Araştırma Makalesi
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The Determinants of Prices of Fan Tokens as a New Sports Finance Tool

Yıl 2024, Cilt: 24 Sayı: 2, 221 - 232, 25.05.2024
https://doi.org/10.21121/eab.1309596

Öz

In the Covid-19 era, the income sources of sports clubs decreased, but the importance of fan tokens as new communication, management, and income source for sports clubs increased with Blockchain technology. For this reason, the relationships between fan token prices and club success, transaction volume, and attractiveness factors were examined and the important determinants of fan token prices were tried to be revealed. To determine the most suitable methods for panel data model, first of all, cross-section dependence, homogeneity, and unit root tests were carried out. Then the durbin test was performed and it was concluded that the variables were cointegrated. Finally, the coefficients were examined with the PMG/ARDL test and it was observed that the most important determinants of fan token prices were club success and transaction volume, respectively. While these factors affect fan token prices positively, the effect of the attractiveness factor is seen as less important and negative compared to other factors. In addition, in the error correction model established, the existence of a long-term equilibrium relationship between the variables was confirmed. It was concluded that the short-term deviations returned to the equilibrium after approximately 21 days.

Teşekkür

We thank Mr. John Kleppe, consultant at Hybercube Business Innovation, for his assistance in providing the ECI data.

