The cryptocurrency market is a new type of financial asset digitally created, gaining the attention of the academic community. These currencies are extremely volatile in comparison to conventional financial assets (Kumar & Anandarao, 2019). The volatility in these currency types is affected by a number of factors, including (1) perceptions of the value and worth of these kinds of investments, (2) uncertainness about their future, (3) the tax system, (4) investors’ expectations and (5) uncertainties regarding regulation (Vasek as well as Moore 2015).
The literature on cryptocurrency examines (1) the efficiency of markets of cryptocurrency Vidal-Tomas and Co. 2019), (2) comparisons of conventional assets with cryptocurrencies Pal and Mitra (2019), (3) the effect of macroeconomics on cryptocurrency Al-Khazali and co. (2018)), (4) portfolio diversification using cryptocurrencies (Akhtaruzzaman et al., 2020), and (5) the dynamics of the systemic risk sharing between cryptocurrencies (Akhtaruzzaman and colleagues. 2022). The study of the impact of volatility spillover on cryptocurrency has received much attention (Kumar & Anandarao, 2019). Geuder et al. (2019) examined the behavior of bubbles in Bitcoin Prices. They concluded that bubble behavior is a frequent and regular aspect that is characteristic of Bitcoin prices.
The research on the volatility of cryptocurrency has primarily focused on the volatility of Bitcoin prices when paired with different currencies (Pichl & Kaizoji, 2017) Interdependencies between cryptocurrency (Corbet et al. in 2018) well as co-movements that affect the volatility of cryptocurrency (Katsiampa and co.. in 2019,) as well as spillovers from volatility to the energy sector (Afjal & Clanganthuruthil, 2022) including foreign exchange, gold markets (Elsayed and al.. 2022). According to the findings of Kinateder and Papavassiliou’s (2021) study, evidence is absent for a Halloween-related calendar anomaly with respect to Bitcoin prices. However, there is a significant volatility observed at the beginning of each week, confirming the existence of the reverse effect of January. Previous studies have identified the effects of market uncertainty on return volatility in cryptocurrency as well as other assets (Wang & Co., 2019).
However, research on the relationship between return connections to cryptocurrency as well as volatility dynamics is not as extensive. The interrelations between the returns of cryptocurrency along with volatility spillovers and the formation of volatility clusters under extremely uncertain global conditions, including pandemics or war as well as pandemics, have not been adequately studied. The effects of the COVID-19 Coronavirus Disease 2019 (COVID-19) pandemic, a hazy incident, led to a dramatic increase in the price of various cryptocurrencies, resulting in a bubble-like behavior as well as volatility spillover (Ozdemir, 2022). After the outbreak of the Russo-Ukrainian War, crypto valuation fell from US$3 trillion in November 2021 and sank to 7.7 billion by June 2022. It could be due to a change in the investment climate, with huge selling by investors owing to increased inflation fears triggered by the Russo-Ukrainian War and herding behavior on the crypto market (Khalfaoui and others. 2022).
This research examines the effect uncertainty has on the dynamic of return connectedness and the volatility spillover networks across 20 distinct cryptocurrencies covering the time before COVID-19 and during COVID-19, along with the Russo-Ukrainian War. We study return connectedness and volatility spillover across cryptocurrencies using VARNI, the Volume Adjusted Return Network Index (VARNI), employing the Student-t Copula method and VAVNI, the Volume Adjusted Volatility Network Index (VAVNI) by using the DCC MGARCH method. We study the indexes (VARNI as well as VAVNI) on the basis of two specific events that are characterized by uncertainty, such as the COVID-19 crisis (prior as well as post) and the Russo-Ukrainian War. In the final analysis, we examine the effect of uncertainty indices (EPU Index) on the return connectedness as well as the impact of volatility on the cryptocurrency.
We have found that cryptocurrency return connectedness and the volatility spillover networks are dispersed prior to and concentrated in the COVID-19 era and extremely focused on the Russo-Ukrainian War. EPU Index The EPU Index influences the volatility spillover between cryptocurrencies but not the return connectedness.
The research into the study of spillovers in volatility across a wide range of cryptocurrencies through Network analysis represents the primary contribution this article makes to the research. The method used to construct VARNI and VAVNI indexes, which could be applied to all financial assets, is an additional contribution to the field of empirical finance. Our results offer new insight into the return spread among cryptocurrency around the world’s war-related uncertainty.
The rest portion of the article is arranged in the following manner. Section 2. examines the methodological approach used to come up with the different network structures and indices. Section 2 also discusses the network dynamics and the influence of the global mood on returns to cryptocurrency. Section 3 focuses on the information sources as well as the time period of study. Section 4 discusses the results, and Section 5 closes the study.
Section Snippets
Methodology
This research identifies the return connectedness and the volatility spillover connections through the network structure and also develops network indexes. These indices of networks are used to analyze the dynamics of networks as well as the effect of global market sentiment on cryptocurrency indexes.
The study’s data and period
The list includes the top 20 cryptocurrencies in terms of market capitalization. They cover more than 80 percent of the crypto market (Table A.1). The data spans between 2018 Q1 and 2022 Q2. The data is a representation of the pre-COVID-19 crises from 2018 Q1 until 2019 Q4, the COVID-19 crisis that ran from 2020 Q1 until 2021 Q4, and the continuing Russo-Ukrainian War covering 2022 Q1 and 2022 Q2, which can help to evaluate the impact of economic and financial uncertainty.