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The Disruptive Innovation Potential of Decentralized Cryptocurrencies

Year 2020, Volume: 27 Issue: 2, 369 - 379, 24.08.2020
https://doi.org/10.18657/yonveek.605395

Abstract

The cryptocurrency market could only accomplish a small fraction of what it was capable of since Bitcoin was first popularized. Improving upon Bitcoin, the development of technically superior cryptocurrencies couldn’t manage to create a disruptive innovation impact on the market either. In order to understand why the cryptocurrency market couldn’t fulfill its perceived disruptive innovation potential, this study systematically reviews the literature. Relevant literature has been thoroughly searched and several studies that use certain methodologies are included in the review. These studies have been categorized based upon their approaches to the subject as supportive studies and contradictory studies. Within these categories, subsections have been created based on the findings and conclusions of each study reviewed. Following the theoretical discussion, the rationality of the movements in the market has been analyzed with regression models supported by sentimental estimation model outputs. According to the interpretation of the studies in the literature, cryptocurrencies seem to need a properly functioning natural selection mechanism, which will only allow the survival of the currencies that have the best “fit” to the needs of the market. Additionally, the findings of the regression analysis are in line with the majority of literature and suggest that the cryptocurrency prices are straight out unpredictable even with the usage of advanced AI algorithms that take human irrationality into account. Collectively, evidence suggests that in its current structural form, the ICO based cryptocurrency market is set to fail in a gradual pattern.
Key Words: Financial Markets, Fintech, Cryptocurrency
JEL Classification: G14, F30, E30