Kaynakça

  • Bhambhwani, S. M., Delikouras, S. and Korniotis, G. M. (2023). Blockchain characteristics and cryptocurrency returns. Journal of International Financial Markets, Institutions and Money, 86, 1-18. Doi: 10.1016/j.intfin.2023.101788
  • Bersvendsen, T. and Ditzen, J. (2021). Testing for slope heterogeneity in Stata. The Stata Journal, 21(1), 51-80. Doi: 10.1177/1536867X211000004
  • Bouri, E. and Jalkh, N. (2023). Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants. International Review of Financial Analysis, 90, 1-17. Doi: 10.1016/j.irfa.2023.102915
  • Chiliz (n.d.). Chiliz $CHZ - Driving Socios.com forward. Avaliable at: https://www.chiliz.com/en/our-story/
  • Ciaian, P., Rajcaniova, M. and Kancs D. (2016). The economics of Bitcoin price formation. Applied Economics, 48(19), 1799–1815. Doi: 10.1080/00036846.2015.1109038
  • CoinMarketCap (n.d.). Historical data [Data], Avaliable at: https://coinmarketcap.com/
  • Demir, E., Ersan, O. and Popesko, B., (2022). Are Fan Tokens Fan Tokens? Finance Research Letters, 102736. Doi: 10.1016/j.frl.2022.102736
  • Demir, M. A. and Aktaş, R. (2022). The relationship between fan tokens and cryptocurrencies: An empirical evıdence. International Journal of Economic and Administrative Studies, 37, 55-70. Doi: 10.18092/ulikidince.1112054
  • Georgoula, I., Pournarakis, D., Bilanakos, C., Sotiropoulos, D. and Giaglis, G.M. (2015). Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices, MCIS 2015 Proceedings. 20, Avaliable at: https://aisel.aisnet.org/mcis2015/20
  • GoogleTrends (n.d.). Discover what topics are searched all over the World [Data], Avaliable at: https://trends.google.com/
  • GSIC (2021). The sports industry and the digital transformation: 5 years ahead [Report]. Avaliable at: https://sport-gsic.com/
  • Guizani, S. and Nafti, I. K. (2019). The determinants of Bitcoin price volatility: An investigation with ARDL model. Procedia Computer Science, 164, 233-238. Doi: 10.1016/j.procs.2019.12.177
  • Hypercube (n.d.). Euro Club Index (ECI) [Data], Avaliable at: https://www.euroclubindex.com/ IWF (2021). AC Milan crypto launch raises $6m as early trading volumes top $50m [Newsletter], Avaliable at: https://www.insideworldfootball.com/
  • Kaminski, J. C. (2014). Nowcasting the Bitcoin market with Twitter signals. Working Paper, Doi: 10.48550/arXiv.1406.7577
  • Kristoufek, L (2015) What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis. PLoS ONE, 10(4), 1-15. Doi: 10.1371/journal.pone.0123923
  • Kwon, J. H. (2021). On the factors of Bitcoin’s value at risk, Financial Innovation, 7, 1-31. Doi: 10.1186/s40854-021-00297-3
  • Marca (2022). Fan Tokens to become second largest source of revenue for sports industry [Newsletter]. Avaliable at: https://www.marca.com/
  • Panagiotidis, T., Stengos, T. and Vravosinos, O. (2018) On the determinants of bitcoin returns: A LASSO approach. Finance Research Letters, 27, 235-240. Doi: 10.1016/j.frl.2018.03.016
  • Pesaran, M.H. (2004). General diagnostic tests for cross-sectional dependence in panels. Cesifo Working Paper No. 1229, 1-39. Avaliable at: https://www.cesifo.org/
  • Pesaran, M.H. (2007). A simple panel unit root test in the presence of cross-section dependence, Journal of Applied Econometrics, 22, 265-312. Doi: 10.1002/jae.951
  • Pesaran, M.H. and Yamagata, T. (2008). Testing slope homogeneity in large panels, Journal of Econometrics, 142(1), 50-93. Doi: 10.1016/j.jeconom.2007.05.010
  • Pesaran, M.H., Shin, Y. and Smith, R.P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634. Doi: 10.2307/2670182
  • Reuters (2021). Messi joins crypto craze as gets part of PSG fee in fan tokens [Newsletter]. Avaliable at: https://www.reuters.com/
  • Scharnowski, M., Scharnowski, S. and Zimmermann, L., (2023). Fan Tokens: Sports and Speculation on the Blockchain, Journal of International Financial Markets, Institutions & Money, 89, 1-27. Doi: 10.1016/j.intfin.2023.101880
  • 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. Doi: 10.1991/jefa.v2i2.a16
  • Sukamulja, S. and Sikora, C. O. (2018). The new era of financial innovation: The determinants of Bitcoın’s price. Journal of Indonesian Economy and Business, 33(1), 46-64. Doi: 10.22146/jieb.30646
  • Vidal-Tomás, D., (2022). Blockchain, sport and fan tokens. Munich Personal RePEc Archive. MPRA Paper No. 111350. https://mpra.ub.uni-muenchen.de/111350/
  • Wang, J., Xue, Y., and Liu, M. (2016). An analysis of bitcoin price based on VEC model. International Conference on Economics and Management Innovations.
  • Wang, Y., Andreeva, G. and Martin-Barragan, B. (2023). Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants. International Review of Financial Analysis, 90, 1-21. Doi: 10.1016/j.irfa.2023.102914
  • Westerlund, J. (2008). Panel cointegration tests of the fisher effect. Journal of Applied Econometrics, 23, 193-233. Doi: 10.1002/jae.967
  • Yelowitz, A. and Wilson. M. (2015). Characteristics of Bitcoin users: an analysis of Google search data. Applied Economics Letters, 22(13), 1030-1036. Doi: 10.1080/13504851.2014.995359
  • Zhu, Y., Dickinson, D. and Li, J. (2017). Analysis on the influence factors of bitcoin’s price based on VEC model. Financial Innovation, 3(1), 1-13. Doi: 10.1186/s40854-017-0054-0
Yıl 2024, Cilt: 24 Sayı: 2, 221 - 232, 25.05.2024
https://doi.org/10.21121/eab.1309596

