Adverse selection in cryptocurrency markets

In this article we investigate the influence that information asymmetry may have on future volatility, liquidity, market toxicity, and returns within cryptocurrency markets. We use the adverse-selection component of the effective spread as a proxy for overall information asymmetry. Using order and trade data from the Bitfinex exchange, we first document statistically significant adverse-selection costs for major cryptocurrencies. Also, our results suggest that adverse-selection costs, on average, correspond to 10% of the estimated effective spread, indicating an economically significant impact of adverse-selection risk on transaction costs in cryptocurrency markets. Finally, we document that adverse-selection costs are important predictors of intraday volatility, liquidity, market toxicity, and returns.     

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.     

MAX momentum in cryptocurrency markets

This paper studies the MAX effect, the relationship between maximum daily returns and future returns in the cryptocurrency market. The cryptocurrency market is an ideal setting for the MAX effect due to its lottery-like features (i.e., large positive skewness). Contrary to findings in other markets, we demonstrate that cryptocurrencies with higher maximum daily returns tend to achieve higher returns in the future and call this the “MAX momentum” effect. We also find that the magnitude of the MAX momentum effect varies with market conditions, investor sentiment and the underpricing of cryptocurrencies. Additionally, this effect is robust to longer holding periods, different MAX measures and alternative sample selection criteria.     

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.     

Is idiosyncratic volatility priced in cryptocurrency markets?

This paper investigates how idiosyncratic volatility is priced in the cross-section of cryptocurrency returns. By conducting both portfolio-level analysis and Fama-MacBeth regression analysis, we demonstrate that idiosyncratic volatility is positively related to the expected returns of cryptocurrencies. This finding is not subsumed by effects of size, momentum, liquidity, volume, and price and is robust to different weighting schemes, holding periods, and sample sizes. Besides, we find no evidence of temporal relation between idiosyncratic volatility and returns in cryptocurrency 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.     

Conditional tail-risk in cryptocurrency markets

In this paper we use $CoVaR$ to estimate the conditional tail-risk in the markets for bitcoin, ether, ripple and litecoin and find that these cryptocurrencies are highly exposed to tail-risk within cryptomarkets, while they are not exposed to tail-risk with respect to other global assets, like the U.S. equity market or gold. Although cryptocurrency returns are highly correlated one with the other, we find that idiosyncratic risk can be significantly reduced and that portfolios of cryptocurrencies offer better risk-adjusted and conditional returns than individual cryptocurrencies. These results indicate that portfolios of cryptocurrencies could offer attractive returns and hedging properties when included in investors’ portfolios. However, when we account for liquidity, the share of crypto assets in investors’ optimal portfolio is small.     

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.     

Distrust or speculation? The socioeconomic drivers of U.S. cryptocurrency investments

Employing representative data from the U.S. Survey of Consumer Payment Choice, we find no evidence that cryptocurrency investors are motivated by distrust in fiat currencies or regulated finance. Compared with the general population, investors show no differences in their level of security concerns with either cash or commercial banking services. We find that cryptocurrency investors tend to be educated, young and digital natives. In recent years, a gap in ownership of cryptocurrencies across genders has emerged. We examine how investor characteristics vary across cryptocurrencies and show that owners of cryptocurrencies increasingly tend to hold their investment for longer periods.     

Can salience theory explain investor behaviour? Real-world evidence from the cryptocurrency market

Research on human attention indicates that objects that stand out from their surroundings, i.e., salient objects, attract the attention of our sensory channels and receive undue weighting in the decision-making process. In the financial realm, salience theory predicts that individuals will find assets with salient upsides (downsides) appealing (unappealing). We investigate whether this theory can explain investor behaviour in the cryptocurrency market. Consistent with the theory's predictions, using a sample of 1738 cryptocurrencies, we find that cryptocurrencies that are more (less) attractive to “salient thinkers” earn lower (higher) future returns, which indicates that they tend to be overpriced (underpriced). On average, a one cross-sectional standard-deviation increase in the salience theory value of a cryptocurrency reduces its next-week return by 0.41%. However, the salience effect is confined to the micro-cap segment of the market, and its size is moderated by limits to arbitrage.     

Up or down? Short-term reversal,momentum, and liquidity effects in cryptocurrency markets

We demonstrate a new powerful predictive signal for cryptocurrency returns: the last day's return. Based on daily prices of more than 3600 coins, we document that the cryptocurrencies with low last day's return significantly outperform their counterparts with high last day's return. The effect is confirmed by a battery of cross-sectional tests and portfolio sorts, and is not subsumed by a broad range of other return predictors. We argue that the daily reversals result from the illiquidity of the vast majority of traded cryptocurrencies. In consequence, the pattern is cross-sectionally dependent on liquidity, and the handful of largest and most tradeable coins exhibit daily momentum rather than a reversal. Our findings help to reconcile earlier conflicting evidence on return persistence in cryptocurrency markets.     

