Blockchain Analiz Göstergelerinin Bitcoin Fiyatı Üzerindeki Etkisi
Bitcoin, pek çok kullanıcıyı kendine çekmeyi başaran, Blockchain piyasasında en çok ilgi gören ilk başarılı kripto para birimi konumundadır. Bitcoin fiyatının aşırı oynak yapısı, araştırmacıları Bitcoin fiyat hareketlerini incelemeye sevk etmiş ve bu konuda oldukça fazla çalışmanın yapılmasını sağlamıştır. Bu tez, Bitcoin fiyatını belirleyen bazı değişkenler kullanılarak Bitcoin fiyat hareketlerinin yönünü anlamaya dönük analizler içermektedir. Çalışmanın analiz dönemi için Ocak 2012 – Aralık 2021 tarihlerini kapsayan her ayın son gününe ait verilerden oluşan zaman serileri kullanılmıştır. Bitcoin fiyatı bağımlı değişken; Harcanan Çıktı Kâr Oranı (SOPR), Madenci Kârlılığı (PM), Bitcoin Aktif Adres (BAA), Google Trendler (GT) ve Dow Jones Borsası Endüstri Endeksi (DJIA) bağımsız değişkenler olarak seçilmiştir. Çalışmanın değişkenlerinin ilk önce durağanlık seviyeleri tespit edilmiş, ardından ARDL Sınır Testi ve Toda-Yamamoto Nedensellik Testi uygulanarak analiz sonuçlarına ulaşılmıştır. Elde edilen ARDL (3,0,3,0,0,0) modelinin kısa ve uzun dönem bulgularına göre: Kısa dönemde Blockchain ağına özgü göstergelerden SOPR, PM ve BAA değişkenleri Bitcoin fiyatını anlamlı olarak pozitif etkilediği tespit edilmiştir. lnDJIA ve GT değişkenleri ile Bitcoin fiyatı arasında anlamlı bir ilişki bulunmamıştır. Uzun dönemde ise SOPR, PM, lnDJIA ve BAA anlamlı ve pozitif yönde Bitcoin fiyatı ile ilişkili iken GT ile anlamlı bir ilişkinin varlığı tespit edilmemiştir. Toda-Yamamoto test sonuçlarına göre ise Bitcoin Fiyatı ile SOPR değişkeni arasında çift yönlü, BAA değişkeni arasında tek yönlü Granger nedensellik ilişkisi bulunmuştur.
The Effect of Blockchain Analysis Indicators on Bitcoin Price
Bitcoin is the first successful cryptocurrency that has attracted the most attention in the Blockchain market, which has managed to attract many users. The extremely volatile nature of the Bitcoin price has prompted researchers to study Bitcoin price movements and has enabled a lot of work to be done on this issue. In this thesis, it contains analyzes aimed at understanding the direction of Bitcoin price movements using some variables that determine the Bitcoin price. January December 2021 – January 2012 For the analysis period of the study, time series consisting of the data of the last day of each month covering the dates were used. Bitcoin price, dependent variable; Spent Output Profit Ratio (SOPR), Miner Profitability (PM), Bitcoin Active Address (BAA), Google Trends (GT) and Dow Jones Stock Exchange Industry Index (DJIA) were selected as independent variables. The stationarity levels of the variables of the study were determined first, then the ARDL Boundary Test and Toda-Yamamoto Causality Test were applied to reach the results of the analysis. According to the short and long-term findings of the ARDL (3,0,3,0,0,0) model obtained: In the short term, SOPR, PM and BAA variables, which are specific to the Blockchain network, have been found to have a significant positive effect on the Bitcoin price. There was no significant relationship between lnDJIA and GT variables and Bitcoin price. In the long term, while SOPR, PM, lnDJIA and BAA were significantly and positively associated with Bitcoin price, no significant relationship was found with GT. According to the Toda-Yamamoto test results, a two-way Granger causality relationship was found between the Bitcoin Price and the SOPR variable, and a one-way Granger causality relationship between the BAA variable.
