Cryptocurrencies are known for their volatile price movements and periodic bubbles. Their prices often drop sharply during market crashes before rebounding quickly afterwards.
By applying clustering algorithms on log return data, we have classified cryptocurrencies into five groups. Cluster 1 represents those cryptocurrencies with relatively homogeneous distributions with moderate central tendencies and skewness but heavy tails (high kurtosis). Meanwhile, other groups tend to have different properties.
Volume
The cryptocurrency market is marked by high volatility and an uncertain understanding of its economic foundations, leading to increasingly volatile prices and significant speculation. Such conditions could contribute to crypto-market contagion and risk transmission which in turn become threats to market stability (Gubareva et al. 2022).
We investigate the interaction of five main cryptocurrencies and three uncertainty indices from gold, oil, and equity markets using an innovative combination of cross-quantilogram and quantile connectedness analysis methods to assess tail dependence and network connectivity between them.
Results suggest that, with the exception of XRP, all cryptocurrencies are net pairwise transmitters of system shocks in the lower quantile, and transmit those shocks directly to volatility indices as a consequence. As a result, they amplify flight-to-quality and flight-to-safety events, potentially endangering financial stability. Higher quantiles reveal more complex interactions that feature stronger right-tail dependence and increased cojumps which suggest cryptocurrencies are more sensitive to unexpected bad shocks than expected good ones.
Price
The crypto market has evolved from its early stage characterized by low capitalization, limited liquidity, price fluctuations that lasted a short time frame (short-term memory), frequent arbitrage opportunities and weak complexity to its mature form characterized by medium capitalization, improved liquidity with inverse power-law fluctuations that long term memory stores and sparse arbitrage opportunities with increasing complexity. Multifractal properties provide key insight into this process of maturation.
This study examines the time-varying dynamics of quantile connectedness and tail spillover between five cryptocurrencies (BTC, ETH, LTC and BCH) and three CBOE volatility indices (VIX, OVX and GVZ). Cross-quantilograms allow us to visualize pairwise net directional spillover as well as connective network interaction, in addition to its effect on COVID-19 pandemic effects.
Confirmation
Cryptocurrencies are highly volatile and speculative assets with the potential to exacerbate flight-to-quality and flight-to-safety events, posing a threat to financial stability. Their volatility is also associated with higher volatility across conventional markets; therefore, this paper investigates these cross-market effects by tracking comovement between cryptocurrency asset classes and conventional security asset classes.
We construct a cryptocurrency market index by examining the exchange rates X/USDT of eight major cryptocurrencies: BTC, ETH, XRP, LTC, ADA, BCPT, ONT THETA THETA and LOOM which comprise 88% of market capitalization. We observe their progression over time and examine logarithmic returns.
Our results reveal that cryptocurrencies exhibit high comovement with fiat currencies and US stock markets, but low correlation with gold, oil, and equity markets. They exhibit negative correlations with these markets while showing an intriguing pattern of inter-market cross-correlations over time depending on q and s; minimal spanning trees using detrended correlation coefficient r(q,s) are used to visualize these patterns in Figure 12 Panel A as we see that all cryptocurrencies act as net pairwise transmitters of shocks to XRP and volatility indices when in this position
Forecast
Crypto markets are experiencing an upswing thanks to Bitcoin’s price surge; however, this recovery may not last for too long due to recent US stock market bloodbath and negative comments from SEC officials. This uncertainty inducing climate is creating chaos within markets like crypto.
Ripple Labs may use Ripple tokens available for investors or decrease its escrow account amount to further drive up XRP’s price and draw newcomers into crypto markets. Such action would help spur trading activity while simultaneously drawing in new investors to join this global cryptocurrency marketplace.
XRP prices are predicted to hit $1 by 2024 and even reach $0.7 by September. This projection is based on XRP’s issuance being reduced by half after its next halving event in May 2020 – increasing demand for it and thus driving its price higher, and making XRP less volatile than other cryptos.
