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.     

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.     

A comparative analysis of cryptocurrency returns and economic policy uncertainty pre- and post-Covid-19

This study analyzes the impact of economic policy uncertainty (EPU) on cryptocurrency returns for a sample of 100 highly capitalized cryptocurrencies from January 2016 to May 2021. The results of the panel data analysis and quantile regression show that increases in global EPU have a positive impact on cryptocurrency returns for lower cryptocurrency returns quantiles and an adverse impact for upper quantiles. In line with the existing literature, the Covid-19 pandemic resulted in higher returns for cryptocurrencies. Inclusion of a Covid-19 dummy in the models strengthened the impact of EPU on cryptocurrency returns. Furthermore, the relationship between the change in EPU and cryptocurrency returns was direct in the pre-Covid-19 period but inverse in the post-Covid-19 period. These results imply that cryptocurrencies act more like traditional financial assets in the post-Covid-19 era.     

Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis

This paper examines the quantile dependence, connectedness, and return spillovers between gold and the price returns of leading cryptocurrencies, using quantile cross-spectral, the return spillovers based the quantile VAR, and quantile connectedness approaches. The results show that the dependencies within cryptocurrencies are highly symmetric and sensitive to different quantile arrangements. Under normal market conditions, we find a high positive dependence within cryptocurrencies and a low positive dependence between cryptocurrencies and gold. The dependence is higher at long term than intermediate- and short- terms before the pandemic during bearish market conditions. In contrast, the degree of dependence decreases at the intermediate- and long-terms during COVID-19 period than before. Moreover, the magnitude of return spillovers is higher at lower quantile (bearish market) than upper quantile (bullish market). Gold serves as a safe haven and diversifier asset for cryptocurrencies during COVID-19 outbreak at both intermediate and long terms.     

NFTs,DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis

This paper examines the efficiency and asymmetric multifractal features of NFTs, DeFi, cryptocurrencies, and traditional assets using Asymmetric Multifractal Cross-Correlations Analysis covering the period from November 2017 to February 2022. Considering the full sample with a significant variation among asset classes, the study reveals DeFi-DigiByte is the most efficient while the cryptocurrency-Tether is the least efficient. However, S&P 500 showed high efficiency before COVID-19, and DeFi-Enjin Coin advanced as the most efficient asset during COVID-19. The volatility dynamics of NFTs, DeFi, and cryptocurrencies follow strong nonlinear cross-correlations, but evidence of weaker nonlinearity exists in traditional assets. Additionally, the sensitivity to smaller events in bull markets is high for NFTs and DeFi. The findings have significant implications for portfolio diversification when an investor's portfolio set includes traditional assets and cryptocurrency and relatively new blockchain-based assets like NFTs and DeFi.     

Diversifying equity with cryptocurrencies during COVID-19

Literature suggests assets become more correlated during economic downturns. The COVID-19 crisis provides an unprecedented opportunity to investigate this considerably further. Further, whether cryptocurrencies provide a diversification for equities is still an unsettled issue. We employ several econometric procedures, including wavelet coherence, and neural network analyses to rigorously examine the role of COVID-19 on the paired co-movements of four cryptocurrencies, with seven equity indices (matching countries particularly impacted by COVID-19). Our period of study includes one year prior to the onset of COVID-19, and one year during the pandemic, extending deeper into the pandemic period (February 2021) than most previous studies. We find co-movements between cryptocurrencies and equity indices gradually increased as COVID-19 progressed. However, most of these co-movements are either modestly positively correlated, or minimal, suggesting cryptocurrencies in general do not provide a diversification benefit during either normal times or downturns. An exception, however, is the co-movement of tether. Tether co-moves negatively with equities to an economically significant degree, both pre COVID-19, and considerably more during COVID-19. Co-movements between tether and equity indices spiked sharply during identified waves of the pandemic. Tether appears to be an important safe haven during times of market turmoil, consistent with investors seeking USD liquidity during periods of volatility.     

Information transmission among energy markets,cryptocurrencies, and stablecoins under pandemic conditions

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.     

On spillover effects between cryptocurrency-linked stocks and the cryptocurrency market: Evidence from Australia

This paper categorizes Australian listed cryptocurrency-linked stocks (CLS) by their involvement as a user, developer and diffuser, and investor of blockchain technology and cryptocurrencies based on company announcements and published information on the company websites. By distinguishing CLS engagement with blockchain technology, we examine their returns and volatility spillover with the cryptocurrency market over the period 1 September 2017 to 7 June 2018, spanning important episodes and dynamics in the cryptocurrency market in 2017-2018, and the emergence of Australian CLS. Utilizing the Diebold and Yilmaz (2012) spillover methodology, we find significant unidirectional return spillover and weak volatility spillover from the cryptocurrency market to CLS, after controlling return dynamics of the Australian dollar, Gold and commodity. However, CLS with high involvement in blockchain technology displays stronger connectedness to the cryptocurrency market through return spillover relative to low involvement CLS. Our findings indicate that investors incorporate the price dynamics of cryptocurrencies into their trading decisions for CLS.     

