FED Politika Faiz Oranları ve Bitcoin Fiyatlarının Analizi: COVID-19 Öncesi ve Sonrası Farklılıkları

Yıl 2024, Erken Görünüm, 83 - 103

Osman Altay

https://doi.org/10.30626/tesamakademi.1447997

Öz

Bu çalışma, Federal Rezerve tarafından açıklanan politika faiz oranları ile Bitcoin fiyatları arasındaki ilişkiyi COVID-19 öncesi ve sonrası dönemleri dikkate alarak karşılaştırmalı bir analiz yapmayı amaçlamaktadır. Vektör Hata Düzeltme Modeline dayalı sağlam bir analitik çerçevenin kullanılması ve her aşamanın ayrı ayrı incelenmesi sonucunda elde edilen bulgulara göre; COVID-19 öncesi dönemde Bitcoin değişkeni için ECM katsayısının -0,03 olması yaklaşık 33 hafta sonra şok stabilizasyona işaret ederken, COVID-19 sonrası dönemde Bitcoin için önemli bir -0,08 ECM katsayısı ortaya çıkıyor ve bu da şokun yaklaşık 12,5 hafta içinde çok daha kısa bir dönemde dengeye döneceğine işaret ediyor. Ayrıca FED Politika Faizinin -0,13 ECM katsayısı ile dikkat çekici bir değere ulaşması COVID-19 sonrası dönemde şokların yaklaşık 7,7 hafta içinde istikrara kavuşmaya başladığına işaret ediyor. Bu bulgular, COVID-19 dönemi koşullarının da etkisiyle Bitcoin ve kripto para birimlerinin geleneksel yatırım araçları olarak giderek daha fazla kabul edildiğini gösteriyor.

Anahtar Kelimeler

Bitcoin, Kiripto Paralar, Faiz Oranı, FED Politika Faizi

Analysis of Federal Reserve Policy Rates and Bitcoin Prices: Pre and Post COVID-19 Differentiations

Öz

This study aims to conduct a comparative analysis of the relationship between policy interest rates declared by the Federal Reserve and Bitcoin prices, taking into account both pre and post-COVID-19 periods. Employing a robust analytical framework based on Vector Error Correction Model, scrutinizing each phase individually. In the pre-COVID-19 period, a notable VECM coefficient of -0.03 for Bitcoin variable implies shock stabilization after approximately 33 weeks, while the FED Policy Rate variable lacks significance in the return-to-balance mechanism. Conversely, the post-COVID-19 period unveils a substantial -0.08 VECM coefficient for Bitcoin, signaling a shock returning to balance in around 12.5 weeks. Furthermore, the FED Policy Rate exhibits a noteworthy -0.13 VECM coefficient, indicating shock stabilization after about 7.7 weeks. These findings suggest a growing acceptance of Bitcoin and cryptocurrencies as conventional investment tools, propelled by the circumstances of the COVID-19 period.