References

  • Alam, S. (2017). Testing the weak form of efficient market in cryptocurrency. Journal of Engineering and Applied Sciences, 12(9), 2285–2288.
  • Ametrano, F. M. (2016). Hayek money: The cryptocurrency price stability solution. Available at SSRN 2425270.
  • Barnes, P. (2018). Crypto Currency and its Susceptibility to Speculative Bubbles, Manipulation, Scams and Fraud. Journal of Advanced Studies in Finance (JASF), 9(2 (18)), 60–77.
  • Baum, S. C. (2018). Cryptocurrency Fraud: A Look Into The Frontier of Fraud.
  • Bian, S., Deng, Z., Li, F., Monroe, W., Shi, P., Sun, Z., … Yuan, A. (2018). Icorating: A deep-learning system for scam ico identification. ArXiv Preprint ArXiv:1803.03670.
  • Bouoiyour, J., Selmi, R., & Tiwari, A. (2014). Is Bitcoin business income or speculative bubble? Unconditional vs. Conditional frequency domain analysis.
  • Bratspies, R. M. (2018). Cryptocurrency and the Myth of the Trustless Transaction.
  • Brenig, C., Accorsi, R., & Müller, G. (2015). Economic Analysis of Cryptocurrency Backed Money Laundering. Presented at the ECIS.
  • Brown, S. D. (2016). Cryptocurrency and criminality: The Bitcoin opportunity. The Police Journal, 89(4), 327–339.
  • Burnie, A., Burnie, J., & Henderson, A. (2018). Developing a Cryptocurrency Assessment Framework: Function over Form. Ledger, 3.
  • Capital, G. (2016a). Cryptojacking: A new method for criminals to stole cryptocurrency.
  • Capital, G. (2016b). In Cryptocurrency, Good projects can turn into scams.
  • Caporale, G. M., Gil-Alana, L., & Plastun, A. (2018). Persistence in the cryptocurrency market. Research in International Business and Finance, 46, 141–148.
  • Catania, L., Grassi, S., & Ravazzolo, F. (2018). Predicting the volatility of cryptocurrency time-series. In Mathematical and Statistical Methods for Actuarial Sciences and Finance (pp. 203–207). Springer.
  • Chen, S., Chen, C. Y.-H., Härdle, W. K., Lee, T., & Ong, B. (2017). Econometric Analysis of a Cryptocurrency Index for Portfolio Investment. In Handbook of Blockchain, Digital Finance, and Inclusion, Volume 1 (pp. 175–206). Elsevier.
  • Cheung, A., Roca, E., & Su, J.-J. (2015). Crypto-currency bubbles: An application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices. Applied Economics, 47(23), 2348–2358.
  • Chuen, K., Lee, D., Guo, L., & Wang, Y. (2017). Cryptocurrency: A new investment opportunity?
  • Cocco, L., Concas, G., & Marchesi, M. (2017). Using an artificial financial market for studying a cryptocurrency market. Journal of Economic Interaction and Coordination, 12(2), 345–365.
  • Constantinescu, M. (2018). CRYPTOCURRENCIES–NATIONAL SECURITY IMPLICATIONS. Defense Resources Management in the 21st Century, 13(13), 115–119.
  • Engle, E. (2015). Is bitcoin rat poison: Cryptocurrency, crime, and counterfeiting (CCC). J. High Tech. L., 16, 340.
  • Evans-Pughe, C., Novikov, A., & Vitaliev, V. (2014). To bit or not to bit?[Bitcoin cryptocurrency]. Engineering & Technology, 9(4), 82–85.
  • Eyal, I. (2017). Blockchain technology: Transforming libertarian cryptocurrency dreams to finance and banking realities. Computer, 50(9), 38–49.
  • Farell, R. (2015). An analysis of the cryptocurrency industry.
  • Foy, J. (2019). Financial Accounting Classification of Cryptocurrency.
  • Fry, J., & Cheah, E.-T. (2016). Negative bubbles and shocks in cryptocurrency markets. International Review of Financial Analysis, 47, 343–352.
  • Güleç, T. C., & Aktaş, H. (2019). KRİPTOPARA BİRİMLERİ PİYASASINDA PUMP&DUMP MANİPULASYONLARININ İKİ AŞAMALI ANALİZİ. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 33(3), 919–932.
  • Halaburda, H., & Gandal, N. (2016). Competition in the cryptocurrency market. Available at SSRN 2506463.
  • Hamrick, J., Rouhi, F., Mukherjee, A., Feder, A., Gandal, N., Moore, T., & Vasek, M. (2018). The Economics of Cryptocurrency Pump and Dump Schemes.
  • Hayes, A. S. (2017). Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing bitcoin. Telematics and Informatics, 34(7), 1308–1321.
  • Howell, S. T., Niessner, M., & Yermack, D. (2018). Initial coin offerings: Financing growth with cryptocurrency token sales. National Bureau of Economic Research.
  • Iwamura, M., Kitamura, Y., Matsumoto, T., & Saito, K. (2014). Can we stabilize the price of a Cryptocurrency?: Understanding the design of Bitcoin and its potential to compete with Central Bank money. Understanding the Design of Bitcoin and Its Potential to Compete with Central Bank Money (October 25, 2014).
  • Jacquez, T. (2016). Cryptocurrency the new money laundering problem for banking, law enforcement, and the legal system.
  • Kamps, J., & Kleinberg, B. (2018). To the moon: Defining and detecting cryptocurrency pump-and-dumps. Crime Science, 7(1), 18.Liu, Y., & Tsyvinski, A. (2018). Risks and Returns of Cryptocurrency. National Bureau of Economic Research.
  • Majumder, A., Routh, M., & Singha, D. (2019). A Conceptual Study on the Emergence of Cryptocurrency Economy and Its Nexus with Terrorism Financing. In The Impact of Global Terrorism on Economic and Political Development: Afro-Asian Perspectives (pp. 125–138). Emerald Publishing Limited.
  • Makarov, I., & Schoar, A. (2018). Trading and arbitrage in cryptocurrency markets.
  • Mensi, W., Al-Yahyaee, K. H., & Kang, S. H. (2019). Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum. Finance Research Letters, 29, 222–230.
  • Raymaekers, W. (2015). Cryptocurrency Bitcoin: Disruption, challenges and opportunities. Journal of Payments Strategy & Systems, 9(1), 30–46.
  • Reddy, E., & Minnaar, A. (2018). Cryptocurrency: A tool and target for cybercrime. Acta Criminologica: Southern African Journal of Criminology, 31(3), 71–92.
  • Scott, B. (2016). How can cryptocurrency and blockchain technology Play a role in building social and solidarity finance? UNRISD Working Paper.
  • Singh, D. J., & Davidson, J. (2018). Bitcoins and Cryptocurrency-Scam, Bubble or Currency of the Future? (Vol. 5). Mendon Cottage Books.
  • Sovbetov, Y. (2018). Factors influencing cryptocurrency prices: Evidence from bitcoin, ethereum, dash, litcoin, and monero. Journal of Economics and Financial Analysis, 2(2), 1–27.
  • Stokel-Walker, C. (2018). The murky world of the bitcoin scam. New Scientist, (3160), 12.
  • Taskinsoy, J. (2018). Bitcoin Mania: An End to the US Dollar’s Hegemony or another Cryptocurrency Experiment Destined to Fail? Available at SSRN 3311989.
  • Torres, C. F., & Steichen, M. (2019). The Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts. ArXiv Preprint ArXiv:1902.06976.
  • Umeh, J. (2016). Blockchain double bubble or double trouble? Itnow, 58(1), 58–61.
  • Wörner, D., Von Bomhard, T., Schreier, Y.-P., & Bilgeri, D. (2016). The Bitcoin ecosystem: Disruption beyond financial services?
  • Zetzsche, D. A., Buckley, R. P., Arner, D. W., & Föhr, L. (2017). The ICO Gold Rush: It’s a scam, it’s a bubble, it’s a super challenge for regulators. University of Luxembourg Law Working Paper, (11), 17–83.