Öz

Kaynakça

  • Bhambhwani, S. M., Delikouras, S. and Korniotis, G. M. (2023). Blockchain characteristics and cryptocurrency returns. Journal of International Financial Markets, Institutions and Money, 86, 1-18. Doi: 10.1016/j.intfin.2023.101788
  • Bersvendsen, T. and Ditzen, J. (2021). Testing for slope heterogeneity in Stata. The Stata Journal, 21(1), 51-80. Doi: 10.1177/1536867X211000004
  • Bouri, E. and Jalkh, N. (2023). Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants. International Review of Financial Analysis, 90, 1-17. Doi: 10.1016/j.irfa.2023.102915
  • Chiliz (n.d.). Chiliz $CHZ - Driving Socios.com forward. Avaliable at: https://www.chiliz.com/en/our-story/
  • Ciaian, P., Rajcaniova, M. and Kancs D. (2016). The economics of Bitcoin price formation. Applied Economics, 48(19), 1799–1815. Doi: 10.1080/00036846.2015.1109038
  • CoinMarketCap (n.d.). Historical data [Data], Avaliable at: https://coinmarketcap.com/
  • Demir, E., Ersan, O. and Popesko, B., (2022). Are Fan Tokens Fan Tokens? Finance Research Letters, 102736. Doi: 10.1016/j.frl.2022.102736
  • Demir, M. A. and Aktaş, R. (2022). The relationship between fan tokens and cryptocurrencies: An empirical evıdence. International Journal of Economic and Administrative Studies, 37, 55-70. Doi: 10.18092/ulikidince.1112054
  • Georgoula, I., Pournarakis, D., Bilanakos, C., Sotiropoulos, D. and Giaglis, G.M. (2015). Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices, MCIS 2015 Proceedings. 20, Avaliable at: https://aisel.aisnet.org/mcis2015/20
  • GoogleTrends (n.d.). Discover what topics are searched all over the World [Data], Avaliable at: https://trends.google.com/
  • GSIC (2021). The sports industry and the digital transformation: 5 years ahead [Report]. Avaliable at: https://sport-gsic.com/
  • Guizani, S. and Nafti, I. K. (2019). The determinants of Bitcoin price volatility: An investigation with ARDL model. Procedia Computer Science, 164, 233-238. Doi: 10.1016/j.procs.2019.12.177
  • Hypercube (n.d.). Euro Club Index (ECI) [Data], Avaliable at: https://www.euroclubindex.com/ IWF (2021). AC Milan crypto launch raises $6m as early trading volumes top $50m [Newsletter], Avaliable at: https://www.insideworldfootball.com/
  • Kaminski, J. C. (2014). Nowcasting the Bitcoin market with Twitter signals. Working Paper, Doi: 10.48550/arXiv.1406.7577
  • Kristoufek, L (2015) What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis. PLoS ONE, 10(4), 1-15. Doi: 10.1371/journal.pone.0123923
  • Kwon, J. H. (2021). On the factors of Bitcoin’s value at risk, Financial Innovation, 7, 1-31. Doi: 10.1186/s40854-021-00297-3
  • Marca (2022). Fan Tokens to become second largest source of revenue for sports industry [Newsletter]. Avaliable at: https://www.marca.com/
  • Panagiotidis, T., Stengos, T. and Vravosinos, O. (2018) On the determinants of bitcoin returns: A LASSO approach. Finance Research Letters, 27, 235-240. Doi: 10.1016/j.frl.2018.03.016
  • Pesaran, M.H. (2004). General diagnostic tests for cross-sectional dependence in panels. Cesifo Working Paper No. 1229, 1-39. Avaliable at: https://www.cesifo.org/
  • Pesaran, M.H. (2007). A simple panel unit root test in the presence of cross-section dependence, Journal of Applied Econometrics, 22, 265-312. Doi: 10.1002/jae.951
  • Pesaran, M.H. and Yamagata, T. (2008). Testing slope homogeneity in large panels, Journal of Econometrics, 142(1), 50-93. Doi: 10.1016/j.jeconom.2007.05.010
  • Pesaran, M.H., Shin, Y. and Smith, R.P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634. Doi: 10.2307/2670182
  • Reuters (2021). Messi joins crypto craze as gets part of PSG fee in fan tokens [Newsletter]. Avaliable at: https://www.reuters.com/
  • Scharnowski, M., Scharnowski, S. and Zimmermann, L., (2023). Fan Tokens: Sports and Speculation on the Blockchain, Journal of International Financial Markets, Institutions & Money, 89, 1-27. Doi: 10.1016/j.intfin.2023.101880
  • 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. Doi: 10.1991/jefa.v2i2.a16
  • Sukamulja, S. and Sikora, C. O. (2018). The new era of financial innovation: The determinants of Bitcoın’s price. Journal of Indonesian Economy and Business, 33(1), 46-64. Doi: 10.22146/jieb.30646
  • Vidal-Tomás, D., (2022). Blockchain, sport and fan tokens. Munich Personal RePEc Archive. MPRA Paper No. 111350. https://mpra.ub.uni-muenchen.de/111350/
  • Wang, J., Xue, Y., and Liu, M. (2016). An analysis of bitcoin price based on VEC model. International Conference on Economics and Management Innovations.
  • Wang, Y., Andreeva, G. and Martin-Barragan, B. (2023). Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants. International Review of Financial Analysis, 90, 1-21. Doi: 10.1016/j.irfa.2023.102914
  • Westerlund, J. (2008). Panel cointegration tests of the fisher effect. Journal of Applied Econometrics, 23, 193-233. Doi: 10.1002/jae.967
  • Yelowitz, A. and Wilson. M. (2015). Characteristics of Bitcoin users: an analysis of Google search data. Applied Economics Letters, 22(13), 1030-1036. Doi: 10.1080/13504851.2014.995359
  • Zhu, Y., Dickinson, D. and Li, J. (2017). Analysis on the influence factors of bitcoin’s price based on VEC model. Financial Innovation, 3(1), 1-13. Doi: 10.1186/s40854-017-0054-0
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makalesi
Yazarlar

