Does Commodity Prices Drive Bitcoin Price?

Hartiny Pop Koapaha

Abstract


This study investigates the relationship between Bitcoin prices and commodity prices, including oil, gold, silver, and copper, using a neural network approach. On a sample of 2,805 observations, 1,952 (69.6%) were used for training, 853 (30.4%) for testing, and the entire sample was used for validation. Neural networks are ideally adapted for this type of analysis due to their ability to model non-linear relationships between variables and to process large datasets. The results of the analysis indicate that the relative relevance of each commodity in predicting Bitcoin prices varies. Copper was determined to be the most significant commodity, followed by oil, silver, and gold. These results may be beneficial to investors, policymakers, and academics as they shed light on the interrelationships between Bitcoin and commodity markets. The findings of the study suggest that fluctuations in copper prices have a greater impact on Bitcoin prices than other commodities. Copper is utilized in numerous industries, including construction, electronics, and transportation. The results also indicate that shifts in the prices of oil, silver, and gold have a significant, albeit lesser, effect on Bitcoin prices. This study contributes to the comprehension of the relationship between Bitcoin and commodity prices, providing investors and policymakers with valuable insights.

Keywords: bitcoin, copper, gold, oil, commodities price, silver

Full Text:

Download PDF

References


Al-Yahyaee, K. H., Mensi, W., & Sensoy, A. (2019). Does oil volatility transmit to Bitcoin? Evidence from enhanced GARCH-MIDAS models. Journal of Economic Studies, 46(3),

-611. https://doi.org/10.1108/JES-07-2017-0158

Bouri, E., Gupta, R., & Tiwari, A. K. (2017). The co-movements among Bitcoin, gold and the dollar: Evidence from time-varying and frequency domain tests with wavelets. The North American Journal of Economics and Finance, 42, 393-406. https://doi.org/10.1016/j.najef.2017.03.006

Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2021). A quantile regression approach to analysing the hedge and safe-haven properties of Bitcoin and gold. Applied Economics Letters, 28(3), 194-199. https://doi.org/10.1080/13504851.2020.1747078

Caporale, G. M., & Plastun, A. (2019). Oil prices and Bitcoin: A new direction for investors.

Journal of International Financial Markets, Institutions and Money, 63, 101185. https://doi.org/10.1016/j.intfin.2019.101185

Cheah, E. T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32-36. https://doi.org/10.1016/j.econlet.2015.02.029

Ji, Q., Bouri, E., Gupta, R., & Roubaud, D. (2018). Gold price and Bitcoin price: Evidence from causality test. Finance Research Letters, 26, 215-219. https://doi.org/10.1016/j.frl.2017.12.003

Jung, S. H., Choi, H. J., & Kim, J. W. (2018). Stock price prediction using LSTM, RNN and CNN-sliding window model. Journal of the Korea Academia-Industrial cooperation Society, 19(7), 614-623.

Kristoufek, L. (2013). BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports, 3, 1-7. https://doi.org/10.1038/srep03415

Lee, K., Ni, S., & Ratti, R. A. (2015). Oil shocks and the US stock market: Do sign and size matter? Journal of International Financial Markets, Institutions and Money, 34, 41-54.

Nadarajah, S., & Chu, J. (2017). On the inefficiency of Bitcoin. Economics Letters, 150, 6-9. https://doi.org/10.1016/j.econlet.2016.11.007

Wang, Y., Wu, C., Yang, X., & Chen, L. (2015). The economic significance of copper price drivers. Resources Policy, 43, 101-109.

Zhang, X., Ding, Y., Song, J., & Huang, D. (2019). Stock price prediction based on LSTM neural network. IEEE Access, 7, 172052-172063.

Zhang, D., Wei, Y., & Liu, J. (2021). Time-varying Granger causality between oil prices and Bitcoin prices: Evidence from a neural network analysis. Energy Economics, 96, 105198. https://doi.org/10.1016/j.eneco.2021.105198




DOI: https://doi.org/10.37531/sejaman.v6i2.5755

Refbacks

  • There are currently no refbacks.


Flag Counter

Creative Commons License

S E I K O : Journal of Management & Business is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
 
© All rights reserved 2018. S E I K O : Journal of Management & Business - ISSN (Print) : 2598-831X, ISSN (Online) : 2598-8301.
 

Web
Analytics