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CAUSALITY AND COINTEGRATION IN CRYPTOCURRENCY MARKETS

Yıl 2022, Sayı: 34, 129 - 142, 31.01.2022
https://doi.org/10.18092/ulikidince.938688

Öz

This paper investigates the causality and cointegration relationships between seven major cryptocurrencies, namely Bitcoin (BTC), Binance Coin (BNB), Cardano (ADA), Dogecoin (DOGE), Ethereum (ETH), Polkadot (DOT) and Ripple (XRP), using Johansen Cointegration and Granger Causality tests over the period from August 21, 2020 to April 19, 2021. Results indicate that there exists cointegration among cryptocurrencies in the long run. Findings also show that there is a bi-directional causal relationship between BNB and ETH. Additionally, BNB appears to be Granger cause of ADA, DOGE and DOT. On the other hand, analyses provide evidence of one-way causality running from XRP to both DOGE and DOT. These results might have some important implications for investors in terms of portfolio management.

Kaynakça

  • Adebola, S.S., Gil-Alana, L.A. and Madigu, G. (2019). Gold Prices and Cryptocurrencies: Evidence of Convergence and Cointegration. Physica A: Statistical Mechanics and Its Applications, 523, 1227-1236.
  • Aksoy, E., Teker, T., Mazak, M. and Kocabıyık, T. (2020). Kripto Paralar ve Fiyat İlişkileri Üzerine Bir Analiz: Toda-Yamamoto Nedensellik Analizi ile Bir İnceleme. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 37, 110-129.
  • Bedowska-Sójka, B., Hinc, T. and Kliber, A. (2020). Volatility and Liquidity in Cryptocurrency Markets – The Causality Approach. 5th Wroclaw International Conference in Finance, 31-44, Wroclaw.
  • Bilgin, C. and Şahbaz, A. (2009). Causality Relations between Growth and Export in Turkey. Gaziantep Üniversitesi Sosyal Bilimler Dergisi, 8(1), 177-198.
  • Büyükakın, F., Bozkurt, H. and Cengiz, V. (2009). Türkiye’de Parasal Aktarımın Faiz Kanalının Granger Nedensellik ve Toda-Yamamoto Yöntemleri ile Analizi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 33, 101-118.
  • Carpenter, A. (2016). Portfolio Diversification with Bitcoin. Journal of Undergraduate Research in Finance, 6(1), 1-27.
  • Corelli, A. (2018). Cryptocurrencies and Exchange Rates: A Relationship and Causality Analysis. Risks, 6(4), 1-11.
  • Dastgir, S., Demir, E., Downing, G., Gozgor, G. and Lau, C.K.M. (2019). The Causal Relationship Between Bitcoin Attention and Bitcoin Returns: Evidence from the Copula-based Granger Causality Test. Finance Research Letters, 28, 160-164.
  • Dirican, C. and Canoz, I. (2017). The Cointegration Relationship Between Bitcoin Prices and Major World Stock Indices: An Analysis with ARDL Model Approach. Journal of Economics, Finance and Accounting, 4(4), 377-392.
  • Elsayed, A.H., Gozgor, G. and Lau, C.K.M. (in press). Causality and Dynamic Spillovers among Cryptocurrencies and Currency Markets. International Journal of Finance & Economics.
  • Engle, R.F. and Granger, C.W.J. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276.
  • Feng, W., Wang, Y. and Zhang, Z. (2018). Can Cryptocurrencies be a Safe Haven: A Tail Risk Perspective Analysis. Applied Economics, 50(44), 4745-4762.
  • Gangwal, S. (2016). Analyzing the Effects of Adding Bitcoin to Portfolio. International Journal of Economics and Management Engineering, 10(10), 3519-3532.
