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BİTCOİN İLE ÖNEMLİ DÖVİZ KURLARI ARASINDA NEDENSELLİK İLİŞKİSİ

Yıl 2021, ICOMEP ÖZEL SAYISI, 108 - 130, 20.12.2021

Emre Çevik , Hande Çalışkan , Emrah İsmail Çevik

https://doi.org/10.54600/igdirsosbilder.991733
Cited By: 3

Öz

Bu çalışmanın amacı, Bitcoin ile Euro/Dolar, İngiliz Sterlini/Dolar, Kanada Doları/Dolar, Japon Yeni/Dolar ve Çin Yuanı/Dolar gibi önemli döviz kurları arasındaki dinamik ilişkiyi incelemektir. Bu bağlamda, Bitcoin ve döviz kurları arasında ortalamada ve volatilitede yayılım etkisinin varlığını incelemek için Hong (2001) tarafından önerilen ortalamada ve varyansta nedensellik testi kullanılmıştır. Ayrıca, Bitcoin ve döviz kurları arasındaki kuyruk bağımlılığının varlığını araştırmak için Hong vd. (2009) tarafından önerilen risk durumlarında nedensellik testi kullanılmıştır. 19 Ağustos 2011 ile 6 Ağustos 2021 tarihleri arasında günlük verileri kullanarak, Euro, Pound ve Kanada Dolar’ından Bitcoin’e yönelik tek yönlü ortalamada nedensellik ilişkisi tespit edilmiştir. Öte yandan, varyansta nedensellik testi sonuçları, Bitcoin ile Euro ve Pound arasında çift yönlü bir oynaklık yayılım etkisinin olduğunu göstermektedir. Ayrıca, Yuan ve Kanada Dolar'ın Bitcoin'in varyansta Granger nedeni olduğu belirlenmiştir. Risk durumlarındaki nedensellik testi sonuçları, Euro ve Pound’dan Bitcoin’e yönelik nedensellik ilişkisine dair kanıt sunmaktadır. Bununla birlikte Bitcoin’deki beklenmedik kayıplar, Yen’deki beklenmedik kayıpların Granger nedenidir. Genel olarak, ampirik sonuçlar Çin para biriminin Bitcoin ile daha az entegre olduğunu göstermektedir.

Anahtar Kelimeler

Bitcoin Kripto Para Döviz Kuru Nedensellik

Teşekkür

20-21 Nisan 2019 tarihinde İstanbul’da gerçekleşen ICOMEP kongresinde tebliğ olarak sunulan “Bitcoin ile Döviz Kurları Arasında Ortalama ve Varyansta Nedensellik Analizi” başlıklı tebliğ bu makaleye teorik temel oluşturmuştur.

