An Analysis Of Blockchain Fundamentals, Technical, And Macroeconomic Factors On Bitcoin Price
(1) Universitas Pertiba
(2) Politeknik Manufaktur Negeri Bangka Belitung
(3) Biro Perekonomian dan Administrasi Pembangunan Setda Provinsi Kep. Bangka Belitung
(*) Corresponding Author
Abstract
Bitcoin has emerged as a prominent digital asset that blends financial innovation, technological advancement, and speculative behavior. However, its growing adoption raises sustainability concerns due to energy-intensive mining and environmental impacts. This study investigates the determinants of Bitcoin prices within the framework of sustainable digital finance by integrating blockchain fundamentals, technical indicators, and macroeconomic variables. Using daily data from 24 November 2021 to 21 November 2024 (753 observations), the analysis conducted with Stata 16—examines miners’ revenue, hashrate, transactions per block, unique addresses, mining difficulty, and trade volume as internal factors, along with gold prices, WTI crude oil, and the S&P 500 index as external factors. Results show that miners’ revenue, hashrate, and transactions per block have positive and significant effects on Bitcoin prices, emphasizing the importance of mining performance and network activity. Trade volume and unique addresses also display positive but less consistent influences, while mining difficulty remains statistically insignificant. Among external factors, WTI crude oil significantly affects Bitcoin prices. Overall, findings suggest that Bitcoin operates as both a financial asset and a technology-driven ecosystem shaped by blockchain dynamics and macroeconomic conditions. The study highlights the need for sustainable mining practices and transparent regulatory frameworks to enhance environmental efficiency.
Keywords
References
Alaminos, D., Salas-Compás, M. B., & Fernández-Gámez, M. (2024). Can Bitcoin trigger speculative pressures on the US Dollar? A novel ARIMA-EGARCH-Wavelet Neural Networks. Physica A: Statistical Mechanics and Its Applications, 654(October). https://doi.org/10.1016/j.physa.2024.130140
Aliyev, F., & Eylasov, N. (2025). The impact of Nasdaq-100 , U . S . Dollar Index and commodities on cryptocurrency : New evidence from Augmented ARDL approach. Economics Letters, 247(January), 112191. https://doi.org/10.1016/j.econlet.2025.112191
Aslanidis, N., Bariviera, A. F., & Perez-laborda, A. (2021). Are cryptocurrencies becoming more interconnected ? Economics Letters, 199, 109725. https://doi.org/10.1016/j.econlet.2021.109725
Bakas, D., Magkonis, G., & Young, E. (2022). What drives volatility in Bitcoin market ? Finance Research Letters, 50(August), 103237. https://doi.org/10.1016/j.frl.2022.103237
Bakhtiar, T., Luo, X., & Adelopo, I. (2023). The impact of fundamental factors and sentiments on the valuation of cryptocurrencies. Blockchain: Research and Applications, 4(4). https://doi.org/10.1016/j.bcra.2023.100154
Baur, D. G., Hong, K. H., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177–189. https://doi.org/10.1016/j.intfin.2017.12.004
Bouri, E., Gabauer, D., Gupta, R., & Tiwari, A. K. (2021). Volatility connectedness of major cryptocurrencies. Journal of Behavioral and Experimental Finance, 30, 100463. https://doi.org/10.1016/j.jbef.2021.100463
Canoz, I., & Dirican, C. (2017). the Cointegration Relationship Between Bitcoin Prices and Major World Stock Indices: an Analysis With Ardl Model Approach. Pressacademia, 4(4), 377–392. https://doi.org/10.17261/pressacademia.2017.748
Chaim, P., & Laurini, M. P. (2019). Is Bitcoin a bubble? Physica A: Statistical Mechanics and Its Applications, 517, 222–232. https://doi.org/10.1016/j.physa.2018.11.031
Diniz, R., Prince, D. de, & Maciel, L. (2022). Bubble detection in Bitcoin and Ethereum and its relationship with volatility regimes. Journal of Economic Studies, 2018. https://doi.org/10.1108/JES-09-2021-0452
Dubey, P. (2022). Short-run and long-run determinants of bitcoin returns: transnational evidence. Review of Behavioral Finance. https://doi.org/10.1108/RBF-02-2022-0040
Erfanian, S., Zhou, Y., Razzaq, A., Abbas, A., Safeer, A. A., & Li, T. (2022). Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach. Entropy, 24(10), 1–29. https://doi.org/10.3390/e24101487
Fousekis, P., & Grigoriadis, V. (2021). Directional predictability between returns and volume in cryptocurrencies markets. Studies in Economics and Finance, 38(4), 693–711. https://doi.org/10.1108/SEF-08-2020-0318
Gil-Alana, L. A., Abakah, E. J. A., & Rojo, M. F. R. (2020). Cryptocurrencies and stock market indices. Are they related? Research in International Business and Finance, 51(July 2019), 101063. https://doi.org/10.1016/j.ribaf.2019.101063
Hakim, R. (2020). Bitcoin pricing : impact of attractiveness variables. Financial Innovation, 6(21).
Hung, N. T. (2022). Asymmetric connectedness among S&P 500, crude oil, gold and Bitcoin. Managerial Finance, 48(4), 587–610. https://doi.org/10.1108/MF-08-2021-0355
Jia, Z., Tiwari, S., Zhou, J., Umar, M., & Fareed, Z. (2023). Asymmetric nexus between Bitcoin , gold resources and stock market returns : Novel findings from quantile estimates. Resources Policy, 81(June 2022), 103405. https://doi.org/10.1016/j.resourpol.2023.103405
Jiang, Y., Nie, H., & Ruan, W. (2018). Time-varying long-term memory in Bitcoin market. Finance Research Letters, 25, 280–284. https://doi.org/10.1016/j.frl.2017.12.009
Karpoff, J. M. (1987). The Relation Between Price Changes and Trading Volume : A Survey Author ( s ): Jonathan M . Karpoff Reviewed work ( s ): Source : The Journal of Financial and Quantitative Analysis , Vol . 22 , No . 1 ( Mar ., 1987 ), pp . Published by : University of Was. The Journal of Financial and Quantitative Analysis, 22(1), 109–126.
