PENGARUH VOLUME PERDAGANGAN DAN PENGEMBALIAN TERHADAP VOLATILITAS HARGA TOKEN NEAR DENGAN MODEL GARCH

This study aims to analyze the effect of trading volume and returns on the volatility of the NEAR token price using the GARCH model, which is known to solve heteroscedasticity problems in time series data. The data used in this study are daily data from the closing price, trading volume and returns of NEAR for the period September to November 2024. The data were analyzed using Eviews 12 software. After the Stationarity Test and the best model estimation, the model chosen as the best model for volatility analysis is ARIMA (1,1,0)-GARCH (1,1). The results of the study also show that trading volume has a positive and significant effect on NEAR price volatility. While returns do not affect NEAR price volatility.