Cryptocurrencies and stock market indices. Are they related?

Abstract

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.

A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets

“…On the other hand, financial markets worldwide have been severely affected by the global pandemic of Covid-19 ( Al-Awadi et al, 2020 , Ali et al, 2020 , Godel, 2020 , Haroon and Rizvi, 2020 , Iqbal et al, 2020 , Sharif et al, 2020 , Zhang et al, 2020 ). In particular, the Covid-19 crisis has negatively impacted the potential role of cryptocurrencies as diversifying investments ( Liu, 2019 , Tiwari et al, 2019 , Conlon and McGee, 2020 , Gil-Alana et al, 2020 ). Hence, the study of the fiat currencies and cryptocurrencies dynamics through the Covid-19 bear market and initial recovery from it provides a unique way to investigate the economic impact of the pandemic in the important domain of the financial system and its stability as a whole.…”

Cryptocurrencies and Artificial Intelligence: Challenges and Opportunities

“…Different regression models and statistical models have been tested by researchers to fit this linear model in different ways [11], [12], [15], [17]- [19]. Simple linear time series models sometimes leave certain aspects of economic and financial data unexplained [29].…”

“…Logistic regression (LR) was compared to autoregressive integrated moving average (ARIMA) for Bitcoin Price prediction in [18] and its other variants in [19]. OLS regression and fractionally integrated ARMA (ARFIMA) were used in [19] to investigate the stochastic properties of the top six largest cryptocurrencies at that time (Bitcoin, Ethereum, Ripple, Litecoin, Stellar and Tether) and their relationship to six stock market indices.…”

“…Price prediction models are away from perfect prediction due to the speculation involved in trading and the complexities involved in the market that affect the trading decisions but as it is well known all models are wrong, but some are useful. Other studies [11], [12], [15], [19], [21], [23]- [25], [28] used different evaluation metrics so they were not included in the figures.…”

“…Price prediction [11], [13], [15], [18], [20], [21], [24]- [26] [12], [16], [17], [19], [22], [23], [28] Volatility prediction [38], [39] [35]- [37], [40] Automated trading [9], [42], [44]- [46], [48], [49] [23] Fraud detection [50]- [52], [54] [53] Mining [68], [71] [69], [70] Security [72], [76], [77], [82] [70], [81] Anonymity and privacy [54], [60]- [63], [65]- [67] None…”