ANALISIS LIKUIDITAS DAN VOLUME TRANSAKSI TERHADAP VOLATILITAS PADA DOGECOIN DENGAN MODEL GARCH

This study aims to analyze the effect of liquidity and trading volume on Dogecoin price volatility using the GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model. Dogecoin was selected as the research object due to its high price fluctuations in the cryptocurrency market. The study employs daily secondary data from January to March 2023, consisting of liquidity, trading volume, and price volatility variables. The analysis was conducted using multiple linear regression and the GARCH model to capture the dynamic patterns of volatility. The results reveal that liquidity significantly affects Dogecoin price volatility, while trading volume has no significant effect. The ARIMA(1,1,0)–GARCH(1,1) model was identified as the most suitable model since it recorded the lowest AIC and SIC values and passed the heteroskedasticity test. These findings indicate that Dogecoin’s volatility is not random but influenced by past volatility, suggesting the presence of a volatility clustering phenomenon. This study provides empirical evidence on the determinants of cryptocurrency volatility and offers insights for investors and academics in understanding market efficiency and managing risk in digital asset markets.