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Asimetrik Volatilitenin Tahmini: Kripto Para Bitcoin Uygulaması

Year 2018, Volume: 3 Issue: 2, 240 - 247, 31.12.2018
https://doi.org/10.33905/bseusbed.450018

Abstract

Bitcoin, merkezi bir otoriteye veya
finansal bir kuruluşa bağlı olmayan ve kriptografik özellikler içeren dijital (kripto)
paralardan biridir. Bitcoin’ in Merkezi otoriteye bağlı olmaması ve fiyatını
etkileyen faktörlerin arz ve talep ile açıklanması yüksek volatite ile
sonuçlanmıştır. Son dönemlerde yatırımcıların en büyük endişesi fiyatlardaki
aşırı volatilite durumudur. Çalışmada Blockchain Teknolojisi, Madencilik ve
Blockchain Teknolojisinin bir çıktısı olan Bitcoin kısaca anlatılmıştır.
Çalışmanın uygulama bölümünde literatürde sıklıkla kullanılan yöntemlerden olan
ve asimetrik volatilitenin belirlenmesi amacıyla ARCH, GARCH, ARCHM, EGARCH ve
TARCH modelleri kullanılmıştır. Bu amaçla Bitcoin/USD kuru kapanış
fiyatlarından Bitcoine ilişkin tarihsel getiriler hesaplanmıştır. Hesaplama
dönemi 01.01.2015-11.02.2018 olarak belirlenmiştir. Yapılan analizler sonucunda
volatilite tahmini için en iyi sonuç veren TARCH yöntemi bulunmuştur. 

References

  • Bollerslev, T. (1990). “Modelling The Coherence İn Short-Run Nominal Exchange Rates: A Multivariate Generalized ARCH Model”. The Review of Economics And Statistics, 72(3): 498-505.Bouoiyour, J., & Selmi, R. (2015). “What does Bitcoin Look Like?” Annals of Economics and Finance, 16(2): 449-492.Bouoiyour, J., Selmi, R., & Tiwari, A. K. (2015). “Is Bitcoin Business İncome Or Speculative Foolery? New İdeas Through An İmproved Frequency Domain Analysis”. Annals of Financial Economics, 10(01). https://doi.org/10.1142/S2010495215500025. Dyhrberg, A. H. (2016). “Hedging Capabilities Of Bitcoin. Is İt The Virtual Gold?” Finance Research Letters, 16: 139-144.Engle, R. F. (1982). “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation”. Econometrica: Journal of the Econometric Society. 50(4): 987-1007.Engle, R. F., Lilien, D. M., & Robins, R. P. (1987). “Estimating Time Varying Risk Premia İn The Term Structure: The ARCH-M Model”. Econometrica: Journal of the Econometric Society, 55(2): 391-407.Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). “Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions”. SSRN Working Paper. https://ssrn.com/abstract=2425247.Gujarati, D. N. (1999). Temel Ekonometri, (Çev. Ümit Şenesen – Gülay Göktürk Şenesen) İstanbul: Literatür Yayınları.Guvenek, B., & Alptekin, V. (2009). “Reel Döviz Kuru Endeksinin Otoregresif Koşullu Değişen Varyanslılığının Analizi: İki Eşikli Tarch Yöntemi İle Modellenmesi”. Maliye Dergisi, 156: 294-309.Katsiampa, P. (2017). “Volatility Estimation for Bitcoin: A Comparison of GARCH Models”. Economics Letters, 158: 3-6.McKinnon, R. I. (1991). “Financial Control İn The Transition From Classical Socialism To A Market Economy”. Journal of Economic Perspectives, 5(4): 107-122.Nakamoto, S. (2008). “Bitcoin: A Peer-to-Peer Electronic Cash System”. https://bitcoin.org/bitcoin.pdf. Nelson, D. B. (1991). “Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica”. Journal of the Econometric Society. 59(2): 347-370.Özer. A. & Ece, O. (2016). “Vadeli İşlem Piyasalarında Anomalilerin Archgarch Modelleri İle Test Edilmesi: Türkiye Vadeli İşlemler Piyasası Üzerine Bir Uygulama”. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 6(2): 1-14. Şahin, E . (2018).” Crypto Money Bitcoin: Price Estimation With ARIMA andArtificial Neural Networks”. Fiscaoeconomia, 2 (2), 74-92.DOI: 10.25295/fsecon.2018.02.005. Tully, E., & Lucey, B. M. (2007). “A Power GARCH Examination of The Gold Market”. Research in International Business and Finance, 21(2): 316-325.Usta A. ve Dogantekin S. (2017). Blockchain 101, 1. Baskı, İstanbul, İnkilap Kitapevi. Vigna P. Ve Casey J. (2015). Kripto Para Çağı,(Çev. Ali ATAV) , 2. Baskı, Buzdağı Yayın Evi. Zakoian, J. M. (1994). “Threshold Heteroskedastic Models”. Journal Of Economic Dynamics And Control. 18(5): 931-955.

