KRİPTO PARALAR VE STABİL COİNLER ARASINDAKİ KANTİL BAĞLANTILILIK

Year 2022, Issue: 37, 143 - 156, 11.11.2022

Cantürk Kayahan Halilibrahim Gökgöz Tolga Murat

https://doi.org/10.18092/ulikidince.1146239

Abstract

Bu çalışma, kripto paralar ve stabil coinler arasındaki volatilite yayılım ilişkisini dinamik olarak analiz etmeyi amaçlamaktadır. Çalışma kapsamında 1 Ocak 2019 – 6 Nisan 2022 dönemini kapsayan Bitcoin (BTC), Ethereum (ETH), BNB kripto para birimleri ile Tether (USDT) ve USD Coin (USDC) stabilcoinlerinin günlük kapanış fiyat verileri, Q-VAR modeli kullanılarak analiz ediLmiştir. Bulgularımız, Covid-19 salgını sırasında kripto paralar ve stabil coinler arasındaki volatilite yayılımının arttığını gösterektedir. Ayrıca, kripto paralar ve stabil coinler arasındaki volatilite yayılımının yönü ve şiddeti küresel olaylardan etkilenmektedir. Kripto paralar ve stabil coinler arasındaki ilişki zayıfken; kendi aralarındaki ilişki güçlüdür. Bulgularımız, küresel olayların kripto varlıklar arasındaki etkileşimi etkilediğini ve kripto paralar ile stabil coinlerin birbirleri için iyi çeşitlendiriciler olabileceğini göstermektedir. Bu bulguların finansal piyasa düzenleyicileri, portföy yatırımcıları ve akademik araştırmalar için önemli etkileri vardır.

Keywords

Kripto paralar, Stabil coinler, Volatilite Yayılımı, Kantil Vektör Otoregresyon

QUANTILE CONNECTEDNESS BETWEEN CRYPTOCURRENCIES AND STABLECOINS

Abstract

This paper aims to analyze the volatility spillover relationship between cryptocurrencies and stablecoins dynamically. Within the scope of the study, the daily closing price data of Bitcoin (BTC), Ethereum (ETH), BNB cryptocurrencies, and Tether (USDT) and USD Coin (USDC) stablecoins covering the period from January 1, 2019 to April 6, 2022 was analyzed using the Q-VAR model. Our results suggest that the volatility spillover between the cryptocurrency and stablecoins increased during the Covid-19 pandemic. Moreover, the direction and severity of volatility spillover between cryptocurrencies and stablecoins are affected by global events. While the relationship between cryptocurrencies and stablecoins themselves is strong, the relationship between each other is weak. Our findings suggest that global events influence the interaction between crypto-assets and that cryptocurrencies and stablecoins can be good diversifiers for each other. These findings have important implications for financial market regulators, portfolio investors, and academic research.

Keywords

Cryptocurrencies, Stablecoins, Volatility Spillover, Quantile Vector Autoregression

