AN ANALYSIS OF THE CAUSALITY RELATIONSHIP BETWEEN BITCOIN ELECTRICITY CONSUMPTION, PRICE AND VOLUME

Year 2022, Volume: 7 Issue: 1, 103 - 122, 27.06.2022

Yakup Söylemez , Samet Gürsoy

https://doi.org/10.54452/jrb.1018901

Cited By: 2

Abstract

Bu çalışma fiyat ve işlem hacmi açısından kripto para piyasasının en önemli enstrümanı olan Bitcoin’in elektrik tüketimi ile fiyatı ve işlem hacmi arasındaki nedensellik ilişkisini analiz etmeyi amaçlamaktadır. Çalışmada Bitcoin elektrik tüketimi değişkeni Cambridge Bitcoin Elektrik Tüketim Endeksi ile temsil edilmektedir. Araştırmada Şubat 2017 ile Şubat 2021 tarihleri arasındaki 1446 günlük veri seti kullanılmıştır. Değişkenler arasındaki nedensellik ilişkisi Hatemi-J (2012) ve Toda Yamamoto (1995) testleri kullanılarak analiz edilmiştir. Ayrıca bu çalışma, Schinckus vd. (2020) tarafından yapılan çalışma ile birlikte Bitcoin elektrik tüketimi ile işlem hacmi asrasındaki ilişkiyi inceleyen ender çalışmalardan biridir. Bu çalışmanın sonuçlarına göre Bitcoin elektrik tüketimindeki düşüş Bitcoin fiyatında düşüşe neden olmaktadır. Ancak bu çalışmada Schinckus vd. (2020) tarafından yapılan çalışmaya benzer olarak zayıf ama negatif bir ilişki tespit edilmiştir.

Keywords

Bitcoin Elektrik Tüketimi, Bitcoin Fiyatı ve İşlem Hacmi, Asimetrik Nedensellik, Hatemi-J, Toda Yamamoto.

AN ANALYSIS OF THE CAUSALITY RELATIONSHIP BETWEEN BITCOIN ELECTRICITY CONSUMPTION, PRICE AND VOLUME

Abstract

This study aims to analyze the causal relationship between electricity consumption, price and transaction volume of Bitcoin, which is the most important asset of the crypto money market in terms of both market capitalization and transaction volume. In this study, the Bitcoin electricity consumption variable is represented by Cambridge Bitcoin Electricity Consumption Index. As the data set, 1446 days of data between February 2017 and February 2021 were used. The causality relationship between the variables is analyzed using the Hatemi-J (2012) and Toda Yamamoto (1995) tests. In addition, this study is a rare study that examines the relationship between electricity and volume, together with the work done by Schinckus et al. (2020). According to the results of this study, the decrease in Bitcoin electricity consumption causes a decrease in the Bitcoin price. However, a negative relationship is detected Bitcoin electricity consumption and Bitcoin trade volume in this study, like the study by Schinckus et al. (2020), the relationship was found to be very weak.

Keywords

Bitcoin Electricity Consumption, Bitcoin Price and Bitcoin Trade Volume, Asymmetric Causality, Hatemi-J, Toda Yamamoto

