COVID-19 and Information Flow between Cryptocurrencies, and conventional financial assets

In this paper, we analyze the impact of the ongoing COVID-19 pandemic on the information flow among the main cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin) and those of the fear index (VIX), Gold price, and the US equity market (S&P500). We use the transfer entropy measure to determine the information flow by allowing for nonlinear dynamics and extreme tail values in the series. Our results indicate that information flow and sharing have changed during the COVID-19 pandemic with the following main findings: i) cryptocurrencies show more correlation with VIX, Gold, and the US equity markets during the COVID-19 period;ii) Gold and VIX maintain their position as safe hedging tools against the pandemic;iii) during COVID-19, S&P500 is the dominant flow transmitter to the four cryptocurrencies, and iv) Ripple plays the dominant role of information flow to VIX, Gold, and S&P500.

COVID-19 and information flow between cryptocurrencies, and conventional financial assets.

In this paper, we analyze the impact of the ongoing COVID-19 pandemic on the information flow among the main cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin) and those of the fear index (VIX), Gold price, and the US equity market (S&P500). We use the transfer entropy measure to determine the information flow by allowing for nonlinear dynamics and extreme tail values in the series. Our results indicate that information flow and sharing have changed during the COVID-19 pandemic with the following main findings: i) cryptocurrencies show more correlation with VIX, Gold, and the US equity markets during the COVID-19 period; ii) Gold and VIX maintain their position as safe hedging tools against the pandemic; iii) during COVID-19, S&P500 is the dominant flow transmitter to the four cryptocurrencies, and iv) Ripple plays the dominant role of information flow to VIX, Gold, and S&P500.

Does economic policy uncertainty drive the dynamic spillover among traditional currencies and cryptocurrencies? The role of the COVID-19 pandemic.

The paper examines the dynamic spillover among traditional currencies and cryptocurrencies before and during the COVID-19 pandemic and investigates whether economic policy uncertainty (EPU) impacts this spillover. Based on the TVP-VAR approach, we find evidence of spillover effects among currencies, which increased widely during the pandemic. In addition, results suggest that almost all cryptocurrencies remain as "safe-haven" tools against market uncertainty during the COVID-19 period. Moreover, comparative analysis shows that the total connectedness for cryptocurrencies is lower than for traditional currencies during the crisis. Further analysis using quantile regression suggests that EPU exerts an impact on the total and the net spillovers with different degrees across currencies and this impact is affected by the health crisis. Our findings have important policy implications for policymakers, investors, and international traders.

Long Memory in the High Frequency Cryptocurrency Markets using Fractal Connectivity Analysis: The Impact of COVID-19

In this paper, we study the long memory behavior of the hourly cryptocurrency returns during the COVID-19 pandemic period. Initially, we apply different tests against the spurious long memory, with the results indicating the presence of true long memory for most cryptocurrencies. Yet, using the multivariate test, the series are found to be contaminated by level shifts or smooth trends. Then, we adopt the wavelet-based multivariate long memory approach suggested by Achard and Gannaz (2016) to model their long memory connectivity. The findings indicate a change in persistence for all series during the sample period. The fractal connectivity clustering indicates a similarity among Ethereum (ETH) and Litecoin (LTC), Monero (XMR), Bitcoin (BTC), and EOC token (EOS), while Stellar (XLM) is clustered away from the remaining series, indicating the absence of any interdependence with other crypto returns. Overall, shocks arising from COVID-19 crisis have led to changes in long-run correlation structure.

When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic.

This paper examines the dynamic spillovers among the major cryptocurrencies under different market conditions and accounts for the ongoing COVID-19 health crisis. We also investigate whether cryptocurrency policy (CCPO) uncertainty and cryptocurrency price (CCPR) uncertainty affect the dynamic connectedness. We adopt the Quantile-VAR approach to capture the left and right tails of the distributions corresponding to return spillovers under different market conditions. Generally, cryptocurrencies show heterogeneous responses to the occurrence of the COVID-19 pandemic. We find that the total spillover index (TCI) varies across quantiles and rises widely during extreme market conditions, with a noticeable impact of the COVID-19 pandemic. Bitcoin lost its position as a dominant "hedger" during the health crisis, while Litecoin became the most dominant "hedger" and/or "safe-haven" asset before and during the pandemic period. Moreover, our analysis shows a significant impact of market uncertainties on total and net connectedness among the five cryptocurrencies. We argue that the COVID-19 pandemic crisis plays a vital role on the relationship between CCPO as well as CCPR and the dynamic connectedness across all market conditions.

Multivariate long memory structure in the cryptocurrency markets: The impact of COVID-19

In this paper, we study the long memory behavior of Bitcoin, Litecoin, Ethereum, Ripple, Monero, and Dash with a focus on the COVID-19 period. Initially, we apply a time-varying Lifting method to estimate the Hurst exponent for each cryptocurrency. Then we test for a change in persistence over time. To model the multivariate connectivity, the wavelet-based multivariate long memory approach proposed by Achard and Gannaz (2016) is implemented. Our results indicate a change in the long-range dependence for the majority of cryptocurrencies, with a noticeable downward trend in persistence after the 2017 bubble and then a dramatic drop after the outbreak of COVID-19. The drop in persistence after COVID-19 is further illustrated by the Fractal connectivity matrix obtained from the Wavelet long-memory model. Our findings provide important implications regarding the evolution of market efficiency in the cryptocurrency market and the associated fractal structure and dynamics of the crypto prices over time.

Information sharing among cryptocurrencies: Evidence from mutual information and approximate entropy during COVID-19.

In this paper, we use mutual information approach to investigate the information sharing between cryptocurrencies during the COVID-19 crisis. We also use the approximate entropy to study their dynamics before COVID-19 and during the pandemic. Results from the mutual information measure indicate a rise in information sharing and ordering in the cryptocurrency markets in the pandemic period, while the evidence from the approximate entropy estimates indicates a rise in randomness during the COVID-19 period. Our results provide new insights on the information sharing of cryptocurrencies and their reaction to shocks such as the COVID-19 pandemic.

Dynamic connectedness between uncertainty and energy markets: Do investor sentiments matter?

This paper examines the dynamics between the energy markets and uncertainty indices from January 1st, 2001 till July 1st, 2020, using the time-domain TVP-VAR-based connectedness approach of Antonakakis and Gabauer (2017). In particular, we examine whether Economic Policy Uncertainty (EPU), Geopolitical Risk (GPR), World Trade Uncertainty (WTU), and Equity Market Uncertainty (EMU) have an impact on the dynamics of returns of oil, gas, and coal markets. Results suggest that the average influence of market uncertainty on energy markets is approximately 53%. Second, we find that the EPU contributes the most to the energy markets, followed by the World Trade Uncertainty index. Third, considering the energy markets, we find that the oil markets contribute the most to other markets. Fourth, we find that the EMU receives the most contribution from other markets, followed by the EPU. Finally, we observe that the total connectedness index is relatively high, coinciding with the Global Financial Crisis of 2008 and the COVID-19 pandemic outbreak. Further analysis of the possible effect of the investor sentiment on the dynamic connectedness shows that the consumer sentiment index (CSI) has a negative (positive) effect on the uncertainty (energy) net connectedness. Our findings have important implications for risk management in energy markets and entail some policy implications for regulators.