  • Gemici, E. and Polat, M. (in press). Causality-in-mean and Causality-in-variance among Bitcoin, Litecoin and Ehtereum. Studies in Economics and Finance.
  • Gil-Alana, L.A., Abakah, E.J.A. and Rojo, M.F.R. (2020). Cryptocurrencies and Stock Market Indices. Are They Related? Research in International Business and Finance, 51, 1-11.
  • Granger, C.W.J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
  • Guesmi, K., Saadi, S., Abid, L. and Ftiti, Z. (2019). Portfolio Diversification with Virtual Currency: Evidence from Bitcoin. International Review of Financial Analysis, 63, 431-437.
  • Gül, Y. (2020). Kripto Paralar ve Portföy Çeşitlendirmesi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 65, 125-141.
  • Güneş, S. (2013). Finansal Gelişmişlik ve Büyüme Arasındaki Nedensellik Testi: Türkiye Örneği. Doğuş Üniversitesi Dergisi, 14(1), 73-85.
  • Işık, N., Acar, M. and Işık, H.B. (2004). Enflasyon ve Döviz Kuru İlişkisi: Bir Eşbütünleşme Analizi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(2), 325-340.
  • Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2&3), 231-254.
  • Kayral, I.E. (2020). En Yüksek Piyasa Değerine Sahip Üç Kripto Paranın Volatilitelerinin Tahmin Edilmesi. Finansal Araştırmalar ve Çalışmalar Dergisi, 12(22), 152-168.
  • Keskin, Z. and Aste, T. (2020). Information-theoretic Measures for Nonlinear Causality Detection: Application to Social Media Sentiment and Cryptocurrency Prices. Royal Society Open Science, 7(9), 1-16.
  • Lee, D.K.C., Guo, L. and Wang, Y. (2018). Cryptocurrency: A New Investment Opportunity? The Journal of Alternative Investments, 20(3), 16-40.
  • Li, R., Li, S., Yuan, D. and Zhu, H. (2021). Investor Attention and Cryptocurrency: Evidence from Wavelet-based Quantile Granger Causality Analysis. Research in International Business and Finance, 56, 1-29.
  • Lin, Z.Y. (2021). Investor Attention and Cryptocurrency Performance. Finance Research Letters, 40, 1-7.
  • Mokni, K. and Ajmi, A.N. (2021). Cryptocurrencies vs. US Dollar: Evidence from Causality in Quantiles Analysis. Economic Analysis and Policy, 69, 238-252.
  • Sahoo, P.K. (in press). COVID-19 Pandemic and Cryptocurrency Markets: An empirical Analysis from a Linear and Nonlinear Causal Relationship. Studies in Economics and Finance.
  • Sami, M. and Abdallah, W. (in press). How does the Cryptocurrency Market Affect the Stock Market Performance in the MENA Region? Journal of Economic and Administrative Sciences.
  • Subramaniam, S. and Chakraborty, M. (2020). Investor Attention and Cryptocurrency Returns: Evidence from Quantile Causality Approach. Journal of Behavioral Finance, 21(1), 103-115.
  • Taban, S. (2006). Türkiye’de Sağlık ve Ekonomik Büyüme Arasındaki Nedensellik İlişkisi. Sosyoekonomi, 4(4), 31-46.
  • Trimborn, S., Li, M. and Härdle, W.K. (2020). Investing with Cryptocurrencies – A Liquidity Constrained Investment Approach, Journal of Financial Econometrics, 18(2), 280-306.
  • Wu, C.Y. and Pandey, V.K. (2014). The Value of Bitcoin in Enhancing the Effiency of an Investor’s Portfolio. Journal of Financial Planning, 27(9), 44-52.
  • Zhang, W. and Wang, P. (2020). Investor Attention and Pricing of Cryptocurrency Market. Evolutionary and Instutitutional Economics Review, 17(2), 445-468.

