SYMMETRIC GARCH MODELING OF SOME CRYPTOCURRENCY RETURNS: IMPLICATIONS FOR COIN INVESTMENT DECISION-MAKING
DOI:
https://doi.org/10.33003/fjs-2026-1009-4760Keywords:
Digital Coin, GARCH Modeling, Mean Reversion, Fat-Tails, Short-and Long-Term Investments, NigeriaAbstract
The rapid growth of cryptocurrency markets has intensified interest in understanding the volatility dynamics of digital assets due to their implications for investment decision-making, risk management, and financial forecasting. Although numerous studies have examined cryptocurrency volatility using GARCH-type models, limited attention has been given to the comparative analysis of volatility mean reversion and half-life measures across multiple cryptocurrencies and their implications for investment horizons. This study addresses this gap by investigating the volatility behaviour, persistence, mean reversion, and volatility half-lives of eight major cryptocurrencies, namely Bitcoin (BTC), Dogecoin (DOGE), Ethereum (ETH), Litecoin (LTC), Tether (USDT), Stellar (XLM), Monero (XMR), and Ripple (XRP) using daily closing price data from January 2014 to August 2024. Descriptive statistics, unit root tests, ARCH effect tests, and symmetric GARCH (1,1) models were employed to estimate volatility persistence and compute volatility half-life measures. The results revealed that all cryptocurrency return series exhibited non-normal and leptokurtic distributions, significant ARCH effects, and strong volatility clustering. The estimated GARCH models indicated high volatility persistence across all cryptocurrencies, with persistence coefficients ranging from approximately 0.8706 for USDT to 0.99995 for BTC. The computed volatility half-lives varied substantially, ranging from 5 days for USDT and 12 days for ETH to 1,708 days for XRP and 13,864 days for BTC, indicating marked differences in the speed of adjustment to market shocks. Cryptocurrencies with shorter volatility half-lives, such as USDT and ETH, were found to be more suitable for short-term trading strategies, whereas BTC and XRP exhibited characteristics consistent with longer-term investment horizons.
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Copyright (c) 2026 David Adugh Kuhe, Amak Solomon Ayum, Tersoo Uba
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