Kaynakça

  • Albuquerque Bruno Saboia de, Marcelo de Castro Callado (2015). “Understanding Bitcoins: Facts and Questions”, Revista Brasileira de Economia, 69, s. 3-16.
  • Al-Yahyaee Khamis Hamed, Mensi Walid, Yoon Seong-Min (2018). “Efficiency, Multifractality, and the Long-Memory Property of The Bitcoin Market: A Comparative Analysis with Stock, Currency, And Gold Markets”, Finance Research Letters, 27, s. 228-234.
  • Badev Anton I., Chen Matthew (2014). “Bitcoin: Technical Background and Data Analysis”, FEDS Working Paper No. 2014-104, https://ssrn.com/abstract=2544331. (Erişim Tarihi: 12.04.2021) Baek Chung, Elbeck Matt (2015). “Bitcoins As an Investment or Speculative Vehicle? A First Look”, Applied Economics Letters, 22, s. 30-34. Blau Benjamin M. (2017). “Price Dynamics and Speculative Trading in Bitcoin”, Research in International Business and Finance, 41, 493-499.
  • Bodart V., Candelon B. (2009). “Evidence of Interdependence and Contagion Using a Frequency Domain Framework”, Emerging Markets Review, 10 (2), s. 140–150.
  • Bollerslev T. (1986). “Generalized Autoregressive Conditional Heteroscedasticity”, Journal of Econometrics, 31, s. 307-327.
  • Bouoiyour Jamal, Selmi Refk, Tiwari Aviral Kumar (2015). “Is Bitcoin Business Income or Speculative Foolery? New Ideas Through an Improved Frequency Domain Analysis”, Annals of Financial Economics,10 (1), s. 1-23.
  • Buğan, Mehmet Fatih (2021). “Bitcoin ve Altcoin Kripto Para Piyasalarında Finansal Balonlar”, Akademik Araştırmalar ve Çalışmalar Dergisi (AKAD), 13 (24), s. 165-180.
  • Çevik E. (2017). “Pay Piyasası ile Döviz Kurları Arasında Risk Durumlarında Nedensellik İlişkisi”, Balkan Sosyal Bilimler Dergisi, 6 (12), s. 82-94.
  • Cevik Emrah Ismail, Dibooglu Sel, Atıf Awad Abdallah, Eisa Abdulrahman Al-Eisa (2021). “Oil Prices, Stock Market Returns, and Volatility Spillovers: Evidence from Saudi Arabia”, International Economics and Economic Policy, 18, s. 157-175.
  • Cheung Yin-Wong, Ng Lilian K. (1996). “A Causality-In-Variance Test and Its Application to Financial Market Prices”, Journal of Econometrics, 72 (1), s. 33-48.
  • Ciaian Pavel, Rajcaniova Miroslava, Kancs d’Artis (2016). “The Economics of Bitcoin Price Formation”, Applied Economics, 48, s. 1799-1815.
  • Conrad Christian, Custovic Anessa, Ghysels Eric (2018). “Long-and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis”, Journal of Risk and Financial Management, 11 (2), s. 1-23.
  • Dirican Cuneyt, Canoz Ismail (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), s. 377-392.
  • Du L., He Y. (2015). “Extreme Risk Spillovers Between Crude Oil and Stock Markets”, Energy Economics, 51, 455-465.
  • Dulupçu Murat Ali, Yiğit Mehmet, Genç Asena Gizem (2017). “Dijital Ekonominin Yükselen Yüzü: Bitcoin’in Değeri ile Bilinirliği Arasındaki İlişkinin Analizi”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 22. Kayfor 15 Özel Sayısı, s. 2241-2258.
  • Dyhrberg Anne Haubo (2016a). “Bitcoin, Gold and the Dollar-A GARCH Volatility Analysis”, Finance Research Letters, 16, s. 85-92.
  • Dyhrberg Anne Haubo (2016b). “Hedging Capabilities of Bitcoin. Is It the Virtual Gold?”, Finance Research Letters, 16, a. 139-144.
  • Guegan Dominique (2018). “The Digital World: I - Bitcoin: from History to Real Live”, https://halshs.archives-ouvertes.fr/halshs-01822962/document, (Erişim Tarihi: 12.04.2021)
  • Hong Y., Liu Y., Wang S. (2009). “Granger Causality in Risk and Detection of Extreme Risk Spillover between Financial Markets”, Journal of Econometrics, 150, s. 271–287.
  • Hong Yongmiao (2001). “A Test for Volatility Spillover with Application to Exchange Rates”, Journal of Econometrics, 103 (1), s. 183-224.
  • Katsiampa Paraskevi (2017). “Volatility Estimation for Bitcoin: A Comparison of GARCH Models”, Economics Letters, 158, s. 3-6.
  • Koçoğlu Şahnaz, Çevik Yasin Erdem, Tanrıöven Cihan (2016). “Bitcoin piyasalarının etkinliği, likiditesi ve oynaklığı”, İşletme Araştırmaları Dergisi, 8 (2), s. 77-97.
  • Korkmaz Turhan, Çevik Emrah İ., Atukeren Erdal (2012). “Return and Volatility Spillovers among CIVETS Stock Markets”, Emerging Markets Review, 13 (2), s. 230-252.
  • Koutmos Dimitrios (2018). “Return and Volatility Spillovers Among Cryptocurrencies”, Economics Letters, 173, s. 122-127.
  • Nakamoto Satoshi (2008). "Bitcoin: A Peer-To-Peer Electronic Cash System”, Decentralized Business Review, s. 21260.
  • Nelson, D. B. (1991). “Conditional Heteroskedasticity in Asset Returns: A New Approach”, Econometrica, 59, s. 347-370.
  • Palazzi Rafael Baptista, Júnior Gerson de Souza Raimundo, Klotzle Marcelo Cabus (2020). “The Dynamic Relationship Between Bitcoin and The Foreign Exchange Market: A Nonlinear Approach to Test Causality Between Bitcoin and Currencies”, Finance Research Letters, s. 101893.
  • Panagiotidis Theodore, Stengos Thanasis, Vravosinos Orestis (2019). "The Effects of Markets, Uncertainty and Search Intensity on Bitcoin Returns”, International Review of Financial Analysis, 63, s. 220-242.
  • Rogojanu Angela, Badea Liana (2014). "The Issue of Competing Currencies. Case Study-Bitcoin”, Theoretical and Applied Economics, 21 (1), s. 103-114.
  • Sovbetov Yhlas (2018). “Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero”, Journal of Economics and Financial Analysis, 2 (2), s. 1-27.
  • Szetela Beata, Mentel Grzegorz, Gędek Stanisław (2016). “Dependency Analysis Between Bitcoin and Selected Global Currencies”, Dynamic Econometric Models, 16 (1), s. 133-144.
  • Tse, Y. K. (1998), “The Conditional Heteroscedasticity of The Yen-Dollar Exchange Rate”, Journal of Applied Econometrics, 13, s. 49-55.
  • Verardi V., Vermandele C. (2018). “Univariate and Multivariate Outlier Identification for Skewed or Heavy-Tailed Distributions”, The Stata Journal, 18(3), s. 517–532.
  • Vockathaler Brian (2015). “The Bitcoin Boom: An In-Depth Analysis of The Price of Bitcoins”, Major Research Paper University of Ottawa, s. 1-75. https://ruor.uottawa.ca/bitstream/10393/32888/1/Vockathaler_ Brian_2015_researchpaper.pdf, (Erişim Tarihi: 12.04.2021)
  • Warshaw, Evan (2020). “Asymmetric Volatility Spillover Between European Equity and Foreign Exchange Markets: Evidence from The Frequency Domain”, International Review of Economics & Finance, 68, s. 1-14.
  • Zheng Zibin, Shaoan Xie, Hongning Dai, Xiangping Chen, Huaimin Wang (2017). “An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends”, IEEE International Congress on Big Data, s. 557-564. doi: 10.1109/BigDataCongress.2017.85. (Erişim Tarihi: 12.04.2021)