Merkezi Olmayan Kriptopara Birimlerinin Yıkıcı Yenilik Potansiyeli

Year 2020, Volume: 27 Issue: 2, 369 - 379, 24.08.2020
https://doi.org/10.18657/yonveek.605395

Abstract

Kriptopara piyasaları, Bitcoin ilk popüler hale geldiğinden bu yana kendisinden beklenenlerin sadece küçük bir kısmını gerçekleştirebildi. Bitcoinden sonra gelen ve teknik olarak üstün niteliklere sahip kriptopara birimlerinin geliştirilmesi, pazarda da yıkıcı bir inovasyon etkisi yaratmayı başaramadı. Kriptopara birimi piyasasının neden algılanan yıkıcı yenilik potansiyelini yerine getiremediğini anlamak için, bu çalışma ilgili yazını sistematik bir şekilde incelemektedir. Yazın detaylıca incelenmiş ve belirli ölçütleri karşılayan birçok çalışma derlemeye dâhil edilmiştir. Bu çalışmalar, konuya yaklaşımlarına dayanarak, destekleyici çalışmalar ve çelişkili çalışmalar olarak kategorize edilmiştir. Bu kategorilerde, incelenen her çalışmanın bulgularına ve sonuçlarına dayanarak alt bölümler oluşturulmuştur. Teorik tartışma sonrasında, sezgisel yapay zeka algoritma çıktılarıyla desteklenen bir regresyon modeli kullanılarak piyasadaki fiyat hareketlerinin rasyonelliği test edilmiştir.Yazındaki çalışmalardan yola çıkarak varılan sonuca göre, kriptopara birimleri, sadece piyasa ihtiyaçlarına en uygun niteliklere sahip olan para birimlerinin hayatta kalmasına izin verecek şekilde çalışan bir doğal seçilim mekanizmasına ihtiyaç duymaktadır. Ek olarak, regresyon analizinin bulguları yazın ile eş yönlüdür ve kripto para birimi fiyatlarının, insan irrasyonelliğini hesaba katan gelişmiş AI algoritmalarının kullanımıyla bile doğrudan tahmin edilemez olduğunu göstermektedir. Tüm bunlar bir bütün olarak, mevcut ICO tabanlı kriptopara piyasasının kademeli bir şekilde başarısız olacağına işaret etmektedir.
Anahtar Kelimeler: Finansal Piyasalar, Fintek, Kriptopara
JEL Sınıflandırması: G14, F30, E30

