A Survey on Efficiency and Profitable Trading Opportunities in the Cryptocurrency Markets: An Approach in the Context of the War of 2022

Abstract

In this paper, we analyse the long memory process in the cryp­tocurrencies Bitcoin (BTC), Cardano (ADA), Binance Coin (BNB), Dogecoin (DOGE), Ethereum (ETH) and Ripple (XRP) from January 1st, 2018, to No­vember 10th, 2022, which includes the 2020 and 2022 events. The results demonstrate that the daily returns are leptokurtic, and the distributions are non-Gaussian. We also observe non-linearity, implying autocorrelation or conditional heteroscedasticity in digital currencies. The DFA exponents re­veal that throughout the Tranquil period, digital currencies with current val­ues higher than 0.5 exhibited long memory in their returns. The BNB digital currency has an exponent of 0.5, indicating that the series were unpredicta­ble throughout this period. As can be shown, all cryptocurrencies offer val­ues of the DFA exponent greater than 0.5 in the Stress subperiod, implying that the higher the DFA exponent and closer to 1, the higher the persistence, as well as the autocorrelation between observations and stronger predictive ability. The findings support the evidence examined by the BDS test, name­ly that price movements are not i.i.d. (independent and identically distribut­ed) and that investors have a high possibility of achieving above-average returns through arbitrage.