Yıl 2021, ICOMEP ÖZEL SAYISI, 108 - 130, 20.12.2021

Emre Çevik , Hande Çalışkan , Emrah İsmail Çevik

https://doi.org/10.54600/igdirsosbilder.991733
Cited By: 3

Öz

The aim of this study is to examine the dynamic relationship between Bitcoin and major foreign exchange rates namely Euro, British Pound, Canadian Dollar, Japanese Yen, and Chinese Yuan. In this context, we employ the causality-in-mean and variance test suggested by Hong (2001) to examine the presence of mean and volatility spillover effects between Bitcoin and foreign exchange rates. Also, we use the causality-in-risks test proposed by Hong et al. (2009) to investigate the existence of tail dependence between Bitcoin and foreign exchange rates. By using daily data from August 19, 2011, through August 6, 2021, we find unidirectional Granger causality-in-mean from Euro, Pound, and Dollar to Bitcoin. On the other hand, causality-in-variance test results suggest a bidirectional volatility spillover effect between Bitcoin and Euro and Pound. Also, Yuan and Dollar are found to be Granger cause-in-variance of Bitcoin. Causality-in-risk test results provide evidence in favor of causal link running from Euro and Pound to Bitcoin. In addition, unexpected losses in Bitcoin are the Granger cause of unexpected losses in the Yen. Overall, our empirical analysis results show that the Chinese currency market seems to be less integrated with Bitcoin.