“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic

In this paper, we empirically analyse the performance of five gold-backed stablecoins during the COVID-19 pandemic and compare them to gold, Bitcoin and Tether. In the digital assets' ecosystem, gold-backed cryptocurrencies have the potential to address regulatory and policy concerns by decreasing volatility of cryptocurrency prices and facilitating broader cryptocurrency adoption. We find that during the COVID-19 pandemic, gold-backed cryptocurrencies were susceptible to volatility transmitted from gold markets. Our results indicate that for the selected gold-backed cryptocurrencies, their volatility, and as a consequence, risks associated with volatility, remained comparable to the Bitcoin. In addition, gold-backed cryptocurrencies did not show safe-haven potential comparable to their underlying precious metal, gold.     

Have cryptocurrencies become an inflation hedge after the reopening of the U.S. economy?

In this paper, we study how the comovement between cryptocurrencies and the U.S. inflation expectation rates has changed during the post-reopening of the U.S. economy after the Covid-19 crisis. To do so, we develop a new concept of “exceedance co-kurtosis” which allows us to quantify asymmetry in strong comovement between each cryptocurrency and the inflation expectation rate. The key findings are as follows. First, we show the change in the co-kurtosis asymmetry for major cryptocurrencies: the downside co-kurtosis was higher than the upside co-kurtosis but it decreased after the reopening of the economy. Although the unconditional correlations between cryptocurrencies and the inflation expectation rates remain very low, our results indicate that the major cryptocurrencies become a slightly better inflation hedge after the reopening. Second and more interestingly, the results do not depend on whether a cryptocurrency has a cap on maximum supply or not. Therefore, treating the major cryptocurrencies as digital commodities could be misleading from the viewpoint of portfolio optimization.     

Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic

This study aims to examine whether the prices and returns of two cryptocurrencies, Dogecoin and Ethereum, are affected by Twitter engagement following the COVID-19 pandemic. We use the autoregressive integrated moving average with explanatory variables model to integrate the effects of investor attention and engagement on Dogecoin and Ethereum returns using data from December 31, 2020, to May 12, 2021. The results provide evidence supporting the hypothesis of a strong effect of Twitter investor engagement on Dogecoin returns; however, no potential impact is identified for Ethereum. These findings add to the growing evidence regarding the effect of social media on the cryptocurrency market and have useful implications for investors and corporate investment managers concerning investment decisions and trading strategies.     

The entry and exit dynamics of the cryptocurrency market

This paper presents an analysis of the entry and exit dynamics of the cryptocurrency market that focuses on the growth of initial coin offerings during 2015–2020. We used two different datasets: one includes long-lived cryptocurrencies, while the other includes the whole cryptocurrency system at our disposal–that is, it considers the entering and exiting cryptocurrencies. Comparing the dynamics between both datasets with the index cohesive force approach, we assessed how the growth of the initial coin offerings and the exiting cryptocurrencies affected the connectedness of the market. Our results show that the expansion of the cryptocurrency system gave rise to a strong collective movement during 2018–2019. Afterwards, the group pressure, due to the bubble of the initial coin offerings, decreased in favour of the largest cryptocurrencies. Lastly, we observed changes in the hierarchical order of the most influential cryptocurrencies. In particular, Ethereum became the most influential cryptocurrency, at the detriment of Bitcoin.     

Searching for safe-haven assets during the COVID-19 pandemic

The ongoing COVID-19 pandemic has shaken the global financial system and caused great turmoil. Facing unprecedented risks in the markets, people have increasing needs to find a safe haven for their investments. Given that the nature of this crisis is a combination of multiple problems, it is substantially different from all other financial crises known to us. It is therefore urgent to re-evaluate the safe-haven role of some traditional asset types, namely, gold, cryptocurrency, foreign exchange and commodities. This paper introduces a sequential monitoring procedure to detect changes in the left-quantiles of asset returns, and to assess whether a tail change in the equity index can be offset by introducing a safe-haven asset into a simple mean-variance portfolio. The sample studied covers a training period between August–December 2019 and a testing period of December 2019–March 2020. Furthermore, we calculate the cross-quantilogram between pair-wise asset returns and compare their directional predictability on left-quantiles in both normal market conditions and the COVID-19 period. The main results show that the role of safe haven becomes less effective for most of the assets considered in this paper, while gold and soybean commodity futures remain robust as safe-haven assets during this pandemic.     

