Bitcoin’in Fiyat Oynaklığının Otoregressif Koşullu Değişen Varyans Modellemeleri ile Belirlenmesi

Yıl 2021, , 290 - 309, 10.05.2021

İbrahim Sezer Belliler , Zerife Yildirim

https://doi.org/10.20990/kilisiibfakademik.731233

Öz

Amaç: Bu araştırmanın amacı, ilk çıkış yılı olan 2009’dan günümüze finansal piyasalarda yeni bir fenomen haline gelen, sanal para veya kripto para olarak tanımlanabilen bitcoinin, finansal bir yatırım aracı olarak görülmesi yönündeki fiyat hareketlerinin analiz edilmesidir. Tasarım/Yöntem: Çalışmada, Otoregresif Koşullu Değişen Varyans modellemeleri ile oynaklık, getiri davranışı ve finansal bir yatırım aracı olarak güvenilirliği incelenmektedir. Bu kapsamda simetrik ve asimetrik etkili ARCH modellemeleri kullanılmıştır. Bulgular: Analizler sonucunda; simetrik ve asimetrik etkili ARCH modellemeleri ile incelenen bitcoin getiri serisi için ilk dönemde asimetrik etkiye sahip olduğu bulunmuştur. Ayrıca half-life ölçütüne göre bitcoin getiri serisinde meydana gelen şoklar her dönemde 30 günden daha fazla oynaklık kalıcılığı etkisine maruz kaldığı tespit edilmiştir. Dönemler itibariyle incelenen bitcoinin ilk yıllarında daha yüksek oynaklığa sahip olduğu tespit edilmiştir. Sınırlılıklar: Günümüzde finansal piyasalarda yeni bir fenomen haline gelen, sanal para veya kripto para olarak tanımlanabilen bitcoinin oynaklığı analiz edilmiştir. Özgünlük/Değer: Aslında piyasada ticareti yapılan çok sayıda sanal para veya diğer adıyla kripto para bulunmaktadır. Ancak birçok sanal para biriminin arasında en çok bilineni ve piyasa hacmi en fazla olanı olarak bitcoin karşımıza çıkmaktadır. Finansal bir yatırım aracı olarak görülmeye başlanan bitcoin’in fiyat hareketlerinin analiz edilmesi güvenilirlik çerçevesinde büyük öneme sahiptir. Bu yönden yapılan inceleme araştırmanın özgün değerini oluşturmaktadır.

Anahtar Kelimeler

Bitcoin, Kriptopara, Oynaklık, Simetrik ve Asimetrik ARCH Modelleri

Determination Price Volatility of Bitcoin with Autoregressive Conditional Heteroscedasticiy Models

Öz

Purpose: The purpose of this research is to analyze the price movements of bitcoin, which has become a new phenomenon in financial markets since 2009, the first year of its release, and can be defined as virtual money or crypto money, to be seen as a financial investment tool. Design/Methodology: In the study, volatility, return behavior and reliability as a financial investment tool are examined with autoregressive Conditional Variable Variance modeling. In this context, symmetrical and asymmetrical ARCH models were used. Findings: As a result of the analysis; it has been found that it has an asymmetric effect in the first period for the bitcoin return series examined with symmetric and asymmetric ARCH models. In addition, it has been determined that shocks occurring in the bitcoin return series according to the half-life criteria are exposed to the volatility effect for more than 30 days in each period. It has been determined that bitcoin, which is examined by periods, has higher volatility in its first years. Limitations: The volatility of bitcoin, which has become a new phenomenon in financial markets today, can be defined as virtual money or crypto money, has been analyzed. Originality/Value: In fact, there are many virtual currencies or cryptocurrencies traded in the market. However, among many virtual currencies, bitcoin is the most known and the most market volume. Analyzing the price movements of bitcoin, which has started to be seen as a financial investment tool, is of great importance in the framework of reliability. The examination made in this respect constitutes the original value of the research.

