BİR YATIRIM ARACI OLARAK BİTCOİN: BİTCOİN İLE GLOBAL TEKNOLOJİ ENDEKSLERİ ARASINDA ASİMETRİK NEDENSELLİK İLİŞKİLERİ

Year 2022, Volume: 9 Issue: 3, 2097 - 2120, 29.11.2022

Mehmet Levent Erdaş , Gamze Göçmen Yağcılar

https://doi.org/10.30798/makuiibf.1097491

Cited By: 1

Abstract

Blok zincir ve kripto paralar son yılların en popüler konuları arasındadır. İlk olarak 2008 yılında Bitcoin (BTC) ile tanıtılan kripto paralar günümüzde artan bir çeşitliliğe ve poülariteye sahiptir. Teknoloji sektöründeki güncel gelişmeler ise teknoloji endeksleri ile kripto paralar arasındaki ilişkilerin varlığına dair soruları akla getirmiştir. Bu amaçla bu çalılşmada G7 ve E7 ülkelerinin teknoloji endeksleri ile Bitcoin arasındaki nedensellik ilişkileri 2016 ve 2021 yıllarına ait aylık veri seti kullanılarak araştırılmıştır. Değişkenler arasındaki nedensellik ilişkisinin araştırılmasında Hatemi-J (2012) testi kullanılmıştır. Hatemi-J (2012) testinden elden edilen sonuçlar Bitcoin ve teknoloji endeksleri arasındaki ilişkinin G7 ve E7 ülkeleri açısından farklılık gösterdiğini ortaya koymuştur. Buna göre gelişmiş ülkelerin endeksleri Bitcoin fiyatlarını etkilerken gelişmekte olan ülkelerin endeksleri Bitcoin fiyatlarından etkilenmektedir. sonuç olarak bulgular G7 ve E7 ülkeleri için asimetrik ilişkinin vavrlığına işaret etmektedir.

Keywords

Kripto paralar, Bitcoin, Teknoloji Hisseleri

BITCOIN AS AN INVESTMENT VEHICLE: THE ASYMMETRIC RELATIONSHIPS BETWEEN BITCOIN AND GLOBAL TECHNOLOGY INDEXES

Abstract

The concept of blockchain and cryptocurrencies is one of the most popular concepts of recent years. Cryptocurrencies were first introduces with Bitcoin in 2008 and now they have an increasing variety and popularity. Recent developments in technology firms have brought into question whether there is a relationship between Bitcoin and technology indexes. To this end, this study investigates the causality relationship between Bitcoin and technology indexes using monthly data between the years 2016 and 2021 in G7 and E7 countries. To test the causality relationship between the variables, the Hatemi-J (2012) asymmetric causality test was used. Hatemi-J (2012) test reveals that the relationship between bitcoin and technology indexes becomes different for G7 and E7 countries. The results suggest that developed countries affect bitcoin prices while developing countries are affected by Bitcoin prices. The conclusion is that findings point out the existence of an asymmetric relationship between the series for G7 and E7 countries.