Kjærland, F., Khazal, A., Krogstad, E., Nordstrøm, F., & Oust, A. (2018). An Analysis of Bitcoin’s Price Dynamics. Journal of Risk and Financial Management, 11(4), 63. https://doi.org/10.3390/jrfm11040063
Kukacka, J., & Kristoufek, L. (2023). Fundamental and speculative components of the cryptocurrency pricing dynamics. Financial Innovation, 9(1). https://doi.org/10.1186/s40854-023-00465-7
Leirvik, T. (2022). Cryptocurrency returns and the volatility of liquidity. Finance Research Letters, 44(March), 102031. https://doi.org/10.1016/j.frl.2021.102031
Li, H., Zhong, W., & Park, S. Y. (2016). Generalized cross-spectral test for nonlinear Granger causality with applications to money-output and price-volume relations. Economic Modelling, 52, 661–671. https://doi.org/10.1016/j.econmod.2015.09.037
Li, Z., Li, J., & Zhou, K. (2023). Bitcoin transaction fees and the decentralization of Bitcoin mining pools. Finance Research Letters, 58(PB), 104347. https://doi.org/10.1016/j.frl.2023.104347
Lin, M., Liu, Y., Ng, V., & Sheng, K. (2025). Analysis of the impact of macroeconomic factors on cryptocurrency returns - Based on quantile regression study. International Review of Economics and Finance, 97(October 2024), 103757. https://doi.org/10.1016/j.iref.2024.103757
Momtaz, P. P. (2021). The Pricing and Performance of Cryptocurrency. European Journal of Finance, 27(4–5), 367–380. https://doi.org/10.1080/1351847X.2019.1647259
Park, S., & Yang, J. S. (2024). Machine learning models based on bubble analysis for Bitcoin market crash prediction. Engineering Applications of Artificial Intelligence, 135. https://doi.org/10.1016/j.engappai.2024.108857
Polyzos, E., & Youssef, L. (2025). Investigating the impact of global events on cryptocurrency performance : a big data event study approach ☆. Journal of International Money and Finance, 157(May), 103375. https://doi.org/10.1016/j.jimonfin.2025.103375
Sapuric, S., Kokkinaki, A., & Georgiou, I. (2020). The relationship between Bitcoin returns, volatility and volume: asymmetric GARCH modeling. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-10-2018-0228
Shen, D., Urquhart, A., & Wang, P. (2020). A three-factor pricing model for cryptocurrencies. Finance Research Letters, 34, 0–11. https://doi.org/10.1016/j.frl.2019.07.021
Sovbetov Y. (2018). Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero. Journal of Economics and Financial Analysis, 2(2), 1–27. https://doi.org/10.1991/jefa.v2i2.a16
Thampanya, N., Nasir, M. A., & Huynh, T. L. D. (2020). Asymmetric correlation and hedging effectiveness of gold & cryptocurrencies: From pre-industrial to the 4th industrial revolution✰. Technological Forecasting and Social Change, 159(April), 120195. https://doi.org/10.1016/j.techfore.2020.120195
Tiwaria, A. K., Adewuyi, A. O., Albulescu, C. T., & Wohar, M. E. (2020). Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies. North American Journal of Economics and Finance, 51(September 2019), 101083. https://doi.org/10.1016/j.najef.2019.101083
Todorova, N., & Souček, M. (2014). The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range. Economic Modelling, 36, 332–340. https://doi.org/10.1016/j.econmod.2013.10.003
Tsai, I. C. (2014). Ripple effect in house prices and trading volume in the UK housing market: New viewpoint and evidence. Economic Modelling, 40, 68–75. https://doi.org/10.1016/j.econmod.2014.03.026
Ünvan, Y. A. (2021). Impacts of Bitcoin on USA, Japan, China and Turkey stock market indexes: Causality analysis with value at risk method (VAR). Communications in Statistics - Theory and Methods, 50(7), 1599–1614. https://doi.org/10.1080/03610926.2019.1678644
Vo, A., Chapman, T. A., & Lee, Y. S. (2022). Examining Bitcoin and Economic Determinants: An Evolutionary Perspective. Journal of Computer Information Systems, 62(3), 572–586. https://doi.org/10.1080/08874417.2020.1865851
Yakubu, M., Asumadu, S., & Leirvik, T. (2023). Heliyon Mutual coupling between stock market and cryptocurrencies. Heliyon, 9(5), e16179. https://doi.org/10.1016/j.heliyon.2023.e16179
Yildirim, H., Akdag, S., & Alola, A. A. (2022). Is there a price bubble in the exchange rates of the developing countries? The case of BRICS and Turkey. Journal of Economics, Finance and Administrative Science. https://doi.org/10.1108/JEFAS-04-2021-0025
Zhang, Y., Zhou, L., Li, Y., & Liu, F. (2023). Higher-order moment nexus between the US Dollar, crude oil, gold, and bitcoin. North American Journal of Economics and Finance, 68(April), 101998. https://doi.org/10.1016/j.najef.2023.101998
Zhu, Y., Dickinson, D., & Li, J. (2017). Analysis on the influence factors of Bitcoin’s price based on VEC model. Financial Innovation, 3(1). https://doi.org/10.1186/s40854-017-0054-0
DOI: http://dx.doi.org/10.33019/ijbe.v10i2.1467
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