References

• Akhtaruzzaman, M., Boubaker, S., Nguyen, D. K., & Rahman, M. (2022). Systemic Risk-Sharing Framework of Cryptocurrencies in the COVID–19 Crisis. Finance Research Letters, 47. https://doi.org/10.1016/j.frl.2022.102787
• Ando, T., Greenwood-Nimmo, M., & Shin, Y. (2022). Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks. Management Science, 4 (68), 2401-2431. https://doi.org/10.1287/mnsc.2021.3984
• Baur, D. G., & Hoang, L. T. (2021). A Crypto Safe Haven against Bitcoin. Finance Research Letters, 38. https://doi.org/10.1016/j.frl.2020.101431
• Bouri, E., Roubaud, D., Saeed, T., & Vo, X. V. (2021). Quantile Connectedness in the Cryptocurrency Market. Journal of International Financial Markets, Institutions and Money, 71. https://doi.org/10.1016/j.intfin.2021.101302
• Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Interest Rate Swaps and the Transmission Mechanism of Monetary Policy: A Quantile Connectedness Approach. Economics Letters, 204. https://doi.org/10.1016/j.econlet.2021.109891
• Fakhfekh, M., & Jeribi, A. (2020). Volatility Dynamics of Crypto-Currencies’ Returns: Evidence from Asymmetric and Long Memory GARCH Models. Research in International Business and Finance, 51. https://doi.org/10.1016/j.ribaf.2019.101075
• Grobys, K., & Duc Huynh, T. L. (2021). When Tether Says “JUMP!” Bitcoin Asks “How Low?”. Finance Research Letters. https://doi.org/10.1016/j.frl.2021.102644
• Grobys, K., Junttila, J., Kolari, J. W., & Sapkota, N. (2021). On the Stability of Stablecoins. Journal of Empirical Finance, 64, 207–223. https://doi.org/10.1016/j.jempfin.2021.09.002
• Hoang, L. T., & Baur, D. G. (2021). How Stable are Stablecoins? The European Journal of Finance. http://dx.doi.org/10.2139/ssrn.3519225
• Huynh, T., Nasir, M. A., Vo, X. V., & Nguyen, T. T. (2020). “Small Things Matter Most”: The Spillover Effects in the Cryptocurrency Market and Gold as a Silver Bullet. The North American Journal of Economics and Finance, 54. https://doi.org/10.1016/j.najef.2020.101277
• Jalan, A., Matkovskyy, R., & Yarovaya, L. (2021). “Shiny” Crypto Assets: A Systemic Look at Gold-Backed Cryptocurrencies during the COVID-19 Pandemic. International Review of Financial Analysis, 78. https://doi.org/10.1016/j.irfa.2021.101958
• Katsiampa, P., Yarovaya, L., & Zięba, D. (2022). High-Frequency Connectedness between Bitcoin and Other Top-Traded Crypto Assets during the COVID-19 Crisis. Journal of International Financial Markets, Institutions and Money, In Press. https://doi.org/10.1016/j.intfin.2022.101578
• Kumar, A. S., & Anandarao, S. (2019). Volatility Spillover in Crypto-Currency Markets: Some Evidences from GARCH and Wavelet Analysis. Physica A: Statistical Mechanics and its Applications, 542, 448-458. https://doi.org/10.1016/j.physa.2019.04.154
• Kumar, A., Iqbal, N., Mitra, S. K., Kristoufek, L., & Bouri, E. (2022). Connectedness among Major Cryptocurrencies in Standard Times and during the COVID-19 Outbreak. Journal of International Financial Markets, Institutions & Money, 77. https://doi.org/10.1016/j.intfin.2022.101523
• Moratis, G. (2021). Quantifying the spillover effect in the cryptocurrency market. Finance Research Letters, 31. doi: https://doi.org/10.1016/j.frl.2020.101534
• Naeem, M. A., Qureshi, S., Rehman, M., & Balli, F. (2021). COVID-19 and Cryptocurrency Market: Evidence from Quantile Connectedness. Applied Economics, 54 (3), 280-306. DOI: 10.1080/00036846.2021.1950908
• Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. https://bitcoin.org/bitcoin.pdf
• Nguyen, T. T., Nguyen, T. V., Nguyen, T. C., Pham, T. A., & Nguyen, Q. M. (2022). Stablecoins Versus Traditional Cryptocurrencies in Response to İnterbank Rates. Finance Research Letters, 47. dhttps://doi.org/10.1016/j.frl.2022.102744
• Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 1(58), 17-29. doi:https://doi.org/10.1016/S0165-1765(97)00214-0
• Pho, K. H., Ly, S., Lu, R., Van Hoang, T. H., & Wong, W.-K. (2021). Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China. International Review of Financial Analysis, 74, 1-30. doi:https://doi.org/10.1016/j.irfa.2021.101674
• Wang, G.-J., Ma, X.-y., & Wy, H.-y. (2020a). Are stablecoins truly diversifiers, hedges, or safe havens against traditional cryptocurrencies as their name suggests? Research in International Business and Finance, 54. doi:https://doi.org/10.1016/j.ribaf.2020.101225
• Wang, P., Li, X., Shen, D., & Zhang, W. (2020b). How does economic policy uncertainty affect the bitcoin market? Research in International Business and Finance, 53. doi:https://doi.org/10.1016/j.ribaf.2020.101234
• Wei, W. C. (2018). The impact of Tether grants on Bitcoin. Economics Letters, 171, 19-22. doi: https://doi.org/10.1016/j.econlet.2018.07.001
• Yousaf, I., & Ali, S. (2020). The COVID-19 outbreak and high frequency information transmission between major cryptocurrencies: Evidence from the VAR-DCC-GARCH approach. Borsa Istanbul Review, 20(1), 1-10. doi: https://doi.org/10.1016/j.bir.2020.10.003
• Zhang, S., & Mani, G. (2021). Popular cryptoassets (Bitcoin, Ethereum, and Dogecoin), Gold, and their relationships: volatility and correlation modeling. Data Science and Management, 4, 30-39.