References

  • Alam, S. (2017). Testing the weak form of efficient market in cryptocurrency. Journal of Engineering and Applied Sciences, 12(9), 2285–2288.
  • Ametrano, F. M. (2016). Hayek money: The cryptocurrency price stability solution. Available at SSRN 2425270.
  • Barnes, P. (2018). Crypto Currency and its Susceptibility to Speculative Bubbles, Manipulation, Scams and Fraud. Journal of Advanced Studies in Finance (JASF), 9(2 (18)), 60–77.
  • Baum, S. C. (2018). Cryptocurrency Fraud: A Look Into The Frontier of Fraud.
  • Bian, S., Deng, Z., Li, F., Monroe, W., Shi, P., Sun, Z., … Yuan, A. (2018). Icorating: A deep-learning system for scam ico identification. ArXiv Preprint ArXiv:1803.03670.
  • Bouoiyour, J., Selmi, R., & Tiwari, A. (2014). Is Bitcoin business income or speculative bubble? Unconditional vs. Conditional frequency domain analysis.
  • Bratspies, R. M. (2018). Cryptocurrency and the Myth of the Trustless Transaction.
  • Brenig, C., Accorsi, R., & Müller, G. (2015). Economic Analysis of Cryptocurrency Backed Money Laundering. Presented at the ECIS.
  • Brown, S. D. (2016). Cryptocurrency and criminality: The Bitcoin opportunity. The Police Journal, 89(4), 327–339.
  • Burnie, A., Burnie, J., & Henderson, A. (2018). Developing a Cryptocurrency Assessment Framework: Function over Form. Ledger, 3.
  • Capital, G. (2016a). Cryptojacking: A new method for criminals to stole cryptocurrency.
  • Capital, G. (2016b). In Cryptocurrency, Good projects can turn into scams.
  • Caporale, G. M., Gil-Alana, L., & Plastun, A. (2018). Persistence in the cryptocurrency market. Research in International Business and Finance, 46, 141–148.
  • Catania, L., Grassi, S., & Ravazzolo, F. (2018). Predicting the volatility of cryptocurrency time-series. In Mathematical and Statistical Methods for Actuarial Sciences and Finance (pp. 203–207). Springer.
  • Chen, S., Chen, C. Y.-H., Härdle, W. K., Lee, T., & Ong, B. (2017). Econometric Analysis of a Cryptocurrency Index for Portfolio Investment. In Handbook of Blockchain, Digital Finance, and Inclusion, Volume 1 (pp. 175–206). Elsevier.
  • Cheung, A., Roca, E., & Su, J.-J. (2015). Crypto-currency bubbles: An application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices. Applied Economics, 47(23), 2348–2358.
  • Chuen, K., Lee, D., Guo, L., & Wang, Y. (2017). Cryptocurrency: A new investment opportunity?
  • Cocco, L., Concas, G., & Marchesi, M. (2017). Using an artificial financial market for studying a cryptocurrency market. Journal of Economic Interaction and Coordination, 12(2), 345–365.
  • Constantinescu, M. (2018). CRYPTOCURRENCIES–NATIONAL SECURITY IMPLICATIONS. Defense Resources Management in the 21st Century, 13(13), 115–119.
  • Engle, E. (2015). Is bitcoin rat poison: Cryptocurrency, crime, and counterfeiting (CCC). J. High Tech. L., 16, 340.
  • Evans-Pughe, C., Novikov, A., & Vitaliev, V. (2014). To bit or not to bit?[Bitcoin cryptocurrency]. Engineering & Technology, 9(4), 82–85.
  • Eyal, I. (2017). Blockchain technology: Transforming libertarian cryptocurrency dreams to finance and banking realities. Computer, 50(9), 38–49.
  • Farell, R. (2015). An analysis of the cryptocurrency industry.
  • Foy, J. (2019). Financial Accounting Classification of Cryptocurrency.
  • Fry, J., & Cheah, E.-T. (2016). Negative bubbles and shocks in cryptocurrency markets. International Review of Financial Analysis, 47, 343–352.
  • Güleç, T. C., & Aktaş, H. (2019). KRİPTOPARA BİRİMLERİ PİYASASINDA PUMP&DUMP MANİPULASYONLARININ İKİ AŞAMALI ANALİZİ. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 33(3), 919–932.
  • Halaburda, H., & Gandal, N. (2016). Competition in the cryptocurrency market. Available at SSRN 2506463.