KRİPTO PARA PİYASALARINDA NEDENSELLİK VE EŞBÜTÜNLEŞME

Yıl 2022, Sayı: 34, 129 - 142, 31.01.2022
https://doi.org/10.18092/ulikidince.938688

Öz

Bu makalede, Johansen Eşbütünleşme ve Granger Nedensellik testleri kullanılarak Bitcoin (BTC), Binance Coin (BNB), Cardano (ADA), Dogecoin (DOGE), Ethereum (ETH), Polkadot (DOT) ve Ripple (XRP) olmak üzere yedi kripto paranın arasındaki nedensellik ve eşbütünleşme ilişkileri araştırılmaktadır. Çalışma dönemi 21 Ağustos 2020 – 19 Nisan 2021 tarihleri arasını kapsamaktadır. Sonuçlar, kripto paralar arasında uzun dönemde eşbütünleşme olduğunu işaret etmektedir. Bulgular ayrıca BNB ve ETH arasında çift yönlü nedensellik ilişkisi bulunduğunu göstermektedir. Bunlarla birlikte BNB’nin, ADA’nın, DOGE’nin ve DOT’un Granger nedeni olduğu görünmektedir. Diğer yandan analizler, XRP’den, hem DOGE’ye hem DOT’a doğru tek yönlü nedensellik bulunduğuna dair kanıtlar sunmaktadır. Bu sonuçlar yatırımcıların portföy yönetimi açısından bazı önemli çıkarımlar yapmasını sağlayabilir.