Anahtar Kelimeler

Cryptocurrencies, Bitcoin, Interest Rate, Federal Reserve Policy Rate

Kaynakça

• Adcock, R., & Gradojevic, N. (2019). Non-fundamental, non-parametric Bitcoin forecasting. Physica A: Statistical Mechanics and Its Applications, 531. https://doi.org/10.1016/j.physa.2019.121727
• Almeida, J., & Gonçalves, T. C. (2023). Portfolio Diversification, Hedge and Safe-Haven Proper-ties in Cryptocurrency Investments and Financial Economics: A Systematic Literature Review. In Journal of Risk and Financial Management (Vol. 16, Issue 1). https://doi.org/10.3390/jrfm16010003
• Alp, E. A., Sefil, S., & Sak, A. K. (2015). The impact of education level and gender on job search duration in Turkey. Kuram ve Uygulamada Egitim Bilimleri, 15(2). https://doi.org/10.12738/estp.2015.2.2355
• Bagus, P., & Schiml, M. H. (2010). A cardiograph of the dollar’s quality: Qualitative easing and the federal reserve balance sheet during the subprime crisis. Prague Economic Papers, 3. https://doi.org/10.18267/j.pep.372
• Basher, S. A., & Sadorsky, P. (2022). Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility? Machine Learning with Appli-cations, 9, 100355. https://doi.org/10.1016/j.mlwa.2022.100355
• Basistha, A., & Kurov, A. (2008). Macroeconomic cycles and the stock market’s reaction to monetary policy. Journal of Banking & Finance, 32(12), 2606–2616. https://doi.org/10.1016/j.jbankfin.2008.05.012
• Baur, D. G., Dimpfl, T., & Kuck, K. (2018). Bitcoin, gold and the US dollar – A replication and ex-tension. Finance Research Letters, 25. https://doi.org/10.1016/j.frl.2017.10.012
• Berument, H., & Ceylan, N. B. (2008). US Monetary Policy Surprises and Foreign Interest Rates: Evidence from a Set of MENA Countries. Review of Middle East Economics and Finance, 4(2). https://doi.org/10.2202/1475-3693.1065
• Bouazizi, T., Galariotis, E., Guesmi, K., & Makrychoriti, P. (2023). Investigating the nature of interaction between crypto-currency and commodity markets. International Review of Finan-cial Analysis, 88. https://doi.org/10.1016/j.irfa.2023.102690
• Corbet, S., McHugh, G., & Meegan, A. (2017a). The influence of central bank monetary policy announcements on cryptocurrency return volatility. Investment Management and Financial Innovations, 14(4), 60–72. https://doi.org/10.21511/imfi.14(4).2017.07
• Corbet, S., McHugh, G., & Meegan, A. (2017b). The influence of central bank monetary policy announcements on cryptocurrency return volatility. Investment Management and Financial Innovations, 14(4), 60–72. https://doi.org/10.21511/imfi.14(4).2017.07
• Damodar N. Gujarati. (2003). Basic Econometrics (4th ed.). Mc Graw Hill.
• Engle, R. F., & Granger, C. W. J. (2015). Co-integration and error correction: Representation, es-timation, and testing. Applied Econometrics, 39(3). https://doi.org/10.2307/1913236
• Fernández, M. Á. E., Alonso, S. L. N., Jorge-Vázquez, J., & Forradellas, R. F. R. (2021). Central banks’ monetary policy in the face of the COVID-19 economic crisis: Monetary stimulus and the emergence of CBDCs. Sustainability (Switzerland), 13(8). https://doi.org/10.3390/su13084242
• GÖKALP, B. T. (2022). The Effects of Cryptocurrency Market on Borsa Istanbul Indices. Ekonomi, Politika & Finans Araştırmaları Dergisi, 7(2). https://doi.org/10.30784/epfad.1081705
• Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424. https://doi.org/10.2307/1912791
• Granger, C. W. J. (1988). Some recent development in a concept of causality. Journal of Econ-ometrics, 39(1–2). https://doi.org/10.1016/0304-4076(88)90045-0
• Gujarati, D. N., & Porter, D. C. (2003). Basic econometrics (ed.). New York: McGraw-HiII.
• Jeffrey M. Wooldridge. (2002). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press.
• Ji, Q., Bouri, E., Roubaud, D., & Kristoufek, L. (2019). Information interdependence among ener-gy, cryptocurrency and major commodity markets. Energy Economics, 81. https://doi.org/10.1016/j.eneco.2019.06.005
• Kaur, A., Nayyar, A., & Singh, P. (2020). BLOCKCHAIN. In Cryptocurrencies and Blockchain Technology Applications (pp. 25–42). Wiley. https://doi.org/10.1002/9781119621201.ch2
• Kayal, P., & Rohilla, P. (2021). Bitcoin in the economics and finance literature: a survey. SN Business & Economics, 1(7). https://doi.org/10.1007/s43546-021-00090-5
• Levin, A. T., & Sinha, A. (2020). Limitations on the Effectiveness of Monetary Policy Forward Guidance in the Context of the COVID-19 Pandemic. In NBER Working Paper.
• Li, J. P., Naqvi, B., Rizvi, S. K. A., & Chang, H. L. (2021). Bitcoin: The biggest financial innovation of fourth industrial revolution and a portfolio’s efficiency booster. Technological Forecasting and Social Change, 162. https://doi.org/10.1016/j.techfore.2020.120383
• Liang, J., Li, L., Chen, W., & Zeng, D. (2019). Towards an Understanding of Cryptocurrency: A Comparative Analysis of Cryptocurrency, Foreign Exchange, and Stock. 2019 IEEE International Conference on Intelligence and Security Informatics (ISI), 137–139. https://doi.org/10.1109/ISI.2019.8823373
• Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System | Satoshi Nakamoto In-stitute. Bitcoin.Org.
• Reinhart, V., & Simin, T. (1997a). The market reaction to federal reserve policy action from 1989 to 1992. Journal of Economics and Business, 49(2), 149–168. https://doi.org/10.1016/S0148-6195(96)00077-X
• Reinhart, V., & Simin, T. (1997b). The market reaction to federal reserve policy action from 1989 to 1992. Journal of Economics and Business, 49(2), 149–168. https://doi.org/10.1016/S0148-6195(96)00077-X
• Sarit Maitra. (2013, November 13). Time-series Analysis with VAR & VECM: Statistical ap-proach. Towards Data Science.
• Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1). https://doi.org/10.2307/1912017
• Suyuan, L., & Khurshid, A. (2015). The effect of interest rate on investment; Empirical evidence of Jiangsu Province, China. Journal of International Studies, 8(1), 81–90. https://doi.org/10.14254/2071-8330.2015/8-1/7
• Uyar, U., Kelten, G. S., & Moralı, T. (2020). Yatırımcılar İçin Teknik Analiz: Bıtcoın ve Ethereum Uygulamaları. Finansal Araştırmalar ve Çalışmalar Dergisi. https://doi.org/10.14784/marufacd.785878
• Wang, J., Ma, F., Bouri, E., & Guo, Y. (2023). Which factors drive Bitcoin volatility: Macroeco-nomic, technical, or both? Journal of Forecasting, 42(4). https://doi.org/10.1002/for.2930
• Wang, L., Sarker, P. K., & Bouri, E. (2023). Short- and Long-Term Interactions Between Bitcoin and Economic Variables: Evidence from the US. Computational Economics, 61(4), 1305–1330. https://doi.org/10.1007/s10614-022-10247-5
• Zebedee, A. A., Bentzen, E., Hansen, P. R., & Lunde, A. (2008a). The Greenspan years: an analy-sis of the magnitude and speed of the equity market response to FOMC announcements. Fi-nancial Markets and Portfolio Management, 22(1), 3–20. https://doi.org/10.1007/s11408-007-0068-0
• Zebedee, A. A., Bentzen, E., Hansen, P. R., & Lunde, A. (2008b). The Greenspan years: an analy-sis of the magnitude and speed of the equity market response to FOMC announcements. Fi-nancial Markets and Portfolio Management, 22(1), 3–20. https://doi.org/10.1007/s11408-007-0068-0