Bitcoin Kapanış Fiyatları ile İşlem Hacmi Arasındaki Nedensellik: Zamanla Değişen Asimetrik Etkiler

Yıl 2025, Cilt: 25 Sayı: 1, 21 - 40, 27.03.2025

Nergis Tosun , Ayşegül Han

https://doi.org/10.18037/ausbd.1527760

Öz

İnternetin yaygınlaşmasıyla birlikte finansal piyasalarda da önemli gelişmeler yaşanmıştır. Kripto parada internetin finansal piyasalara kazandırmış olduğu faktörlerden biridir. Kripto paraların çeşitleri bulunmaktadır. En eski ve işlem hacmi en büyük olanı ise Bitcoin’dir. Bu çalışma, 17 Eylül 2014 ile 30 Haziran 2024 tarihleri arasında Bitcoin’in kapanış fiyatları-işlem hacmi arasındaki nedensellik ilişkisini kapsamlı bir şekilde incelemeyi amaçlamaktadır. Bu kapsamda, Hacker-Hatemi (2006) simetrik nedensellik testi, Hatemi-J (2012) Asimetrik Nedensellik Testi ve Zamanla Değişen Asimetrik Nedensellik Analizi yöntemleri kullanılmıştır. Hacker-Hatemi (2006) Simetrik Nedensellik Testi sonucunda, değişkenler arasında nedensellik ilişkisi elde edilememiştir. Ancak Hatemi-J (2012) Asimetrik Nedensellik Testi sonucunda, kapanış fiyatlarının pozitif şokları ile işlem hacminin pozitif şokları arasında çift yönlü nedensellik ilişkisi, işlem hacminin negatif şoklarından fiyatların negatif şoklarına doğru tek yönlü nedensellik olduğu görülmüştür.

Anahtar Kelimeler

Bitcoin İşlem Hacmi, Bitcoin Kapanış Fiyatı, Simetrik Nedensellik Testi, Asimetrik Nedensellik Testi, Zamanla Değişen Asimetrik Nedensellik Analizi

Causality between Bitcoin Closing Prices and Trading Volume: Time-Varying Asymmetric Effects

Öz

Financial markets have evolved as the Internet has become widespread. Cryptocurrency is one of the factors that the internet has brought to the financial markets. Different cryptocurrencies exist. The oldest and the one with the largest trading volume is bitcoin. It aims to fully investigate a cause-and-effect relationship between Bitcoin's closing price and trading volume between 17/09/2014 and 30/06/2024. In this context, Hacker-Hatemi (2006) symmetric causality test, Hatemi-J (2012) Asymmetric Causality Test and Time-Varying Asymmetric Causality Analysis methods were used. The Hacker-Hatemi (2006) symmetric causality test, Hatemi-J (2012) Asymmetric Causality Test and Time-Varying Asymmetric Causality Analysis methods were used in the study. As a result of the Hacker-Hatemi (2006) Symmetric Causality Test, no causal relationship was found between the variables. However, Hatemi-J (2012) Asymmetric Causality Test revealed that there is a bidirectional causality relationship between positive shocks of closing prices and positive shocks of trading volume and unidirectional causality from negative shocks of trading volume to negative shocks of prices.

Anahtar Kelimeler

Bitcoin Trading Volume, Bitcoin Closing Price, Symmetric Causality Test, Asymmetric Causality Test, Time-Varying Asymmetric Causality Analysis