Estimation Of Asymmetric Volatility: Crypto Money Application

Year 2018, Volume: 3 Issue: 2, 240 - 247, 31.12.2018
https://doi.org/10.33905/bseusbed.450018

Abstract

Bitcoin is one of the digital (crypto) entities that are not affiliated to a central authority or financial institution and that contain cryptographic features. The fact that Bitcoin does not depend on central authority and disclose the factors affecting its price by supply and demand have resulted in high volatility. The biggest concern of investors in recent times is the excessive volatility of Bitcoin prices. Bitcoin, which is an output of Blockchain Technology, Mining and Blockchain Technology, is briefly described in this study. ARCH, GARCH, ARCH-M, EGARCH and TARCH models are used to determine the asymmetric volatility which is frequently used in the literature in the application part of the study. For this purpose, historical returns for Bitcoin are calculated from Bitcoin/USD closing prices. The calculation period is determined as 01.01.2015-11.02.2018. As a result of the analyzes made, it was found as TARCH method which gives the best result for estimating volatility.

References

  • Bollerslev, T. (1990). “Modelling The Coherence İn Short-Run Nominal Exchange Rates: A Multivariate Generalized ARCH Model”. The Review of Economics And Statistics, 72(3): 498-505.Bouoiyour, J., & Selmi, R. (2015). “What does Bitcoin Look Like?” Annals of Economics and Finance, 16(2): 449-492.Bouoiyour, J., Selmi, R., & Tiwari, A. K. (2015). “Is Bitcoin Business İncome Or Speculative Foolery? New İdeas Through An İmproved Frequency Domain Analysis”. Annals of Financial Economics, 10(01). https://doi.org/10.1142/S2010495215500025. Dyhrberg, A. H. (2016). “Hedging Capabilities Of Bitcoin. Is İt The Virtual Gold?” Finance Research Letters, 16: 139-144.Engle, R. F. (1982). “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation”. Econometrica: Journal of the Econometric Society. 50(4): 987-1007.Engle, R. F., Lilien, D. M., & Robins, R. P. (1987). “Estimating Time Varying Risk Premia İn The Term Structure: The ARCH-M Model”. Econometrica: Journal of the Econometric Society, 55(2): 391-407.Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). “Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions”. SSRN Working Paper. https://ssrn.com/abstract=2425247.Gujarati, D. N. (1999). Temel Ekonometri, (Çev. Ümit Şenesen – Gülay Göktürk Şenesen) İstanbul: Literatür Yayınları.Guvenek, B., & Alptekin, V. (2009). “Reel Döviz Kuru Endeksinin Otoregresif Koşullu Değişen Varyanslılığının Analizi: İki Eşikli Tarch Yöntemi İle Modellenmesi”. Maliye Dergisi, 156: 294-309.Katsiampa, P. (2017). “Volatility Estimation for Bitcoin: A Comparison of GARCH Models”. Economics Letters, 158: 3-6.McKinnon, R. I. (1991). “Financial Control İn The Transition From Classical Socialism To A Market Economy”. Journal of Economic Perspectives, 5(4): 107-122.Nakamoto, S. (2008). “Bitcoin: A Peer-to-Peer Electronic Cash System”. https://bitcoin.org/bitcoin.pdf. Nelson, D. B. (1991). “Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica”. Journal of the Econometric Society. 59(2): 347-370.Özer. A. & Ece, O. (2016). “Vadeli İşlem Piyasalarında Anomalilerin Archgarch Modelleri İle Test Edilmesi: Türkiye Vadeli İşlemler Piyasası Üzerine Bir Uygulama”. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 6(2): 1-14. Şahin, E . (2018).” Crypto Money Bitcoin: Price Estimation With ARIMA andArtificial Neural Networks”. Fiscaoeconomia, 2 (2), 74-92.DOI: 10.25295/fsecon.2018.02.005. Tully, E., & Lucey, B. M. (2007). “A Power GARCH Examination of The Gold Market”. Research in International Business and Finance, 21(2): 316-325.Usta A. ve Dogantekin S. (2017). Blockchain 101, 1. Baskı, İstanbul, İnkilap Kitapevi. Vigna P. Ve Casey J. (2015). Kripto Para Çağı,(Çev. Ali ATAV) , 2. Baskı, Buzdağı Yayın Evi. Zakoian, J. M. (1994). “Threshold Heteroskedastic Models”. Journal Of Economic Dynamics And Control. 18(5): 931-955.
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Details

Primary Language Turkish
Subjects Business Administration
Journal Section Articles
Authors

Eyyüp Ensari Şahin

Oktay Özkan

Publication Date December 31, 2018
Submission Date August 1, 2018
Acceptance Date November 26, 2018
Published in Issue Year 2018 Volume: 3 Issue: 2

Cite

APA Şahin, E. E., & Özkan, O. (2018). Asimetrik Volatilitenin Tahmini: Kripto Para Bitcoin Uygulaması. Bilecik Şeyh Edebali Üniversitesi Sosyal Bilimler Dergisi, 3(2), 240-247. https://doi.org/10.33905/bseusbed.450018

Cited By

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Anadolu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
https://doi.org/10.53443/anadoluibfd.1209648






Kriptopara Getirilerinin Piyasa Risklerinin Karşılaştırılması
Bingöl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
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