Keywords

Cryptocurrencies, Bitcoin, Technology equities

References

• Akyıldırım, E., Corbet, S., Sensoy, A. & Yarovaya, L. (2020). The impact of blockchain related name changes on corporate performance, Journal of Corporate Finance, 65, 101759. Al-Yahyaee, K. H., Mensi, W., Al-Jarrah, I. M. W., Hamdi, A. & Kang, S. H. (2019). Volatility forecasting, downside risk and diversification benefits of Bitcoin and oil and international commodity markets: A comapartive analysis with yellow metal, North American Journal of Economics and Finance, 49, pp. 104-120.
• Baur, D. G., Hong, K. H. & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, pp. 177-189.
• Bhuiyan, R. H., Husain, A. & Zhang, C. (2021). A wavalet approach for causal relationship between Bitcoin and conventional asset classes, Resources Policy, 71, 101971.
• Bouri, E., Molnar, P., Azzi, G., Roubaud, D. & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier? Finance Research Letters, 20, pp. 192-198.
• Bouri, E., Shahzad, S. J. H., Roubaud, D., Kristoufek, L. & Lucey, B. (2020). Bitcoin, gold and commodities as safe havens for stocks: New insight through wavalet analysis, The Quarterly Review of Economics and Finance, 77, pp. 156-164.
• BTC Türk, (2020). “ICO Nedir?” [online] Available at: https://www.btcturk.com/bilgi-platformu/initial-coin-offering-ico-nedir/ [Accessed in January 2021].
• Cahill, D., Baur, D. G., Liu, Z. F. & Yang, J. W. (2020). I’m a blockchain too:How does the market respond to companies’ interest in blockchain? Journal of Banking and Finance, 113, 105740. Cheng, S. F., De Franco, G., Jiang, H. & Lin, P. (2019). Riding the blockchain mania: Public firms’ speculative 8-k disclosures, Management Science, INFORMS, 65(12), pp. 5901-5913.
• Ciaian, P., Rajcaniova, M. & Kancs, D. (2016). The economics of Bitcoin price formation, Applied Economics, 48(19), pp. 1799-1815.
• Corbet, S., Larkin, C., Lucey, B. & Yarovaya, L. (2020). KODAKCoin: A blockchain revolution or exploiting a potential cryptocurrency bubble? Applied Economic Letters, 27(7), pp. 518-524.
• Corbet, S., Lucey, B. & Yarovaya, L. (2021). Bitcoin-energy markets interrelationships - new evidence. Resources Policy, 70, 101916.
• Corbet, S., Meegan, A., Larkin, C., Lucey, B. & Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets, Economics Letters, 165, pp. 28-34.
• Damianov, D. S. & Elsayed, A. H. (2020). Does Bitcoin add value to global industry protfolios? Economic Letters, 191, 108935.
• Elliott, G., Rothenberg, J. T. & Stock, J. H. (1996). Efficient tests for an autoregressive unit root, Econometrica, 64(4), pp. 813-836.
• Erdas, M. L. & Caglar, A. E. (2018). Analysis of the relationships between Bitcoin and exchange rate, commodities and global indexes by asymmetric causality test, Eastern Journal of European Studies, 9(2), pp. 27-45.
• Granger, C. W. & Yoon, G. (2002). Hidden cointegration, University of California, Department of Economics, Working Paper. San Diego: University of California.
• Grobys, K. & Junttilla, J. (2021). Speculation and lottery-like demand in cryptocurrency markets, Journal of International Financial Markets, Institutions and Money, 71, 101289.
• Gurdgiev, C. & O’Loughlin, D. (2020). Herding and anchoring in crypocurryncy markets: Investor reaction to fear and uncertainty, Journal of Behavioral and Experimental Finance, 25.
• Hacker, R. S. & Hatemi-J, A. (2006). Tests for causality between integrated variables using asymptotic and bootstrap distributions: Theory and application, Applied Economics, 38(13), pp.1489-1500.
• Hatemi-J, A. (2012). Asymmetric causality tests with an application, Empirical Economics, 3, pp. 447-456.
• Hatemi-J, A., Rangan, G., Axel, K., Thabo, M. & Ndivhuho, N. (2014). Are there asymmetric causal relationships between tourism and economic growth in a panel of g-7 countries? University of Pretoria, Department of Economics Working Paper Series, Working Paper: 2014-76.
• Hsiao, C. (1981). Autoregressive modelling and money-income causality detection, Journal of Monetary Economics, 7(1), pp.85-106.
• Hui, C.-H., Lo, C.-F., Chau, P.-H. & Wong, A. (2020). Does Bitcoin behave as a currency?: A standard monetary model approach, International Review of Financial Analysis, 70, 101518.
• Jain, A. & Jain, C. (2019). Blockchain hysteria: Adding “blockchain” to comany’s name, Economic Letters, 181, pp. 178-181. Klein, T., Thu, H. P. & Walther, T. (2018). Bitcoin is not the new gold - a comparison of volatility, correlation and portfolio performance, International Review of Financial Analysis, 59, pp. 105-116.
• Kliber, A., Marszalek, P., Musialkowska, I. & Swierczynska, K. (2019). Bitcoin: Safe haven, hedge or diversifier? Perception of Bitcoin in the context of a country’s economic situation - a stochastic volatility approach, Physica A, 524, pp. 246-257.
• Kwon, J. H. (2020).Tail behavior of Bitcoin, the Dollar, gold and the stock market index, Journal of International Financial Markets, Institutions and Money, 67, 101202.
