Coverage of the Coronavirus Pandemic through Entropy Measures

Abstract

The rapidly evolving coronavirus pandemic brings a devastating effect on the entire world and its economy as awhole. Further instability related to COVID-19will negatively affect not only on companies and financial markets, but also on traders and investors that have been interested in saving their investment, minimizing risks, and making decisions such as how to manage their resources, how much to consume and save, when to buy or sell stocks, etc., and these decisions depend on the expectation of when to expect next critical change. Trying to help people in their subsequent decisions, we demonstrate the possibility of constructing indicators of critical and crash phenomena on the example of Bitcoin market crashes for further demonstration of their efficiency on the crash that is related to the coronavirus pandemic. For this purpose, the methods of the theory of complex systems have been used. Since the theory of complex systems has quite an extensive toolkit for exploring the nonlinear complex system, we take a look at the application of the concept of entropy in finance and use this concept to construct 6 effective entropy measures: Shannon entropy, Approximate entropy, Permutation entropy, and 3 Recurrence based entropies. We provide computational results that prove that these indicators could have been used to identify the beginning of the crash and predict the future course of events associated with the current pandemic.

Machine learning for prediction of emergent economy dynamics

“…xvii This article highlights further research by the authors, begun in [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33]. The focus of the article "Irreversibility of financial time series: a case of crisis" [34] by Andrii O. Bielinskyi, Serhii V. Hushko (figure 5), Andriy V. Matviychuk, Oleksandr A. Serdyuk, Serhiy O. Semerikov and Vladimir N. Soloviev to measure the varying irreversibility of stock markets.…”

Econophysics of cryptocurrency crashes: a systematic review

“…Kristoufek [75], Li and Wang [76] consider that measures of financial and macroeconomic activity can be drivers of Bitcoin returns. Reviewing papers of the researches above, the experience of others and our own [77,78,79,80,81,82,83,84,85,86], we have revised our classification of such leaps and falls, relying on Bitcoin time series during the entire period (01.01.2011-21.01.2021) of verifiable fixed daily values of the Bitcoin price (BTC) (https://finance.yahoo.com/cryptocurrencies). We emphasize that • crashes are short and time-localized drops that last approximately two weeks, with the weighty losing of price each day.…”

Strengthening of e-learning at the leading Ukrainian pedagogical universities in the time of COVID-19 pandemic

“…Unfortunately, Ukraine is dealing with worse scenario of COVID-19 spreading than other European countries and takes 47-th place in the world due to new cases of COVID-19 per 100,000 people ( [40]). The consequences of a pandemic include not only negative impact on physical health, but also mental health disorders [37], disturbance of economy [3,30,32] and some dimensions of education system [6,36]. Almost 120 countries have stopped face-to-face learning and shifted to e-learning [22,26].…”