References

• Balcilar, M., Bouri, E., Gupta, R., & Roubaud, D. (2017). Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Economic Modelling, 64(March), 74–81. https://doi.org/10.1016/j.econmod.2017.03.019
• Bastian-Pinto, C. L., Araujo, F. V. d. S., Brandão, L. E., & Gomes, L. L. (2021). Hedging renewable energy investments with Bitcoin mining. Renewable and Sustainable Energy Reviews, 138(September 2020). https://doi.org/10.1016/j.rser.2020.110520
• Baur, D. G. (2019). The ( Un- ) Sustainability of Bitcoin Investments. 1–19.
• Bhuiyan, R. A., Husain, A., & Zhang, C. (2021). A wavelet approach for causal relationship between bitcoin and conventional asset classes. Resources Policy, 71(May 2020), 101971. https://doi.org/10.1016/j.resourpol.2020.101971
• Cocco, L., Pinna, A., & Marchesi, M. (2017). Banking on blockchain: Costs savings thanks to the blockchain technology. Future Internet, 9(3), 1–20. https://doi.org/10.3390/fi9030025
• Corbet, S., Katsiampa, P., & Lau, C. K. M. (2020). Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets. International Review of Financial Analysis, 71(April), 101571. https://doi.org/10.1016/j.irfa.2020.101571
• Corbet, S., Lucey, B., & Yarovaya, L. (2020). Bitcoin-energy markets interrelationships - New evidence. Resources Policy, June, 101916. https://doi.org/10.1016/j.resourpol.2020.101916
• Das, D., & Dutta, A. (2020). Bitcoin’s energy consumption: Is it the Achilles heel to miner’s revenue? Economics Letters, 186, 108530. https://doi.org/10.1016/j.econlet.2019.108530
• de Vries, A. (2020). Bitcoin’s energy consumption is underestimated: A market dynamics approach. Energy Research and Social Science, 70(February), 101721. https://doi.org/10.1016/j.erss.2020.101721
• Gallersdörfer, U., Klaaßen, L., & Stoll, C. (2020). Energy Consumption of Cryptocurrencies Beyond Bitcoin. Joule, 4(9), 1843–1846. https://doi.org/10.1016/j.joule.2020.07.013
• Gemici, E., & Polat, M. (2019). Relationship between price and volume in the Bitcoin market. Journal of Risk Finance, 20(5), 435–444. https://doi.org/10.1108/JRF-07-2018-0111
• Giungato, P., Rana, R., Tarabella, A., & Tricase, C. (2017). Current trends in sustainability of bitcoins and related blockchain technology. Sustainability (Switzerland), 9(12). https://doi.org/10.3390/su9122214
• Gozgor, G., Tiwari, A. K., Demir, E., & Akron, S. (2019). The relationship between Bitcoin returns and trade policy uncertainty. Finance Research Letters, 29(March), 75–82. https://doi.org/10.1016/j.frl.2019.03.016
• Granger, C. W., & Yoon, G. (2002). "Hidden cointegration". U of California, Economics Working Paper, (2002-02).
• Gürsoy, S. (2021). The effect of the monetary policy uncertainty of US and Japan on Bitcoin price. Journal of Yalova Social Scientific, 11(1), 7-16.
• Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1), 447-456.
• Jang, S. M., Yi, E., Kim, W. C., & Ahn, K. (2019). Information flow between bitcoin and other investment assets. Entropy, 21(11), 1–8. https://doi.org/10.3390/e21111116
• Jareño, F., González, M. de la O., Tolentino, M., & Sierra, K. (2020). Bitcoin and gold price returns: A quantile regression and NARDL analysis. Resources Policy, 67(February). https://doi.org/10.1016/j.resourpol.2020.101666
• Jiang, Y., Wang, G.-J., Wen, D.-Y., & Yang, X. (2020). Business conditions, uncertainty shocks and Bitcoin returns. Evolutionary and Institutional Economics Review, 17(2), 415–424. https://doi.org/10.1007/s40844-020-00172-3
• Kang, S. H., McIver, R. P., & Hernandez, J. A. (2019). Co-movements between Bitcoin and Gold: A wavelet coherence analysis. Physica A: Statistical Mechanics and Its Applications, 536, 120888. https://doi.org/10.1016/j.physa.2019.04.124
• Kang, S. H., Yoon, S. M., Bekiros, S., & Uddin, G. S. (2020). Bitcoin as Hedge or Safe Haven: Evidence from Stock, Currency, Bond and Derivatives Markets. Computational Economics, 56(2), 529–545. https://doi.org/10.1007/s10614-019-09935-6
• Keskin, Z., & Aste, T. (2019). Information-theoretic measures for non-linear causality detection: application to social media sentiment and cryptocurrency prices. ArXiv. https://doi.org/10.1098/rsos.200863
• Krause, M. J., & Tolaymat, T. (2018). Quantification of energy and carbon costs for mining cryptocurrencies. Nature Sustainability, 1(11), 711–718. https://doi.org/10.1038/s41893-018-0152-7
• Küfeoğlu, S., & Özkuran, M. (2019). Bitcoin mining: A global review of energy and power demand. Energy Research and Social Science, 58(August), 101273. https://doi.org/10.1016/j.erss.2019.101273
• Lahmiri, S., & Bekiros, S. (2020). Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic. Chaos, Solitons and Fractals, 139, 110084. https://doi.org/10.1016/j.chaos.2020.110084
