The Impact of the COVID-19 Pandemic on the Unpredictable Dynamics of the Cryptocurrency Market

Abstract

The global economy is under great shock again in 2020 due to the COVID-19 pandemic; it has not been long since the global financial crisis in 2008. Therefore, we investigate the evolution of the complexity of the cryptocurrency market and analyze the characteristics from the past bull market in 2017 to the present the COVID-19 pandemic. To confirm the evolutionary complexity of the cryptocurrency market, three general complexity analyses based on nonlinear measures were used: approximate entropy (ApEn), sample entropy (SampEn), and Lempel-Ziv complexity (LZ). We analyzed the market complexity/unpredictability for 43 cryptocurrency prices that have been trading until recently. In addition, three non-parametric tests suitable for non-normal distribution comparison were used to cross-check quantitatively. Finally, using the sliding time window analysis, we observed the change in the complexity of the cryptocurrency market according to events such as the COVID-19 pandemic and vaccination. This study is the first to confirm the complexity/unpredictability of the cryptocurrency market from the bull market to the COVID-19 pandemic outbreak. We find that ApEn, SampEn, and LZ complexity metrics of all markets could not generalize the COVID-19 effect of the complexity due to different patterns. However, market unpredictability is increasing by the ongoing health crisis.

Regularity in Stock Market Indices within Turbulence Periods: The Sample Entropy Approach

“…In light of the recently growing literature, a fairly broad research field regards assessing informational efficiency and predictability of financial markets with various entropy-based methods (e.g., [ 8 , 21 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]).…”

“…Wang and Wang [ 45 ] employ a multi-scale entropy-based method to analyse efficiency of various financial time series during the COVID-19 pandemic. Kim and Lee [ 21 ] use the approximate entropy, the sample entropy, and the Lempel-Ziv measure for the complexity of a time sequence to investigate predictability in cryptocurrency markets during the pandemic period. However, studies that deeply explore wide groups of stock markets in the context of their regularity and predictability are scarce.…”

“…The SampEn algorithm solves the self-matching problem and eliminates the ApEn bias. The SampEn was initially used in physiological time series analyses, but it is also a suitable indicator for economic and financial data sets (e.g., [ 21 , 22 ]). Both ApEn and SampEn statistics are model-independent measures of sequential regularity in experimental or empirical data series.…”

Relationship between eHealth, Perceived Risk, and Phobia of COVID-19 among Chinese University Students in Korea and China

“…As the COVID-19 pandemic ebbs and fows, people's psychological experiences are also recurring, resulting in a series of problems such as stress, fear, and phobia [1][2][3][4]. Previous studies have pointed out that the psychological burden of fear and phobia of COVID-19 varies by country, and the health and wellbeing of vulnerable groups must be prioritized [5][6][7]. University students are well-educated, socially engaged, and highly active young adults.…”

Observing Cryptocurrencies through Robust Anomaly Scores

“…Even though investments in cryptocurrencies were initially viewed as risky bets, increased participation by individuals as well as institutions have been transforming those views, as the cryptocurrency market is now perceived as a new asset class for many investors. With these revolutions, there have been numerous studies with the overall objective of understanding the cryptocurrency market [ 1 , 2 , 3 ] or, more specifically, cryptocurrencies as investment assets. Much effort has been put into analyzing diversification effects and evaluating cryptocurrencies as an asset class [ 4 , 5 , 6 , 7 , 8 ].…”