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- Aggarwal, D., Chandrasekaran, S., & Annamalai, B. (2020). A complete empirical ensemble mode decomposition and support vector machine-based approach to predict Bitcoin prices. Journal of Behavioral and Experimental Finance, 27, 1-12. doi:https://doi.org/10.1016/j.jbef.2020.100335
- Ahn, Y., & Kim, D. (2020). Sentiment disagreement and bitcoin price fluctuations: a psycholinguistic. APPLIED ECONOMICS LETTERS, 27(5), 412-416. doi:https://doi.org/10.1080/13504851.2019.1619013
- Ali, M., & Shatabda, S. (2020). A Data Selection Methodology to Train Linear Regression Model to Predict Bitcoin Price. 2020 2nd International Conference on Advanced Information and Communication Technology (s. 330-335). Dhaka: Institute of Electrical and Electronics Engineers. doi:https://doi.org/10.1109/ICAICT51780.2020.9333525
- Allen, F., Gu, X., & Jagtiani, J. (2022). Fintech, Cryptocurrencies, and CBDC: Financial Structural Transformation in China. Journal of International Money and Finance, 124, 1-13. doi:https://doi.org/10.1016/j.jimonfin.2022.102625
- Anderson, R. J. (1996). The Eternity Service. Cambridge Üniversitesi Bilgisayar Laboratuvarı, 1-11. Şubat 12, 2022 tarihinde http://www.cl.cam.ac.uk/~rja14/Papers/eternity.pdf adresinden alındı
- Arslan, U. (2020). The Relationship Between Bitcoin Returns and Google Trend: Country Level Evidence. İstanbul: Istanbul Bilgi University Institute Of Social Science, Yayınlanmamış Yüksek Lisans Tezi. https://tez.yok.gov.tr/UlusalTezMerkezi/TezGoster?key=Eb5EkakJlp3olBdo_wNEGb-bm0pZn-pVTvJ6guekKxlMpgu_ODMZv0oMNHwjz9Wd adresinden alındı
- Ata, B. (2019). Google Trends Verileri ile Kripto Para İlişkisi: Bitcoin Örneği. Burdur: Burdur Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü, Yayınlanmamış Yüksek Lisans Tezi. https://tez.yok.gov.tr/UlusalTezMerkezi/TezGoster?key=Mir2lXQK1dkmQ9Ige3PZbiGfLkttDByCZzyRixRxwI086ZwxUGzF4YERR3S0nZDn adresinden alındı
- Bayer, D., Haber, S., & Stornetta, W. S. (1992). Improving the Efficiency and Reliability of Digital Time-Stamping. Methods in Communication, Security, and Computer Science, 329-334. Şubat 17, 2022 tarihinde http://www.math.columbia.edu/~bayer/papers/Timestamp_BHS93.pdf adresinden alındı
- BtcTürk. (2020, Mayıs 1). Bilgi Platformu: BtcTürk. Ocak 18, 2022 tarihinde BtcTürk Web Sitesi: https://www.btcturk.com/bilgi-platformu/bitcoin-tarihi/ adresinden alındı
- Chen, Y. (. (2021). Empirical Analysis of Bitcoin Price. Journal of Economics and Finance, 692-715. doi:https://doi.org/10.1007/s12197-021-09549-5
- Cheng, P. (2022). Decoding the rise of Central Bank Digital Currency in China: designs, problems, and prospects. Journal of Banking Regulation, 1-15. doi:https://doi.org/10.1057/s41261-022-00193-5
- Chkili, W. (2021). Modeling Bitcoin price volatility: long memory vs Markov switching. Eurasian Economic Review: A Journal in Applied Macroeconomics and Finance, 11(3), 433-448. doi:https://doi.org/10.1007/s40822-021-00180-7
- Coinmarketcap. (2021, Aralık 1). Coinmarketcap. Aralık 2, 2021 tarihinde Coinmarketcap Web Sitesi: https://coinmarketcap.com/ adresinden alındı
- Crosby, M. (2016). BlockChain Technology: Beyond Bitcoin. Applied Innovation Review, 6-19. Şubat 25, 2022 tarihinde http://scet.berkeley.edu/wp-content/uploads/AIR-2016-Blockchain.pdf adresinden alındı
- Cryptoquant. (2019-2022, Şubat 18). CryptoQuant. Ocak 4, 2022 tarihinde Cryptoquant Web Sitesi: https://cryptoquant.com/asset/btc/chart/market-indicator/spent-output-profit-ratio-sopr?window=DAY&sma=0&ema=0&priceScale=linear&metricScale=log&chartStyle=line adresinden alındı