Kaynakça

• Avrupa Merkez Bankası (2012). Virtual currency schemes. Research Papers, Germany. Available at https://www.ecb.europa.eu/pub/pdf/other/virtualcurrencyschemes201210en.pdf. Erişim tarihi: 21.05.2024.
• Balcılar, M., Bouri, E., Gupta, R. and Roubaud, D. (2017). Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Economic Modelling, 64, 74-81. https://doi.org/10.1016/j.econmod.2017.03.019.
• Bouri, E., Lau, C. K. M., Lucey, B. and Roubaud, D. (2019). Trading volume and the predictability of return and volatility in the cryptocurrency market. Finance Research Letters, 29, 340-346. https://doi.org/10.1016/j.frl.2018.08.015.
• Copeland, L. (1991). Cointegration tests with daily exchange rate data. Oxford Bulletin of Economics and Statistics, 53(2), 185-198. https://doi.org/10.1111/j.1468-0084.1991.mp53002005.x.
• Değer, M. K. and Pata, U. K. (2017). Türkiye’de dış ticaret ve karbondioksit salınımı arasındaki ilişkilerin simetrik ve asimetrik nedensellik testleriyle analizi, Doğuş Üniversitesi Dergisi, 18(1), 31-44.
• Dolado, J. J. and Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Theory, 15(4), 369-386. https://doi.org/10.1080/07474939608800362.
• El Alaoui, M., Bouri, E. and Roubaud, D. (2019). Bitcoin price–volume: A multifractal cross-correlation approach. Finance Research Letters, 31, 374-381. https://doi.org/10.1016/j.frl.2018.12.011.
• Fousekis, P. and Tzaferi, D. (2021). Returns and volume: Frequency connectedness in cryptocurrency markets. Economic Modelling, 95, 13-20. https://doi.org/10.1016/j.econmod.2020.11.013.
• Garfinkel, J. A., Hsiao, L. and Hu, D. (2024). The negative relation between abnormal volume and return in cryptocurrency. Working Paper. Available at http://dx.doi.org/10.2139/ssrn.4345640. Erişim tarihi: 17.06.2024.
• Gemici, E. and Polat, M. (2019). Relationship between price and volume in the Bitcoin market. The Journal of Risk Finance, 20(5), 435-444. https://doi.org/10.1108/JRF-07-2018-0111.
• Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross spectral methods. Econometrica, 37, 424-438. https://doi.org/10.2307/1912791.
• Granger, C. W. J. and Yoon, G. (2002). Hidden cointegration. University of California Department of Economics Discussion Paper 2002-02, San Diego. https://doi.org/10.2139/ssrn.313831.
• Hacker, R. S. and Hatemi-J, A. (2006). Tests for causality between integrated variables using asymptotic and bootstrap distribution: Theory and application, Applied Economics, 38(13), 1489-1500. https://doi.org/10.1080/00036840500405763.
• Hatemi-J, A. (2003). A new method to choose optimal lag order in stable and unstable VAR models. Applied Economics Letters, 10(3), 135-137. https://doi.org/10.1080/1350485022000041050.
• Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1), 447-456. https://doi.org/10.1007/s00181-011-0484-x.
• Horowitz, J. L. (2019). Bootstrap methods in econometrics. Annual Review of Economics, 11(1), 193-224. https://doi.org/10.1146/annurev-economics-080218-025651.
• Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and Quantitative Analysis, 22(1), 109-126. https://doi.org/10.2307/2330874.
• Katsiampa, P., Gkillas, K. and Longin, F. (2018). Cryptocurrency market activity during extremely volatile periods. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.3220781. Erişim tarihi: 18.05.2024.
• Moyo, C. and Phiri, A. (2023). Re-Examining Bitcoin’s price-volume relationship: A time-varying spectral analysis. Journal of Risk and Financial Management, 16(7), 324. https://doi.org/10.3390/jrfm16070324.
• Naeem, M., Bouri, E., Boako, G. and Roubaud, D. (2019). Tail dependence in the return-volume of leading cryptocurrencies. Finance Research Letters, 36, 101326. https://doi.org/10.1016/j.frl.2019.101326.
• Naeem, M., Joseph, M. and Hao, J. (2023). Is cryptocurrencies extreme returns-volumes relationship affected by COVID-19? Review of Economics and Finance, 21, 2713-2725. https://doi.org/10.55365/1923.x2023.21.293.
• Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Erişim tarihi: 12.06.2024. https://bitcoin.org/bitcoin.pdf.
• Özkan, N. (2012). Kripto para piyasasında fiyat değişimlerinin makine öğrenmesi yöntemleriyle tahmini. A. Ünvan, Y. (Ed.), Bankacılık ve Finans Çalışmaları (ss. 92- 114). Fransa: Livre de Lyon.
• Özyeşil, M. (2019). The relationship between the popularity of cryptocurrencies and their prices, returns and trading volumes: A structural break and comparative analysis. İstanbul İktisat Dergisi, 69(2), 133-157. https://doi.org/10.26650/ISTJECON2019-0017
• Pata, U. K. (2018). Türkiye’de enflasyon, tasarruf ve ekonomik büyüme arasındaki ilişkilerin simetrik ve asimetrik nedensellik testleri ile analizi, Maliye Dergisi, 174, 92-111.
• Sahoo, P. K. and Sethi, D. (2024). Market efficiency of the cryptocurrencies: Some new evidence based on price–volume relationship. International Journal of Finance & Economics, 29(2), 1569-1580. https://doi.org/10.1002/ijfe.2744.
• Sahoo, P. K., Sethi, D. and 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.
• Samut, S. and Yamak R. (2018). Price-volume relationship in cryptocurrencies: Rolling window causality test. B. Polat, M. Güler, H. Derin, H. (Ed.). Studies on Social Sciences (ss. 133-51), Adıyaman: İksad Yayınevi.
• Sapuric, S., Kokkinaki, A. and Georgiou, I. (2020). The relationship between Bitcoin returns, volatility and volume: Asymmetric GARCH modeling. Journal of Enterprise Information Management, 35(6), 1506-1521. https://doi.org/10.1108/JEIM-10-2018-0228.
• Toda, H. Y. and Yamamoto, Y. (1995). Statistical inference in vector autoregressions with possibly integrated processes, Journal of Econometrics, 66(1) 225-250. https://doi.org/10.1016/0304-4076(94)01616-8.
• Yılancı, V. and Bozoklu, Ş. (2014). Türk sermaye piyasasında fiyat ve işlem hacmi ilişkisi: Zamanla değişen asimetrik nedensellik analizi. Ege Academic Review, 14(2), 211-220.
• Yılmaz, T. and Kaygın, C. Y. (2018). Kripto paralarda getiri ve işlem hacmi arasındaki ilişkisi üzerine ampirik bir inceleme. A. Temizer, İ. Serbestoğlu, (Ed.). Multidisipliner Çalışmalar-4 (ss. 251-268). Montenegro: Institut za Geografıju.
• Zhang, Y., Garg, R., Golden, L. L., Brockett, P. L. and Sharma, A. (2024). Segmenting Bitcoin transactions for price movement prediction. Journal of Risk and Financial Management, 17(128), 1-17. https://doi.org/10.3390/jrfm17030128.