbulence triggered by oil price and continue to reduce its energy dependency via drastic and proactive measures. The economic and fiscal initiatives of Putin administration may help to cope with sudden shocks, to lessen the great oil dependence and to build confidence needed for economic recovery. While our research does not say much about the routes through which oil price may affect differently real exchange rate, it clearly indicates the presence of short-term relationship conditional to GDP, government expenditures, terms of trade and productivity differential. The conditional analysis and signal detection appear as meaningful exercises to find new insights into the focal issue.

Theory suggests that partisan conflict negatively affects the possibility of economic policy change, implying that financial markets tend to operate under lower policy risk. Given that stockreturn volatility measures risk, if the gridlock argument holds, stock-market volatility should be lower under divided than under a unified government. Using a partisan conflict index (PCI), we empirically confirm this theoretical argument for the U.S. stock market based on quantiles-based regressions. In particular, quantile-on-quantile regressions show that PCI tends to predict reduced volatility, with the effect being stronger at levels of volatility that are moderately low (i.e., below the median, but not at its extreme) for an increase in the predictor, especially with moderately low and high initial values (i.e., when PCI is at quantiles around the median).

:We assess the causality between electricity consumption and economic growth for a panel of twelve MENA countries (seven energy exporters and five energy importers) over the period 1975-2010 within a bivariate framework using panel cointegration methods and panel causality test. By doing so, we show that 16.66% of MENA countries supported the growth hypothesis, 25% the conservation hypothesis, 33.33% the feedback hypothesis and 25% the neutrality hypothesis. For energy exporters, we support the growth hypothesis in 14.28% of cases at the same way of conservation hypothesis, the feedback hypothesis in 42.88% and the neutrality hypothesis in 28.57%. For energy importers, almost 60% of cases provide support for conservation hypothesis. Additionally, we show that Iran and Turkey behave better than the rest of countries in terms of the focal link. We attribute this apparently result to the good structuring of the electricity sector.