Kaynakça

  • Albuquerque Bruno Saboia de, Marcelo de Castro Callado (2015). “Understanding Bitcoins: Facts and Questions”, Revista Brasileira de Economia, 69, s. 3-16.
  • Al-Yahyaee Khamis Hamed, Mensi Walid, Yoon Seong-Min (2018). “Efficiency, Multifractality, and the Long-Memory Property of The Bitcoin Market: A Comparative Analysis with Stock, Currency, And Gold Markets”, Finance Research Letters, 27, s. 228-234.
  • Badev Anton I., Chen Matthew (2014). “Bitcoin: Technical Background and Data Analysis”, FEDS Working Paper No. 2014-104, https://ssrn.com/abstract=2544331. (Erişim Tarihi: 12.04.2021) Baek Chung, Elbeck Matt (2015). “Bitcoins As an Investment or Speculative Vehicle? A First Look”, Applied Economics Letters, 22, s. 30-34. Blau Benjamin M. (2017). “Price Dynamics and Speculative Trading in Bitcoin”, Research in International Business and Finance, 41, 493-499.
  • Bodart V., Candelon B. (2009). “Evidence of Interdependence and Contagion Using a Frequency Domain Framework”, Emerging Markets Review, 10 (2), s. 140–150.
  • Bollerslev T. (1986). “Generalized Autoregressive Conditional Heteroscedasticity”, Journal of Econometrics, 31, s. 307-327.
  • Bouoiyour Jamal, Selmi Refk, Tiwari Aviral Kumar (2015). “Is Bitcoin Business Income or Speculative Foolery? New Ideas Through an Improved Frequency Domain Analysis”, Annals of Financial Economics,10 (1), s. 1-23.
  • Buğan, Mehmet Fatih (2021). “Bitcoin ve Altcoin Kripto Para Piyasalarında Finansal Balonlar”, Akademik Araştırmalar ve Çalışmalar Dergisi (AKAD), 13 (24), s. 165-180.
  • Çevik E. (2017). “Pay Piyasası ile Döviz Kurları Arasında Risk Durumlarında Nedensellik İlişkisi”, Balkan Sosyal Bilimler Dergisi, 6 (12), s. 82-94.
  • Cevik Emrah Ismail, Dibooglu Sel, Atıf Awad Abdallah, Eisa Abdulrahman Al-Eisa (2021). “Oil Prices, Stock Market Returns, and Volatility Spillovers: Evidence from Saudi Arabia”, International Economics and Economic Policy, 18, s. 157-175.
  • Cheung Yin-Wong, Ng Lilian K. (1996). “A Causality-In-Variance Test and Its Application to Financial Market Prices”, Journal of Econometrics, 72 (1), s. 33-48.
  • Ciaian Pavel, Rajcaniova Miroslava, Kancs d’Artis (2016). “The Economics of Bitcoin Price Formation”, Applied Economics, 48, s. 1799-1815.
  • Conrad Christian, Custovic Anessa, Ghysels Eric (2018). “Long-and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis”, Journal of Risk and Financial Management, 11 (2), s. 1-23.
  • Dirican Cuneyt, Canoz Ismail (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), s. 377-392.
  • Du L., He Y. (2015). “Extreme Risk Spillovers Between Crude Oil and Stock Markets”, Energy Economics, 51, 455-465.
  • Dulupçu Murat Ali, Yiğit Mehmet, Genç Asena Gizem (2017). “Dijital Ekonominin Yükselen Yüzü: Bitcoin’in Değeri ile Bilinirliği Arasındaki İlişkinin Analizi”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 22. Kayfor 15 Özel Sayısı, s. 2241-2258.
  • Dyhrberg Anne Haubo (2016a). “Bitcoin, Gold and the Dollar-A GARCH Volatility Analysis”, Finance Research Letters, 16, s. 85-92.
  • Dyhrberg Anne Haubo (2016b). “Hedging Capabilities of Bitcoin. Is It the Virtual Gold?”, Finance Research Letters, 16, a. 139-144.
  • Guegan Dominique (2018). “The Digital World: I - Bitcoin: from History to Real Live”, https://halshs.archives-ouvertes.fr/halshs-01822962/document, (Erişim Tarihi: 12.04.2021)
  • Hong Y., Liu Y., Wang S. (2009). “Granger Causality in Risk and Detection of Extreme Risk Spillover between Financial Markets”, Journal of Econometrics, 150, s. 271–287.
  • Hong Yongmiao (2001). “A Test for Volatility Spillover with Application to Exchange Rates”, Journal of Econometrics, 103 (1), s. 183-224.