Anahtar Kelimeler

Bitcoin, Cryptocurrency, Volatility, Symmetric and Asymmetric ARCH Models

Kaynakça

• Atik, M., Köse, Y., Yılmaz, B., & Sağlam, F. (2015). Kripto para: Bitcoin ve döviz kurları üzerine etkileri. Bartın Üniversity İİBF Journal, 6(11), 247-262. http://abs.kafkas.edu.tr/upload/357/11_sayi_bartin_univ__iibf_dergisi.pdf
• Baur, D. G., Dimpfl, T., & Kuck, K. (2018). Bitcoin, gold and the US dollar-A replication and extension. Finance Research Letters, 25, 103-110. https://doi.org/10.1016/j.frl.2017.10.012
• Baur, D. G., Hong, Ki-H., & Lee, A. D. (2017). Bitcoin: Medium of exchange or speculative assets?. Journal of International Financial Markets. Institutions and Money, 54, 177-189. https://www.sciencedirect.com/science/article/abs/pii/S1042443117300720?casa_token=OhBXjgoI7uEAAAAA:xzpqdhhW0WdtCoeenG60g9axO6SA2geaDKfzQsxQV0EhfkEx_Buq-4CDoRzkDJNyOkOerpn
• Bera, A. K., & Higgins, M. L. (1993). ARCH models: Properties, estimation and testing. Journal of Economic Surveys, 7(4), 305-366. https://www.onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-6419.1993.tb00170.x
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. https://www.sciencedirect.com/science/article/abs/pii/0304407686900631
• Bouri, E., Azzi, G., & Dyhrberg, A. H. (2016). On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics Discussion Papers, (41), https://ideas.repec.org/p/zbw/ifwedp/201641.html
• Brooks, C. (2014). Introductory econometrics for finance. Cambridge University Press. https://www.scirp.org/reference/ReferencesPapers.aspx?ReferenceID=2271775
• Chaim, P., & Laurini, M. P. (2018). Volatility and return jumpsin bitcoin. Economics Letters, 173, 158-163. https://doi.org/10.1016/j.econlet.2018.10.011
• Christopher, C. M. (2013). Whack-A-Mole: Why prosecuting digital currency exchanges won’t stop online money laundering. Social Science Research Network, http://ssrn.com/abstract=2312787
• Coindesk. (2018). Bitcoin price. https://www.coindesk.com/price/bitcoin
• Cutcu, I., & Kılıc, Y. (2018). Döviz kurları ile Bitcoin fiyatları arasındaki ilişki: Yapısal kırılmalı zaman serisi analizi. Yönetim ve Ekonomi Araştırmaları Dergisi, 16(4), 349-366. https://doi.org/10.11611/yead.474993
• DeMartino, I. (2018). The bitcoin guidebook: How to obtain, invest and spend the world?, First decentralized cryptocurrency. New York; Skyhorse Publishing. (Revised Ed.). https://www.torontopubliclibrary.ca/detail.jsp?R=3371138
• Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar-A GARCH volatility analysis. Finance Research Letters, 16, 85-92. https://www.sciencedirect.com/science/article/abs/pii/S1544612315001038
• Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007. https://ideas.repec.org/a/ecm/emetrp/v50y1982i4p987-1007.html
• Gemici, E., & Polat, M. (2019). Relationship between price and volume in the Bitcoin market, Journal of Risk Finance, Emerald Group Publishing, 20(5), 435-444. https://ideas.repec.org/a/eme/jrfpps/jrf-07-2018-0111.html
• Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M., & Siering, M. (2014). Bitcoin-asset or currency?. Revealing Users' Hidden Intentions. https://www.scirp.org/reference/ReferencesPapers.aspx?ReferenceID=2313124
• Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economic Letters, 158, 3-6. https://econpapers.repec.org/article/eeeecolet/v_3a158_3ay_3a2017_3ai_3ac_3ap_3a3-6.htm
• Katsiampa, P., Corbet, S., & Lucey, B. (2019). Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis. Finance Research Letters, 29, https://doi.org/10.1016/j.frl.2019.03.009
• Kocoglu, Ş., Çevik, Y. E., & Tanrıöven, C. (2016). Bitcoin piyasalarının etkinliği, likiditesi ve oynaklığı. Journal of Business Studies, 8(2), 77-97. https://doi.org/10.20491/isarder.2016.170
• Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. http://bitcoin.org/bitcoin.pdf
• Quandll. (2018). Euro-Dollar. https://www.quandl.com/data/ECB/EURUSD-EUR-vs-USD-Foreign-Exchange-Reference-Rate
• Rodrigue, J. P. (2011). Factors impacting North American freight distribution in view of the Panama canal expansion. Horne Institut Van, http://people.hofstra.edu/jeanpaul_rodrigue/downloads/Panama%20Canal%20Study%202011%20Final.pdf
• Szetela, B., Mentel G., & Gedek S. (2016). Dependency analysis between Bitcoin and selected global currencies. Dynamic Econometric Models, 16, 133-144. https://ideas.repec.org/a/cpn/umkdem/v16y2016p133-144.html
• Topaloglu, E. E. (2020). Borsa İstanbul pay endekslerinin volatilite yapısı ve volatilite yayılımı: GARCH ve MGARCH modelleri ile BIST sınai ve mali endeksleri örneği. dergipark.org.tr/tr/pub/dpusbe/issue/51845/568128
• Tsay, R. S. (2010). Analysis of financial time series. John Wiley & Sons, Inc. https://www.scirp.org/(S(oyulxb452alnt1aej1nfow45))/reference/referencespapers.aspx?referenceid=2848858
• Yermarck, D. (2013). Is bitcoin a real currency? An economic appraisal, NBER Working Paper Series, Working Paper 19747, National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w19747/w19747.pdf