  • Hamrick, J., Rouhi, F., Mukherjee, A., Feder, A., Gandal, N., Moore, T., & Vasek, M. (2018). The Economics of Cryptocurrency Pump and Dump Schemes.
  • Hayes, A. S. (2017). Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing bitcoin. Telematics and Informatics, 34(7), 1308–1321.
  • Howell, S. T., Niessner, M., & Yermack, D. (2018). Initial coin offerings: Financing growth with cryptocurrency token sales. National Bureau of Economic Research.
  • Iwamura, M., Kitamura, Y., Matsumoto, T., & Saito, K. (2014). Can we stabilize the price of a Cryptocurrency?: Understanding the design of Bitcoin and its potential to compete with Central Bank money. Understanding the Design of Bitcoin and Its Potential to Compete with Central Bank Money (October 25, 2014).
  • Jacquez, T. (2016). Cryptocurrency the new money laundering problem for banking, law enforcement, and the legal system.
  • Kamps, J., & Kleinberg, B. (2018). To the moon: Defining and detecting cryptocurrency pump-and-dumps. Crime Science, 7(1), 18.Liu, Y., & Tsyvinski, A. (2018). Risks and Returns of Cryptocurrency. National Bureau of Economic Research.
  • Majumder, A., Routh, M., & Singha, D. (2019). A Conceptual Study on the Emergence of Cryptocurrency Economy and Its Nexus with Terrorism Financing. In The Impact of Global Terrorism on Economic and Political Development: Afro-Asian Perspectives (pp. 125–138). Emerald Publishing Limited.
  • Makarov, I., & Schoar, A. (2018). Trading and arbitrage in cryptocurrency markets.
  • Mensi, W., Al-Yahyaee, K. H., & Kang, S. H. (2019). Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum. Finance Research Letters, 29, 222–230.
  • Raymaekers, W. (2015). Cryptocurrency Bitcoin: Disruption, challenges and opportunities. Journal of Payments Strategy & Systems, 9(1), 30–46.
  • Reddy, E., & Minnaar, A. (2018). Cryptocurrency: A tool and target for cybercrime. Acta Criminologica: Southern African Journal of Criminology, 31(3), 71–92.
  • Scott, B. (2016). How can cryptocurrency and blockchain technology Play a role in building social and solidarity finance? UNRISD Working Paper.
  • Singh, D. J., & Davidson, J. (2018). Bitcoins and Cryptocurrency-Scam, Bubble or Currency of the Future? (Vol. 5). Mendon Cottage Books.
  • Sovbetov, Y. (2018). Factors influencing cryptocurrency prices: Evidence from bitcoin, ethereum, dash, litcoin, and monero. Journal of Economics and Financial Analysis, 2(2), 1–27.
  • Stokel-Walker, C. (2018). The murky world of the bitcoin scam. New Scientist, (3160), 12.
  • Taskinsoy, J. (2018). Bitcoin Mania: An End to the US Dollar’s Hegemony or another Cryptocurrency Experiment Destined to Fail? Available at SSRN 3311989.
  • Torres, C. F., & Steichen, M. (2019). The Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts. ArXiv Preprint ArXiv:1902.06976.
  • Umeh, J. (2016). Blockchain double bubble or double trouble? Itnow, 58(1), 58–61.
  • Wörner, D., Von Bomhard, T., Schreier, Y.-P., & Bilgeri, D. (2016). The Bitcoin ecosystem: Disruption beyond financial services?
  • Zetzsche, D. A., Buckley, R. P., Arner, D. W., & Föhr, L. (2017). The ICO Gold Rush: It’s a scam, it’s a bubble, it’s a super challenge for regulators. University of Luxembourg Law Working Paper, (11), 17–83.
There are 47 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Tuna Can Güleç 0000-0003-2551-6460

Publication Date August 24, 2020
Published in Issue Year 2020 Volume: 27 Issue: 2

Cite

APA Güleç, T. C. (2020). Merkezi Olmayan Kriptopara Birimlerinin Yıkıcı Yenilik Potansiyeli. Journal of Management and Economics, 27(2), 369-379. https://doi.org/10.18657/yonveek.605395