- CryptoQuant. (2022, Ocak 1). CryptoQuant. CryptoQuant Web Sitesi: https://cryptoquant.com/privacy-policy adresinden alındı
Demertzis, M., Merler, S., & Wolff, G. B. (2018). Capital Markets Union and the Fintech Opportunity. Journal of Financial Regulation, 4(1), 157-165. doi:https://doi.org/10.1093/jfr/fjx012
- Dev, J. A. (2014). Bitcoin Mining Acceleration and Performance. 2014 IEEE 27. Kanada Elektrik ve Bilgisayar Mühendisliği Konferansı (CCECE) (s. 1-6). Toronto: IEEE. doi:https://doi.org/10.1109/CCECE.2014.6900989
- Dirican, C., & Canoz, İ. (2017). THE COINTEGRATION RELATIONSHIP BETWEEN BITCOIN PRICES AND MAJOR WORLD STOCK INDICES: AN ANALYSIS WITH ARDL MODEL APPROACH. ournal of Economics, Finance and Accounting (JEFA), 4(4), 377-392. doi:http://doi.org/10.17261/Pressacademia.2017.748
- Edgari, E., Thiojaya, J., & Qomariyah, N. N. (2022). The Impact of Twitter Sentiment Analysis on Bitcoin Price during COVID-19 with XGBoost. 2022 5th International Conference on Computing and Informatics (ICCI) (s. 337-342). New Cairo: Institute of Electrical and Electronics Engineers (IEEE). doi:https://doi.org/10.1109/ICCI54321.2022.9756123
- Finans, G. (1998-2022, Eylül 4). Google Finans. Ocak 9, 2022 tarihinde Google Web Sayfası: https://www.google.com/finance/quote/.DJI:INDEXDJX?sa=X&ved=2ahUKEwjBlZqaz7b2AhVOOs0KHQ85CMoQ3ecFegQIHRAc&window=MAX adresinden alındı
- Finney, H. (2004, Ağustos 15). RPOW - Reusable Proofs of Work. Satoshi Nakamoto Institute, 1-3. Şubat 19, 2022 tarihinde https://nakamotoinstitute.org/rpow/ adresinden alındı
- Gemici, E., & Polat, M. (2019). Relationship between price and volume in the Bitcoin market. The Journal of Risk Finance, 20(5), 435-444. Şubat 25, 2022 tarihinde https://www.emerald.com/insight/content/doi/10.1108/JRF-07-2018-0111/full/pdf?title=relationship-between-price-and-volume-in-the-bitcoin-market adresinden alındı
- Glassnode. (2019-2022, Şubat 18). Glassnode Studio. Ocak 6, 2022 tarihinde Glassnode Web Sitesi: https://studio.glassnode.com/metrics?a=BTC&category=&m=indicators.PuellMultiple adresinden alındı
- Glassnode. (2022, Ocak 3). Bitcoin: Number of Active Addresses. Ocak 16, 2022 tarihinde Glassnode Web Sitesi: https://studio.glassnode.com/metrics?a=BTC&category=Addresses&m=addresses.ActiveCount adresinden alındı
- Glassnode. (2022, Ocak 1). Glassnode. Glassnode Web Sitesi: https://glassnode.com/company adresinden alındı
- Gomber, P., Koch, J.-A., & Siering, M. (2017). Digital Finance and FinTech: current research and future research directions. Journal of Business Economics, 87, 537-580. doi:https://doi.org/10.1007/s11573-017-0852-x
- Gronwald, M. (2019). Is Bitcoin a Commodity? On price jumps, demand shocks, and certainty of supply. Journal of International Money and Finance, 86-92. doi:https://doi.org/10.1016/j.jimonfin.2019.06.006
- Guégan, D., & Renault, T. (2021). Does investor sentiment on social media provide robust information for Bitcoin returns predictability? Finance Research Letters, 38, 1-7. doi:https://doi.org/10.1016/j.frl.2020.101494
- Guizani, S., & Nafti, I. K. (2019). The Determinants of Bitcoin Price Volatility: An Investigation With ARDL Model. Procedia Computer Science, 164, 233-238. doi:https://doi.org/10.1016/j.procs.2019.12.177
- Gülcü, Y., & Kıtkıt, M. A. (2022). BITCOİN FİYATLARI İLE BORSA İSTANBUL 100 ENDEKSİ NEDENSELLİK VE EŞ BÜTÜNLEŞME İLİŞKİSİ. Fırat Üniversitesi Sosyal Bilimler Dergisi, 32(2), 615-624. doi:https://doi.org/10.18069/firatsbed.1032053
