Analyze the Factors that Affect the Price of the Cryptocurrency Using the Error Correction Model
DOI:
https://doi.org/10.55324/josr.v5i11.3518Keywords:
Litecoin, Litecoin Price, Blockchain, Error Correction ModelAbstract
Cryptocurrency price volatility underscores the importance of understanding the factors associated with digital asset valuations across different time horizons. This study examined the short- and long-run relationships between Litecoin prices and circulating supply, transaction counts, transaction fees, the number of Blockchain.com wallet users, and gold prices. A quantitative research approach was employed using 537 weekly observations covering the period from January 4, 2016, to April 10, 2026. The variables were transformed into natural logarithms and analyzed using the Engle–Granger error correction modeling (ECM) approach in EViews 12, supported by unit root, cointegration, and model diagnostic tests. The results revealed statistically significant positive relationships between transaction counts, transaction fees, and Litecoin prices in both the short and long run. The number of Blockchain.com wallet users and gold prices exhibited statistically significant positive relationships with Litecoin prices only in the long run, whereas circulating supply showed no statistically significant relationship in either period. The negative and statistically significant error correction coefficient indicated that approximately 10.36% of the deviation from long-run equilibrium was corrected each week. The adjusted coefficients of determination (adjusted R²) were 94.81% for the long-run model and 17.06% for the short-run model, indicating substantially greater explanatory power in the long-run specification. These findings suggested that blockchain network activity and broader cryptocurrency adoption indicators were associated with Litecoin's long-run valuation, while a considerable proportion of short-run price variation remained unexplained by the model. The study concluded that the determinants of Litecoin prices exhibited distinct short- and long-run relationships, highlighting the importance of considering blockchain network indicators, broader market conditions, and risk management strategies when evaluating cryptocurrency investments rather than relying on individual predictors.
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Copyright (c) 2026 I Wayan Darma Yasa
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