• Li, J., Li, N., Peng, J., Cui, H., & Wu, Z. (2019). Energy consumption of cryptocurrency mining: A study of electricity consumption in mining cryptocurrencies. Energy, 168, 160–168. https://doi.org/10.1016/j.energy.2018.11.046
• Maghyereh, A., & Abdoh, H. (2020). Tail dependence between Bitcoin and financial assets: Evidence from a quantile cross-spectral approach. International Review of Financial Analysis, 71(June), 101545. https://doi.org/10.1016/j.irfa.2020.101545
• Martinazzi, S., Regoli, D., & Flori, A. (2020). A tale of two layers: The mutual relationship between bitcoin and lightning network. Risks, 8(4), 1–18. https://doi.org/10.3390/risks8040129
• Mir, U. (2020). Bitcoin and its energy usage: Existing approaches, important opinions, current trends, and future challenges. KSII Transactions on Internet and Information Systems, 14(8), 3243–3256. https://doi.org/10.3837/tiis.2020.08.005
• Mora, C., Rollins, R. L., Taladay, K., Kantar, M. B., Chock, M. K., Shimada, M., & Franklin, E. C. (2018). Bitcoin emissions alone could push global warming above 2°C. Nature Climate Change, 8(11), 931–933. https://doi.org/10.1038/s41558-018-0321-8
• Qin, M., Su, C. W., & Tao, R. (2021). BitCoin: A new basket for eggs? Economic Modelling, 94(February 2020), 896–907. https://doi.org/10.1016/j.econmod.2020.02.031
• Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57:1361-1401.
• Rehman, M. U., & Apergis, N. (2019). Determining the predictive power between cryptocurrencies and real time commodity futures: Evidence from quantile causality tests. Resources Policy, 61(July 2018), 603–616. https://doi.org/10.1016/j.resourpol.2018.08.015
• Rehman, M. U., & Vinh Vo, X. (2020). Cryptocurrencies and precious metals: A closer look from diversification perspective. Resources Policy, 66(April), 101652. https://doi.org/10.1016/j.resourpol.2020.101652
• Sahoo, P. K., Sethi, D., & Acharya, D. (2019). Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship. International Journal of Managerial Finance, 15(4), 533–545. https://doi.org/10.1108/IJMF-06-2017-0107
• Sapkota, N., & Grobys, K. (2019). Blockchain Consensus Protocols, Energy Consumption and Cryptocurrency Prices. SSRN Electronic Journal, 1–29. https://doi.org/10.2139/ssrn.3403983
• Schinckus, C., Nguyen, C. P., & Ling, F. C. H. (2020). Crypto-currencies trading and energy consumption. International Journal of Energy Economics and Policy, 10(3), 355–364. https://doi.org/10.32479/ijeep.9258
• Sedlmeir, J., Buhl, H. U., Fridgen, G., & Keller, R. (2020). The Energy Consumption of Blockchain Technology: Beyond Myth. Business and Information Systems Engineering, 62(6), 599–608. https://doi.org/10.1007/s12599-020-00656-x
• Stoll, C., Klaaßen, L., & Gallersdörfer, U. (2019). The Carbon Footprint of Bitcoin. Joule, 3(7), 1647–1661. https://doi.org/10.1016/j.joule.2019.05.012
• Su, C. W., Qin, M., Tao, R., Shao, X. F., Albu, L. L., & Umar, M. (2020). Can Bitcoin hedge the risks of geopolitical events? Technological Forecasting and Social Change, 159(June), 120182. https://doi.org/10.1016/j.techfore.2020.120182
• Su, C. W., Qin, M., Tao, R., & Umar, M. (2020). Financial implications of fourth industrial revolution: Can bitcoin improve prospects of energy investment? Technological Forecasting and Social Change, 158(June), 120178. https://doi.org/10.1016/j.techfore.2020.120178
• Taylor, D. (2018). An Analysis of Bitcoin and the Proof of Work Protocols Energy Consumption, Growth, Impact and Sustainability. http://www.esru.strath.ac.uk/Documents/MSc_2018/Taylor.pdf
• Umar, Z., Trabelsi, N., & Alqahtani, F. (2021). Connectedness between cryptocurrency and technology sectors: International evidence. International Review of Economics and Finance, 71(May 2019), 910–922. https://doi.org/10.1016/j.iref.2020.10.021
• Unvan, Y. A. (2019). 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, 0(0), 1–16. https://doi.org/10.1080/03610926.2019.1678644
• Wang, G. J., Xie, C., Wen, D., & Zhao, L. (2019). When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin. Finance Research Letters, 31(November 2018), 489–497. https://doi.org/10.1016/j.frl.2018.12.028
• Zade, M., Myklebost, J., Tzscheutschler, P., & Wagner, U. (2019). Is bitcoin the only problem? A scenario model for the power demand of blockchains. Frontiers in Energy Research, 7(MAR). https://doi.org/10.3389/fenrg.2019.00021
• Zivot, E. and Andrews, D. W. K. 1992. Further Evidence on the Great Crash, the Oil Price Shock, and the Unit-Root Hypothesis. Journal of Business & Economic Statistics 10(3):251-270.