• Lee, A. D., Li, M. & Zheng, H. (2020). Bitcoin: Speculative asset or innovative technology? Journal of International Financial Markets, Institutions and Money, 67, 101209.
• Lee, J. & Strazicich M. (2013). Minimum LM unit root test with one structural break, Economics Bulletin, 33(4), pp. 2483-2492.
• Lopez-Cabarcos, M. A., Perez-Pico, A. M., Pineiro-Chousa, J. & Sevic, A. (2021). Bitcoin volatility, stock market and investor sentiment. Are they connected?, Finance Research Letters, 38, 101399.
• Maghyereh, A. & Abdoh, H. (2021). Time-frequancy quantile dependence between Bitcoin and global equitiy markets, North American Journal of Economics and Finance, 56, 101355.
• Mariana, C. D., Ekaputra, I. A. & Husodo, Z. A. (2021). Are Bitcoin and Ethereum safe havens for stocks during the Covid-19 pandemic?, Finance Research Letters, 38, 101798.
• Matkovskyy, R., Jalan, A., Dowling, M. & Bouraoui, T. (2021). From bottom ten to top ten: The role of cryptocurrencies in enhancing portfolio return of poorly performing stocks, Finance Research Letters, 38,
• Mensi, W., Rehman, M. U., Maitra, D., Al-Yahyaee, K. H. & Sensoy, A. (2020). Does Bitcoin co-move and share risk with Sukuk and world and regional Islamic stock markets? Evidence using a time-frequency approach, Research in International Business and Finance, 53, 101230.
• Mert, M. & Cağlar, A. E. (2019). Eviews and Gauss Uygulamalı Zaman Serileri Analizi, Detay Publication, Ankara. Mokni, K., Ajmi, A. N., Bouri, E. & Vo, X. V. (2020). Economic policy uncertainty and the Bitcoin-US stock nexus, Journal of Multinational Financial Management, 57-58, 100656.
• Nakamoto, S. (2008). Bitcoin, a peer-to-peer electronic cash system, Retrieved from https://bitcoin.org/bitcoin.pdf Okorie, D. I. (2020). Could stock hedge Bitcoin risk(s) and vice versa?, Digital Finance, 2, pp. 117-136.
• Özcan, C. C. (2015). Analysis of relationship between tourism income and economic growth by symmetric and asymmetric causality approaches: The case of Turkey, Erciyes Univ. Jou. of Faculty of Economics and Administrative Sciences, 46, pp. 177-198.
• Pelster, M., Breitmayer, B. & Hasso, T. (2019). Are cryptocurrency traders pioneers of just risk-seekers? Evidence from brokerage accounts, Economic Letters, 182, pp. 98-100.
• Platanakis, E. & Urquhart, A. (2020). Should investors include Bitcoin in their portfolios? A portfolio theory approach, The British Accounting Review, 52, 100837.
• Phillips, P. C. B. & Perron, P. (1988). Testing for a unit root in time series regression, Biometrica, 75(2), pp. 335-346. Rehman, M. U., Asghar, N. & Kang, S. (2020). Do Islamic indices provide diversification to Bitcoin? A time-varying copulas and value at risk application, Pasific-Basin Finance Journal, 61, 101326.
• Salisu, A. A., Kazeem, I. & Akanni, L. O. (2019). Improving the predictability of stock returns with Bitcoin prices, North American Jou.of Economics and Finance, 48, pp. 857-867.
• Selmi, R., Mensi W., Hammoudeh, S. & Bouoiyour, J. (2018). Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold, Energy Economics, 74, pp. 787-801.
• Sims, C. A. (1972). Money, income, and causality, The American Economic Review, 62(4), pp.540-552. Stavros, S. & Vassilios, B. (2019). Herding behavior in cryptocurrencies revisited: Novel evidence from a TVP model, Journal of Behavioral and Experimental Finance, 22, pp. 57-63.
• Tiwari, A. K., Raheem, I. D. & Kang, S. H. (2019). Time-varying dynamic conditional correlation between stock and cryptocurrency markets using Copula-ADCC-EGARCH model. Physica A, 535, 122295.
• Toda, H. Y. & Yamamoto T. (1995). Statistical inferences in vector autoregressions with possibly integrated processes, Journal of Econometrics, 66, pp. 225‐250
• Umar, Z., Trabelsi, N. & Alqahtani, F. (2021). Connectedness between cryptocurrency and technology sectors: International evidence, Internatinal Review of Economics and Finance, 71, pp. 910-922.
• Üzer, B. (2017), Sanal Para Birimleri, TCMB, Uzmanlık Yeterlik Tezi.
• Vidal-Tomas, D., Ibanez, A. M. & Farinos, J. E. (2019). Herding in the cryptocurrency market: CSSD and CSAD approaches, Finance Research Letters, 30, pp. 181-186.
• Yen, J.-C. & Wang, T. (2021), Stock price relevance of voluntary disclosures about blockchain technology and crptocurrencies, International Journal of Accounting Information Systems, 40, 100499.
• Yılancı, V. & Bozuklu, S. (2014). Price and trade volume relationship in Turkish stock market: A time-varying asymmetric causality analysis, Ege Academic Review, 14(2), pp. 211-220.
• Zhang, W., Wang, P., Li, X. & Shen, D. (2018). The inefficiency of cryptocurrency and its cross-correlation with dow jones industrial average, Physica A, 510, pp. 658-670.
• Zhang, Y.-J., Bouri, E., Gupta, R. & Ma, S.-J. (2021). Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach. North American Journal of Economics and Finance, 55, 101296.
• Zivot, E. & Andrews, D. (1992). Further evidence on the great grash, the oil-price shock, and the unit-root hypothesis, Journal of Business and Economic Statistics, 10(3), pp. 251-270.