Kaynakça

  • Adebola, S.S., Gil-Alana, L.A. and Madigu, G. (2019). Gold Prices and Cryptocurrencies: Evidence of Convergence and Cointegration. Physica A: Statistical Mechanics and Its Applications, 523, 1227-1236.
  • Aksoy, E., Teker, T., Mazak, M. and Kocabıyık, T. (2020). Kripto Paralar ve Fiyat İlişkileri Üzerine Bir Analiz: Toda-Yamamoto Nedensellik Analizi ile Bir İnceleme. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 37, 110-129.
  • Bedowska-Sójka, B., Hinc, T. and Kliber, A. (2020). Volatility and Liquidity in Cryptocurrency Markets – The Causality Approach. 5th Wroclaw International Conference in Finance, 31-44, Wroclaw.
  • Bilgin, C. and Şahbaz, A. (2009). Causality Relations between Growth and Export in Turkey. Gaziantep Üniversitesi Sosyal Bilimler Dergisi, 8(1), 177-198.
  • Büyükakın, F., Bozkurt, H. and Cengiz, V. (2009). Türkiye’de Parasal Aktarımın Faiz Kanalının Granger Nedensellik ve Toda-Yamamoto Yöntemleri ile Analizi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 33, 101-118.
  • Carpenter, A. (2016). Portfolio Diversification with Bitcoin. Journal of Undergraduate Research in Finance, 6(1), 1-27.
  • Corelli, A. (2018). Cryptocurrencies and Exchange Rates: A Relationship and Causality Analysis. Risks, 6(4), 1-11.
  • Dastgir, S., Demir, E., Downing, G., Gozgor, G. and Lau, C.K.M. (2019). The Causal Relationship Between Bitcoin Attention and Bitcoin Returns: Evidence from the Copula-based Granger Causality Test. Finance Research Letters, 28, 160-164.
  • Dirican, C. and Canoz, I. (2017). The Cointegration Relationship Between Bitcoin Prices and Major World Stock Indices: An Analysis with ARDL Model Approach. Journal of Economics, Finance and Accounting, 4(4), 377-392.
  • Elsayed, A.H., Gozgor, G. and Lau, C.K.M. (in press). Causality and Dynamic Spillovers among Cryptocurrencies and Currency Markets. International Journal of Finance & Economics.
  • Engle, R.F. and Granger, C.W.J. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276.
  • Feng, W., Wang, Y. and Zhang, Z. (2018). Can Cryptocurrencies be a Safe Haven: A Tail Risk Perspective Analysis. Applied Economics, 50(44), 4745-4762.
  • Gangwal, S. (2016). Analyzing the Effects of Adding Bitcoin to Portfolio. International Journal of Economics and Management Engineering, 10(10), 3519-3532.
  • Gemici, E. and Polat, M. (in press). Causality-in-mean and Causality-in-variance among Bitcoin, Litecoin and Ehtereum. Studies in Economics and Finance.
  • Gil-Alana, L.A., Abakah, E.J.A. and Rojo, M.F.R. (2020). Cryptocurrencies and Stock Market Indices. Are They Related? Research in International Business and Finance, 51, 1-11.
  • Granger, C.W.J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
  • Guesmi, K., Saadi, S., Abid, L. and Ftiti, Z. (2019). Portfolio Diversification with Virtual Currency: Evidence from Bitcoin. International Review of Financial Analysis, 63, 431-437.
  • Gül, Y. (2020). Kripto Paralar ve Portföy Çeşitlendirmesi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 65, 125-141.
  • Güneş, S. (2013). Finansal Gelişmişlik ve Büyüme Arasındaki Nedensellik Testi: Türkiye Örneği. Doğuş Üniversitesi Dergisi, 14(1), 73-85.
  • Işık, N., Acar, M. and Işık, H.B. (2004). Enflasyon ve Döviz Kuru İlişkisi: Bir Eşbütünleşme Analizi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(2), 325-340.
  • Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2&3), 231-254.
  • Kayral, I.E. (2020). En Yüksek Piyasa Değerine Sahip Üç Kripto Paranın Volatilitelerinin Tahmin Edilmesi. Finansal Araştırmalar ve Çalışmalar Dergisi, 12(22), 152-168.
  • Keskin, Z. and Aste, T. (2020). Information-theoretic Measures for Nonlinear Causality Detection: Application to Social Media Sentiment and Cryptocurrency Prices. Royal Society Open Science, 7(9), 1-16.
  • Lee, D.K.C., Guo, L. and Wang, Y. (2018). Cryptocurrency: A New Investment Opportunity? The Journal of Alternative Investments, 20(3), 16-40.
  • Li, R., Li, S., Yuan, D. and Zhu, H. (2021). Investor Attention and Cryptocurrency: Evidence from Wavelet-based Quantile Granger Causality Analysis. Research in International Business and Finance, 56, 1-29.
  • Lin, Z.Y. (2021). Investor Attention and Cryptocurrency Performance. Finance Research Letters, 40, 1-7.
  • Mokni, K. and Ajmi, A.N. (2021). Cryptocurrencies vs. US Dollar: Evidence from Causality in Quantiles Analysis. Economic Analysis and Policy, 69, 238-252.
  • Sahoo, P.K. (in press). COVID-19 Pandemic and Cryptocurrency Markets: An empirical Analysis from a Linear and Nonlinear Causal Relationship. Studies in Economics and Finance.
  • Sami, M. and Abdallah, W. (in press). How does the Cryptocurrency Market Affect the Stock Market Performance in the MENA Region? Journal of Economic and Administrative Sciences.
  • Subramaniam, S. and Chakraborty, M. (2020). Investor Attention and Cryptocurrency Returns: Evidence from Quantile Causality Approach. Journal of Behavioral Finance, 21(1), 103-115.
  • Taban, S. (2006). Türkiye’de Sağlık ve Ekonomik Büyüme Arasındaki Nedensellik İlişkisi. Sosyoekonomi, 4(4), 31-46.
  • Trimborn, S., Li, M. and Härdle, W.K. (2020). Investing with Cryptocurrencies – A Liquidity Constrained Investment Approach, Journal of Financial Econometrics, 18(2), 280-306.
  • Wu, C.Y. and Pandey, V.K. (2014). The Value of Bitcoin in Enhancing the Effiency of an Investor’s Portfolio. Journal of Financial Planning, 27(9), 44-52.
  • Zhang, W. and Wang, P. (2020). Investor Attention and Pricing of Cryptocurrency Market. Evolutionary and Instutitutional Economics Review, 17(2), 445-468.
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm MAKALELER
Yazarlar

Yavuz Gül 0000-0002-0208-6798

Yayımlanma Tarihi 31 Ocak 2022
Yayımlandığı Sayı Yıl 2022 Sayı: 34

Kaynak Göster

APA Gül, Y. (2022). CAUSALITY AND COINTEGRATION IN CRYPTOCURRENCY MARKETS. Uluslararası İktisadi Ve İdari İncelemeler Dergisi(34), 129-142. https://doi.org/10.18092/ulikidince.938688


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