A tale of two tails among carbon prices,green and non-green cryptocurrencies

This paper studies the tail dependence among carbon prices, green and non-green cryptocurrencies. Using daily closing prices of carbon, green and non-green cryptocurrencies from 2017 to 2021 and a quantile connectedness framework, we find evidence of asymmetric tail dependence among these markets, with stronger dependence during highly volatile periods. Moreover, carbon prices are largely disconnected from cryptocurrencies during periods of low volatilities, while Bitcoin and Ethereum exhibit time-varying spillovers to other markets. Our results also show that green cryptocurrencies are weakly connected to Bitcoin and Ethereum, and their net connectedness are close to 0, except during the COVID-19 pandemic. Finally, we find a significant influence of macroeconomic and financial factors on the tail dependence among carbon, green and non-green cryptocurrency markets. Our results highlight the time-varying diversification benefits across carbon, green and non-green cryptocurrencies and have important implications for investors and policymakers.     

Non-linear relationship between oil and cryptocurrencies: Evidence from returns and shocks

The price instabilities between oil prices and cryptocurrencies have motivated the current study to examine the nonlinear relationship between oil returns/shocks and cryptocurrencies during March 3, 2018 to October 10, 2021. We employed a novel methodology of cross-quantilogram to unveil the nonlinearity and asymmetry between oil shocks and cryptocurrencies. We find that when markets are normal and bullish, there is a positive correlation between oil returns and cryptocurrency returns at first lag; however, there is a negative correlation between oil returns and cryptocurrencies in all market conditions. Moreover, rising fluctuations in oil demand shocks brings significant movement in cryptocurrency returns in bearish market conditions and it is unlikely that oil demand shocks and cryptocurrencies returns move in same directions. Given these results, we proposed useful implications for policymakers, strategists, regulators, financial market participants, and investors to hedge/diversify their risk.     

Cryptocurrency returns under empirical asset pricing

This study examines the predictability of cryptocurrency returns based on investors' risk premia. Prior studies that have examined the predictability of cryptocurrencies using various economic risk factors have reported mixed results. Our out-of-sample evidence identifies the existence of a significant return predictability of cryptocurrencies based on the cryptocurrency market risk premium. Consistent with capital asset pricing theory (CAPM), our results show that investors often require higher positive returns before taking on any additional risks, particularly in terms of riskier assets like cryptocurrencies. Tests involving the CAPM model demonstrates that the three largest cryptocurrencies have significant exposures to the proposed market factor with insignificant intercepts, demonstrating that the market factor explains average cryptocurrency returns very well.     

Investor attention and cryptocurrency: Evidence from wavelet-based quantile Granger causality analysis

This paper investigates the relationship between investor attention and the major cryptocurrency markets by wavelet-based quantile Granger causality. The wavelet analysis illustrates the interdependence between investor attention and the cryptocurrency returns. Multi-scale quantile Granger causality based on wavelet decomposition further demonstrates bidirectional Granger causality between investor attention and the returns of Bitcoin, Ethereum, Ripple and Litecoin for all quantiles, except for the medium. Among them, the Granger causality from investor attention to the returns is relatively very weak for Ethereum. In the short term, the Granger causality from these cryptocurrency returns to investor attention seems symmetric, but in the medium- and long- term, the causality shows some asymmetry. The Granger causality from investor attention to these cryptocurrency returns is asymmetric and varies across cryptocurrencies and time scales. Specifically, investor attention has a relatively stronger impact on the cryptocurrency returns in bearish markets than that in bullish markets in the short term.     

Asymmetric volatility in the cryptocurrency market: New evidence from models with structural breaks

Previous literature shows that major cryptocurrencies exhibit inverse asymmetric volatility: positive shocks increase price volatility more than negative ones. In this study, we revisit the asymmetric volatility dynamics of major cryptocurrencies using asymmetric GARCH models that incorporate endogenously detected structural breaks. Our results show that after incorporating structural breaks, volatility persistence decreases and asymmetric volatility increases for all cryptocurrencies in this study. Thus, prior research that ignores structural breaks underestimates the impact of unexpected news on price volatility in cryptocurrency markets. We also present important economic implications of our results: ignoring structural breaks adversely affects the hedging strategies, derivatives valuations, and risk exposure measurement of investors in cryptocurrency markets.     

Nonlinear tail dependence in cryptocurrency-stock market returns: The role of Bitcoin futures

We investigate the median and tail dependence between cryptocurrency and stock market returns of BRICS and Developed countries using a newly developed nonparametric cumulative measure of dependence over the period January 4, 2016 – December 31, 2019 as well as before and after the introduction of Bitcoin futures on December 17, 2017. The new measure is model-free and permits measuring tail risk. The results highlight the leading role of S&P500, Nasdaq and DAX 30 in predicting BRICS and developed countries’ stock market returns. Among BRICS countries, BVSP shows a starring role in predicting stock market returns. BSE 30 is the most predictor of cryptocurrencies, which have a little predictability on stock market returns. Ethereum has the leading role in predicting cryptocurrencies and stock market returns followed by Bitcoin. Tail dependence shows substantial role of S&P500, Nasdaq and BVSP in predicting stock market returns. Subsample analysis show the role of Bitcoin futures in reshaping the mean and tail dependence between cryptocurrency and stock market returns. Our results have important policy implications for portfolio managers, hedge funds and investors.     

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.