Investor attention in cryptocurrency markets

We examine the relationship between investor attention, and measures of uncertainty, with the market dynamics of Bitcoin and other cryptocurrencies. We find that increases in investor attention are associated with higher returns, more volatility, and greater illiquidity in cryptocurrency markets. In contrast, cryptocurrency uncertainty (UCRY) and financial market uncertainty (VIX) are also positively related to volatility and illiquidity but have a negative contemporaneous relationship with returns. The identified relationships are accentuated during the COVID-pandemic, and are robust to different measures of investor attention, volatility, and illiquidity. Our results suggest that monitoring investor attention could assist both investors and policymakers.     

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.     

Cryptocurrencies and stock market indices. Are they related?

In this paper, we investigate the stochastic properties of six major cryptocurrencies and their bilateral linkages with six stock market indices using fractional integration techniques. From the univariate analysis, we observe that for Bitcoin and Ethereum, the unit root null hypothesis cannot be rejected; for Litecoin, Ripple and Stellar, the order of integration is found to be significantly higher than 1; for Tether, however, we find evidence in favour of mean reversion. For the stock market indices, the results are more homogeneous and the unit root cannot be rejected in any of the series, with the exception of VIX where mean reversion is obtained. Concerning bivariate results within the cryptocurrencies and testing for cointegration, we provide evidence of no cointegration between the six cryptocurrencies. Along the same lines, testing for cointegration between the cryptocurrencies and the stock market indices, we find evidence of no cointegration, which implies that the cryptocurrencies are decoupled from the mainstream financial and economic assets. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class.     

Reprint of: Market liquidity in the financial crisis: The role of liquidity commonality and flight-to-quality

We examine the dynamics and the drivers of market liquidity during the financial crisis, using a unique volume-weighted spread measure. According to the literature we find that market liquidity is impaired when stock markets decline, implying a positive relation between market and liquidity risk. Moreover, this relationship is the stronger the deeper one digs into the order book. Even more interestingly, this paper sheds further light on so far puzzling features of market liquidity: liquidity commonality and flight-to-quality. We show that liquidity commonality varies over time, increases during market downturns, peaks at major crisis events and becomes weaker the deeper we look into the limit order book. Consistent with recent theoretical models that argue for a spiral effect between the financial sector’s funding liquidity and an asset’s market liquidity, we find that funding liquidity tightness induces an increase in liquidity commonality which then leads to market-wide liquidity dry-ups. Therefore our findings corroborate the view that market liquidity can be a driving force for financial contagion. Finally, we show that there is a positive relationship between credit risk and liquidity risk, i.e., there is a spread between liquidity costs of high and low credit quality stocks, and that in times of increased market uncertainty the impact of credit risk on liquidity risk intensifies. This corroborates the existence of a flight-to-quality or flight-to-liquidity phenomenon also on the stock markets.     

“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.     

The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?

The role of the carbon market in relation to the cryptocurrency market is still unclear. Given the carbon-intensive nature of the cryptocurrency industry, whether the carbon market is able to capture the carbon footprint of the cryptocurrency market (i.e., diversification) or act as a safe haven or a hedge against it remain unexplored issues. To address this issue, this paper employs the generalized autoregressive score-dynamic conditional score-Copula (GAS–DCS–Copula) model, incorporating the asymmetric tail distribution. We identify the asymmetric tail properties of both the carbon and cryptocurrency markets with significant otherness. Further, to account the importance of China in mining the cryptocurrencies, we incorporate Chinese carbon market in our analysis to investigate the difference with the European carbon market. Finally, we provide evidence that the European carbon market provides a safe haven and a hedge against the cryptocurrency market while Chinese carbon market is not. Our findings have implications for both investors and policymakers.     

What Style Liquidity Timing Skills Do Mutual Fund Managers Possess?

Recent studies claim that mutual fund managers demonstrate strong MARKET liquidity timing skills. We extend their liquidity timing tests to the four‐factor case and investigate liquidity timing skills with respect to the MARKET, SIZE, VALUE and MOMENTUM factors. Contrary to these claims, we find no evidence that fund managers adjust market exposure in anticipation of market liquidity changes. We find rather strong evidence that fund managers successfully overweight small stocks as market liquidity increases. Our study also demonstrates that it is easy to misidentify SIZE liquidity timing as MARKET liquidity timing in models that focus only on MARKET liquidity timing.     

Dependence and risk spillovers among clean cryptocurrencies prices and media environmental attention

This paper examines the relationships among cryptocurrency environmental attention and clean cryptocurrencies prices using Time-Varying Parameter Vector Auto-Regression (TVP-VAR) and wavelets techniques. Results show strong connectedness among these variables, implying that the prices of clean cryptocurrencies are influenced by attention on cryptocurrency sustainability. Connectedness is stronger with positive shocks on environmental attention than negative shocks. Also, in the short-term, clean cryptocurrencies prices lead environmental attention, especially after 2021. However, there are notable periods when environmental attention led clean cryptocurrency prices before 2021. In the long-term, clean cryptocurrencies such as Hedera, Polygon, Cosmos, IOTA, TRON, Stellar, Tezos and Ripple lead environmental attention. In the presence of bitcoin, the degrees of connectedness increased across both shocks on cryptocurrency environmental attention. In all cases, the bitcoin market is the main destination of shocks from the system. We highlight some crucial implications of these results.     

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.