  • Katsiampa Paraskevi (2017). “Volatility Estimation for Bitcoin: A Comparison of GARCH Models”, Economics Letters, 158, s. 3-6.
  • Koçoğlu Şahnaz, Çevik Yasin Erdem, Tanrıöven Cihan (2016). “Bitcoin piyasalarının etkinliği, likiditesi ve oynaklığı”, İşletme Araştırmaları Dergisi, 8 (2), s. 77-97.
  • Korkmaz Turhan, Çevik Emrah İ., Atukeren Erdal (2012). “Return and Volatility Spillovers among CIVETS Stock Markets”, Emerging Markets Review, 13 (2), s. 230-252.
  • Koutmos Dimitrios (2018). “Return and Volatility Spillovers Among Cryptocurrencies”, Economics Letters, 173, s. 122-127.
  • Nakamoto Satoshi (2008). "Bitcoin: A Peer-To-Peer Electronic Cash System”, Decentralized Business Review, s. 21260.
  • Nelson, D. B. (1991). “Conditional Heteroskedasticity in Asset Returns: A New Approach”, Econometrica, 59, s. 347-370.
  • Palazzi Rafael Baptista, Júnior Gerson de Souza Raimundo, Klotzle Marcelo Cabus (2020). “The Dynamic Relationship Between Bitcoin and The Foreign Exchange Market: A Nonlinear Approach to Test Causality Between Bitcoin and Currencies”, Finance Research Letters, s. 101893.
  • Panagiotidis Theodore, Stengos Thanasis, Vravosinos Orestis (2019). "The Effects of Markets, Uncertainty and Search Intensity on Bitcoin Returns”, International Review of Financial Analysis, 63, s. 220-242.
  • Rogojanu Angela, Badea Liana (2014). "The Issue of Competing Currencies. Case Study-Bitcoin”, Theoretical and Applied Economics, 21 (1), s. 103-114.
  • Sovbetov Yhlas (2018). “Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero”, Journal of Economics and Financial Analysis, 2 (2), s. 1-27.
  • Szetela Beata, Mentel Grzegorz, Gędek Stanisław (2016). “Dependency Analysis Between Bitcoin and Selected Global Currencies”, Dynamic Econometric Models, 16 (1), s. 133-144.
  • Tse, Y. K. (1998), “The Conditional Heteroscedasticity of The Yen-Dollar Exchange Rate”, Journal of Applied Econometrics, 13, s. 49-55.
  • Verardi V., Vermandele C. (2018). “Univariate and Multivariate Outlier Identification for Skewed or Heavy-Tailed Distributions”, The Stata Journal, 18(3), s. 517–532.
  • Vockathaler Brian (2015). “The Bitcoin Boom: An In-Depth Analysis of The Price of Bitcoins”, Major Research Paper University of Ottawa, s. 1-75. https://ruor.uottawa.ca/bitstream/10393/32888/1/Vockathaler_ Brian_2015_researchpaper.pdf, (Erişim Tarihi: 12.04.2021)
  • Warshaw, Evan (2020). “Asymmetric Volatility Spillover Between European Equity and Foreign Exchange Markets: Evidence from The Frequency Domain”, International Review of Economics & Finance, 68, s. 1-14.
  • Zheng Zibin, Shaoan Xie, Hongning Dai, Xiangping Chen, Huaimin Wang (2017). “An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends”, IEEE International Congress on Big Data, s. 557-564. doi: 10.1109/BigDataCongress.2017.85. (Erişim Tarihi: 12.04.2021)
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makaleleri
Yazarlar

Emre Çevik 0000-0002-2012-9886

Hande Çalışkan 0000-0002-3137-932X

Emrah İsmail Çevik 0000-0002-8155-1597

Yayımlanma Tarihi 20 Aralık 2021
Yayımlandığı Sayı Yıl 2021 ICOMEP ÖZEL SAYISI

Kaynak Göster

APA Çevik, E., Çalışkan, H., & Çevik, E. İ. (2021). BİTCOİN İLE ÖNEMLİ DÖVİZ KURLARI ARASINDA NEDENSELLİK İLİŞKİSİ. Iğdır Üniversitesi Sosyal Bilimler Dergisi108-130. https://doi.org/10.54600/igdirsosbilder.991733

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Finans Ekonomi ve Sosyal Araştırmalar Dergisi
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Bitcoin’in kriz dönemindeki çeşitlendirici etkisi: G7’den kanıtlar
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