Abstract

Abstract Developments in digital technologies are considered to be the most important innovations since the advent of the internet. In several countries, this has led to a significant change in the way payments are made, leading to new forms of payment, such as crypto-currencies. With regard to cryptocurrencies, it remains a complex issue involving especially volatility, but also money laundering and consumer protection issues. While most countries consider cryptocurrencies too volatile to be used as a payment alternative, crypto-currencies gain interest of investors in the last 10 years due to the possibility of obtaining large profits. The aim of the paper is to study the volatility of the first 5 cryptocurrencies (Bitcoin, Ethereum, Binance Coin, Cardano and Ripple) through GARCH models. The process of evaluating highly volatile cryptocurrencies is complex and depends on many parameters. Therefore, our results would be particularly useful in terms of portfolio and risk management and could help them to be more agile in evaluating their investments, in making optimal decisions and making future forecasts. We find that the GARCH (1.1) models provide the best fit, in terms of modelling of the volatility in the most popular and largest cryptocurrencies. The results show that for BTC, ETH and XRP the appropriate model is GARCH (1.1) and in the case of BNC and CARDANO GARCH-M explain better the volatility of the crypto-currencies. Therefore, more in depth analysis of the datasets may be required to confirm or deny possible structural change. The study can be complemented by carrying out an event study on the 5 cryptocurrencies analyzed or extending the analysis by applying other GARCH models, to research the optimal model for several cryptocurrencies.

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