# Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19

arXiv: https://arxiv.org/abs/2101.00576 · HTML: https://mlsanity.com/paper/2101.00576/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 80 references that are in the map.
- First posted on arXiv 3 Jan 2021.

## Builds on (most cited first, 8 of 8)

- [A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data](https://mlsanity.com/paper/1306.4933/) (2013)
- [Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil](https://mlsanity.com/paper/2007.12261/) (2020)
- [Do the rich get richer? An empirical analysis of the BitCoin transaction network](https://mlsanity.com/paper/1308.3892/) (2013)
- [Novel semi-metrics for multivariate change point analysis and anomaly detection](https://mlsanity.com/paper/1911.00995/) (2019)
- [Multiscale characteristics of the emerging global cryptocurrency market](https://mlsanity.com/paper/2010.15403/) (2020)
- [Bitcoin market route to maturity? Evidence from return fluctuations, temporal correlations and multiscaling effects](https://mlsanity.com/paper/1804.05916/) (2018)
- [Detecting correlations and triangular arbitrage opportunities in the Forex by means of multifractal detrended cross-correlations analysis](https://mlsanity.com/paper/1906.07491/) (2019)
- [Competition of noise and collectivity in global cryptocurrency trading: route to a self-contained market](https://mlsanity.com/paper/1911.08944/) (2019)

## Abstract (arXiv)

This paper uses new and recently introduced methodologies to study the similarity in the dynamics and behaviours of cryptocurrencies and equities surrounding the COVID-19 pandemic. We study two collections; 45 cryptocurrencies and 72 equities, both independently and in conjunction. First, we examine the evolution of cryptocurrency and equity market dynamics, with a particular focus on their change during the COVID-19 pandemic. We demonstrate markedly more similar dynamics during times of crisis. Next, we apply recently introduced methods to contrast trajectories, erratic behaviours, and extreme values among the two multivariate time series. Finally, we introduce a new framework for determining the persistence of market anomalies over time. Surprisingly, we find that although cryptocurrencies exhibit stronger collective dynamics and correlation in all market conditions, equities behave more similarly in their trajectories, extremes, and show greater persistence in anomalies over time.