Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litecoin, and Monero

ArXiv ID: 2511.22782 “View on arXiv”

Authors: Yhlas Sovbetov

Abstract

This paper examines factors that influence prices of most common five cryptocurrencies such as Bitcoin, Ethereum, Dash, Litecoin, and Monero over 2010-2018 using weekly data. The study employs ARDL technique and documents several findings. First, cryptomarket-related factors such as market beta, trading volume, and volatility appear to be significant determinant for all five cryptocurrencies both in short- and long-run. Second, attractiveness of cryptocurrencies also matters in terms of their price determination, but only in long-run. This indicates that formation (recognition) of the attractiveness of cryptocurrencies are subjected to time factor. In other words, it travels slowly within the market. Third, SP500 index seems to have weak positive long-run impact on Bitcoin, Ethereum, and Litcoin, while its sign turns to negative losing significance in short-run, except Bitcoin that generates an estimate of -0.20 at 10% significance level. Lastly, error-correction models for Bitcoin, Etherem, Dash, Litcoin, and Monero show that cointegrated series cannot drift too far apart, and converge to a long-run equilibrium at a speed of 23.68%, 12.76%, 10.20%, 22.91%, and 14.27% respectively.

Keywords: Cryptocurrencies, ARDL, Market Factors, Cointegration, Cryptocurrency

Complexity vs Empirical Score

• Math Complexity: 4.5/10
• Empirical Rigor: 7.0/10
• Quadrant: Street Traders
• Why: The paper uses standard econometric techniques (ARDL, cointegration, error-correction models) that are well-established but not particularly advanced, placing math complexity in the moderate range. However, it demonstrates strong empirical rigor through weekly data analysis, construction of a custom index, and application of formal statistical models to real cryptocurrency data from 2010-2018.

  flowchart TD
    A["Research Goal:<br>Identify factors influencing prices of 5 major cryptocurrencies"] --> B["Data & Inputs<br>Weekly data (2010-2018)<br>5 Cryptos: BTC, ETH, DASH, LTC, XMR"]
    B --> C["Methodology<br>ARDL Bounds Test &<br>Error Correction Model"]
    C --> D["Computational Process<br>Estimate short-run & long-run<br>coefficients; Test for cointegration"]
    D --> E["Key Findings / Outcomes"]
    E --> E1["Market Factors (Beta, Volume, Volatility)<br>Significant in Short & Long run"]
    E --> E2["Attractiveness<br>Significant only in Long run"]
    E --> E3["S&P 500 Index<br>Weak positive long-run impact (BTC, ETH, LTC)"]
    E --> E4["Error Correction Speeds<br>BTC: 23.68%, ETH: 12.76%,<br>DASH: 10.20%, LTC: 22.91%, XMR: 14.27%"]