Ersin Kanat 0000-0002-9361-4495

Emrah Öget 0000-0002-7659-4357

Ferudun Kaya 0000-0002-8930-9711

Erken Görünüm Tarihi 23 Mayıs 2024
Yayımlanma Tarihi 25 Mayıs 2024
Kabul Tarihi 8 Mart 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 24 Sayı: 2

Kaynak Göster

APA Kanat, E., Öget, E., & Kaya, F. (2024). The Determinants of Prices of Fan Tokens as a New Sports Finance Tool. Ege Academic Review, 24(2), 221-232. https://doi.org/10.21121/eab.1309596
AMA Kanat E, Öget E, Kaya F. The Determinants of Prices of Fan Tokens as a New Sports Finance Tool. eab. Mayıs 2024;24(2):221-232. doi:10.21121/eab.1309596
Chicago Kanat, Ersin, Emrah Öget, ve Ferudun Kaya. “The Determinants of Prices of Fan Tokens As a New Sports Finance Tool”. Ege Academic Review 24, sy. 2 (Mayıs 2024): 221-32. https://doi.org/10.21121/eab.1309596.
EndNote Kanat E, Öget E, Kaya F (01 Mayıs 2024) The Determinants of Prices of Fan Tokens as a New Sports Finance Tool. Ege Academic Review 24 2 221–232.
IEEE E. Kanat, E. Öget, ve F. Kaya, “The Determinants of Prices of Fan Tokens as a New Sports Finance Tool”, eab, c. 24, sy. 2, ss. 221–232, 2024, doi: 10.21121/eab.1309596.
ISNAD Kanat, Ersin vd. “The Determinants of Prices of Fan Tokens As a New Sports Finance Tool”. Ege Academic Review 24/2 (Mayıs 2024), 221-232. https://doi.org/10.21121/eab.1309596.
JAMA Kanat E, Öget E, Kaya F. The Determinants of Prices of Fan Tokens as a New Sports Finance Tool. eab. 2024;24:221–232.
MLA Kanat, Ersin vd. “The Determinants of Prices of Fan Tokens As a New Sports Finance Tool”. Ege Academic Review, c. 24, sy. 2, 2024, ss. 221-32, doi:10.21121/eab.1309596.
Vancouver Kanat E, Öget E, Kaya F. The Determinants of Prices of Fan Tokens as a New Sports Finance Tool. eab. 2024;24(2):221-32.