- Güler, D. (2021). The Impact of Investor Sentiment on Bitcoin Returns and Conditional Volatilities during the Era of Covid-19. Journal of Behavioral Finance, 1-14. doi:https://doi.org/10.1080/15427560.2021.1975285
- Haber, S., & Stornetta, W. S. (1991). How to Time-stamp a Digital Document. Journal of Cryptology, 3(2), 99-111. Mart 1, 2022 tarihinde https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.46.8740&rep=rep1&type=pdf adresinden alındı
- Investing. (2007-2022, Ocak 1). Fusion Media Limited. Ocak 3, 2022 tarihinde Investing Web Sitesi: https://tr.investing.com/crypto/bitcoin/historical-data adresinden alındı
- Kakinuma, Y. (2021). Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic. Journal of Asia Business Studies, 16(4), 693-711. 2022 tarihinde https://www.emerald.com/insight/content/doi/10.1108/JABS-02-2021-0050/full/pdf?title=nexus-between-southeast-asian-stock-markets-bitcoin-and-gold-spillover-effect-before-and-during-the-covid-19-pandemic adresinden alındı
- Kalyvas, A., Papakyriakou, P., Sakkas, A., & Urquhart, A. (2020). What drives Bitcoin’s price crash risk? Economics Letters, 191, 1-4. doi:https://doi.org/10.1016/j.econlet.2019.108777
- Kaya, U., Akba, F., Medeni, İ. T., & Medeni, T. D. (2020). Covid-19 Öncesi ve Sonrasındaki Bitcoin Fiyat Değişimlerinin Makine Öğrenmesi, Zaman Serileri Analizi ve Derin Öğrenme Yöntemleriyle Değerlendirilmesi. International Journal of InformaticsTechnologies, 13(3), 341-355. doi:https://doi.org/10.17671/gazibtd.648424
- Lin, H.-J., Chen, C.-C., Chiu, Y.-h., & Lin, T.-Y. (2021, Nisan 5). How financial technology (fintech) can improve the business performance of securities firms by using the dynamic data envelopment analysis modified model. Managerial and Decision Economics, 1-20. doi:https://doi.org/10.1002/mde.3443
- Mattila, J. (2016, Mayıs 10). The Blockchain Phenomenon – The Disruptive Potential of Distributed Consensus Architectures. ETLA Working Papers, 6-7. Şubat 11, 2022 tarihinde http://pub.etla.fi/ETLA-Working-Papers-38.pdf adresinden alındı
- Millera, N., Yanga, Y., Sunb, B., & Zhang, G. (2019). Identification of Technical Analysis Patterns with Smoothing Splines for Bitcoin Prices. Journal of Applied Statistics, 46(12), 2289-2297. doi:https://doi.org/10.1080/02664763.2019.1580251
- Mittal, A., Dhiman, V., Singh, A., & Prakash, C. (2019). Short-Term Bitcoin Price Fluctuation Prediction Using Social Media and Web Search Data. Twelfth International Conference on Contemporary Computing (s. 1-16). Delhi: Department of Information Technology Indira Gandhi Delhi Technical University for Women. doi:https://doi.org/10.1109/IC3.2019.8844899
- Nakamoto, S. (2008, Ocak 3). Bitcoin: A Peer-to-Peer Electronic Cash System. Şubat 10, 2022 tarihinde Bitcoin.org Web Sitesi: https://bitcoin.org/en/bitcoin-paper adresinden alındı
- Nguyen, K. Q. (2022). The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods. Finance Research Letters, 46(A), 1-5. doi:https://doi.org/10.1016/j.frl.2021.102284
- Özsoy, Ç. Y. (2019). Yükselen teknoloji ürünü bıtcoın'in arz – talep ve fiyat hareketlerinin markov rejim değişim hata düzeltme modeli ile incelenmesi. Ankara: Ulusal Tez Merkezi. Nisan 5, 2022 tarihinde https://tez.yok.gov.tr/UlusalTezMerkezi/TezGoster?key=aEzj_IdWAsjiSAfK3qwrBiEOw2U_dPHlxAeyP1iB8xU3EJAdPWSzkfPr8If3algZ adresinden alındı
- Pavlidis, G. (2021). Europe in the digital age: regulating digital finance without suffocating innovation. Law, Innovation & Technology, 13(2), 464-477. doi:https://doi.org/10.1080/17579961.2021.1977222
- Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. doi:https://doi.org/10.1002/jae.616
- Philippasa, D., Rjiba, H., Guesmi, K., & Goutte, S. (2019). Media attention and Bitcoin prices. Finance Research Letters, 30, 37-43. doi:https://doi.org/10.1016/j.frl.2019.03.031
- Polat, M., & Tuncel, F. B. (2020). Borsa İstanbul ve Kripto Paralar Arasında Saklı Eşbütünleşme İlişkisi. Finans Politik & Ekonomik Yorumlar, 57(654), 119-137. 2022 tarihinde https://eds.p.ebscohost.com/eds/pdfviewer/pdfviewer?vid=2&sid=3f4eef01-dade-49fb-a7c7-d62efc760fb0%40redis adresinden alındı
- Puell, D. (2019, Nisan 5). A New Barometer of Bitcoin’s Market Cycles. Medium Web Sitesi: https://medium.com/unconfiscatable/the-puell-multiple-bed755cfe358 adresinden alındı
- Samirkas, M. C. (2020). Google Aramaları ile Bitcoin Fiyatı Arasındaki İlişkinin Tespiti. PressAcademia Procedia, 11(1), 67-72. doi:https://doi.org/10.17261/Pressacademia.2020.1242
- Schneier, B., & Kelsey, J. (1998). Cryptographic Support for Secure Logs on Untrusted Machines. Proceedings of the 7th USENIX Security Symposium (s. 1-11). Texas: USENIX Association. Şubat 13, 2022 tarihinde http://usenix.org/publications/library/proceedings/sec98/full_papers/schneier/schneier.pdf adresinden alındı
- Shirakashi, R. (2022, Ocak 3). Glassnode Academy. Glassnode Web Sitesi: https://academy.glassnode.com/indicators/sopr/sopr-spent-output-profit-ratio adresinden alındı
- Szabo, N. (2005, Aralık 29). Bit Gold. Şubat 16, 2022 tarihinde Unenumerated Web Sitesi: http://unenumerated.blogspot.com/2005/12/bit-gold.html adresinden alındı
- Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. doi:https://doi.org/10.1016/0304-4076(94)01616-8
- Trends, G. (2022, Ocak 5). Google Trends. Google Web Sayfası: https://trends.google.com.tr/trends/explore?date=2012-01-01%202021-12-31&q=%2Fm%2F05p0rrx adresinden alındı
- Tuncel, M. B., & Gürsoy, S. (2020). KORKU ENDEKSİ (VIX), BITCOIN FİYATLARI VE BİST100 ENDEKSİ ARASINDAKİ NEDENSELLİK İLİŞKİSİ ÜZERİNE AMPİRİK BİR UYGULAMA. Electronic Journal of Social Sciences, 19(76), 1999-2011. Aralık 24, 2021 tarihinde https://eds.s.ebscohost.com/eds/Citations/FullTextLinkClick?sid=c7f03ff9-87cd-4ea7-9bfb-792b1787bc15@redis&vid=1&id=pdfFullText adresinden alındı
- Ullah, S., Attah-Boakye, R., Adams, K., & Zaefarian, G. (2021). Assessing the influence of celebrity and government endorsements on bitcoin’s price volatility. Journal of Business Research, 228-239. doi:https://doi.org/10.1016/j.jbusres.2022.01.055
- Vo, A., Chapman, T. A., & Lee, Y.-S. (2021). Examining Bitcoin and Economic Determinants: An Evolutionary Perspective. Journal of Computer Information Systems, 1-15. doi:https://doi.org/10.1080/08874417.2020.1865851
- Xin, W. (2021). Application of Blockchain Technology and Cloud Computing in Digital Finance. 2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) (s. 759-764). Shenyang: Institute of Electrical and Electronics Engineers. doi:https://doi.org/10.1109/TOCS53301.2021.9688853
- Yıldırım, Ç. (2020). GOOGLE TRENDS "BİTCOİN" ARAMALARI İLE BİTCOİN/USD FİYATLARI ARASINDAKİ İLİŞKİNİN ANALİZİ: ARDL SINIR TESTİ. Journal of Knowlede Economy and Knowledge Management, 15(2), 99-113. Mart 8, 2022 tarihinde https://dergipark.org.tr/en/download/article-file/1186981 adresinden alındı
- Zheng, Z., Xie, S., Dai, H.-N., Chen, X., & Wang, H. (2018, Ekim 17). Blockchain challenges and opportunities: A survey. International Journal of Web and Grid Services, 14(4), 352-375. doi:http://dx.doi.org/10.1504/IJWGS.2018.095647