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References

  1. Bouri, E., Azzi, G., & Dyhrberg, A.H. (2017). On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics: The Open-Access, Open-Assessment E-Journal, 11 (2017-2): 1–16.
  2. Bouri, E., Gupta, R., & Roubaud, D. (2018). Herding behaviour in cryptocurrencies. Finance Research Letters.
  3. Blanchard, O. (1979). Speculative bubbles, crashes and rational expectations. Economic Letters, 3(4), 387–389.
  4. Cheah, E.-T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32–36.
  5. Chen, C.Y.H., Härdle, W.K., Hou, A.J., & Wang, W. (2018). Pricing cryptocurrency options: the case of CRIX and Bitcoin.
  6. Chen, S., Chen, C.Y.H., Härdle, W.K., Lee, T.M., & Ong, B. (2017). A first econometric analysis of the CRIX family. In D. Lee, K. Chuen, and Robert Deng (eds.), Handbook of blockchain, digital finance and inclusion, vol 1, Cryptocurrency, FinTech, InsurTech, and regulation. Academic Press, Elsevier.
  7. Filimonov, V., Demos, G. & Sornette, D. (2016). Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles. Quantitative Finance 17(8), 1167–1186.
  8. Fantazzini, D., Nigmatullin, E., Sukhanovskaya, V., & Ivliev, S. (2016). Everything you always wanted to know about Bitcoin modelling but were afraid to ask. Draft in English, Moscow School of Economics, published in Russian in Applied Econometrics, 44, 5–24 as part I and Applied Econometrics, 45, 5–28 as part 2.
  9. Fry, J., & Cheah, E.-T. (2016). Negative bubbles and shocks in cryptocurrency markets. International Review of Financial Analysis, 47, 343–352.
  10. Goldenfeld, N. (1992). Lectures on phase transitions and the renormalization group frontiers in physics. Addison-Wesley, Boston.
  11. Hu, A, Parlour, C.A. & Rajan, U. (2018). Cryptocurrencies: Stylized facts on a new investible instrument. Working Paper. Available online at:
  12. Johansen, A., Ledoit, O., & Sornette, D. (2000). Crashes as critical points, International Journal of Theoretical and Applied Finance, 3, 219-255.
  13. MacDonell, A. (2014). Popping the Bitcoin bubble: An application of log-periodic power law modelling to digital currency. University of Notre Dame working paper.
  14. Madureira, A., Den Hartog, F., Bouwman, H. & Baken, N. (2013). Empirical validation of Metcalfe’s law: how internet usage patterns have changed over time. Information Economics and Policy, 25(4), 246–256.
  15. Malhotra, A., & Maloo, M. (2014). Bitcoin–is it a bubble? Evidence from unit root tests.
  16. Metcalfe, B. (2013). Metcalfe’s law after 40 years of ethernet. Computer, 46(12), 26–31.
  17. Shu, M., & Zhu, W. (2020). Detection of Chinese stock market bubbles with LPPLS confidence indicator. Physica A: Statistical Mechanics and its Applications, 557, 124892. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.
  18. Pele, D.T. (2012). An LPPL algorithm for estimating the critical time of a stock market bubble. Journal of Social and Economic Statistics, 21: 14–22. Available online at:
  19. Pele, D.T., Mazurencu-Marinescu-Pele, M. (2019). Metcalfe’s law and log-period power laws in the cryptocurrencies market, Economics, vol. 13, no. 1, 2019, pp. 20190029.
  20. Peterson, T. (2018). Metcalfe’s law as a model for Bitcoin’s value. Alternative Investment Analyst Review, 7(2), 9–18.
  21. Shen, D., Urquhart, A., & Wang, P. (2019). Does twitter predict Bitcoin? Economics Letters, 174, 118–122.
  22. Sornette, D., & Cauwels, P. (2014). Financial bubbles: mechanisms and diagnostics. Review of Behavioral Economics, 2(3).
  23. Sung, S., Kim, J., Park, B. & Kim, S. (2022). A Study on Cryptocurrency Log-Return Price Prediction Using Multivariate Time-Series Model. Axioms, 11(9).
  24. Toda, H.Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250.
  25. Trimborn, S., & Härdle, W.K. (2018). CRIX an index for cryptocurrencies. Journal of Empirical Finance, 49, 107–122.
  26. Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80–82.
  27. Van Hove, L. (2014). Metcalfe’s law: not so wrong after all. NETNOMICS: Economic Research and Electronic Networking, 15(1), 1–8.
  28. Van Hove, L. (2016). Metcalfe’s law and network quality: an extension of Zhang et al. Journal of Computer Science and Technology, 31(1), 117–123.
  29. Van Vliet, B. (2018). An alternative model of Metcalfe’s Law for valuing Bitcoin. Economics Letters, 165, 70–72.
  30. Vidal-Tomás, D., Ibáñez, A.M., & Farinós, J.E. (2018). Herding in the cryptocurrency market: CSSD and CSAD approaches. Finance Research Letters (forthcoming).
  31. Wheatley, S., Sornette, D., Huber, T., Reppen, M., & Gantner, R.N. (2018). Are Bitcoin bubbles predictable? Combining a generalized Metcalfe’s law and the LPPLS model. Swiss Finance Institute Research. Paper No. 18-22.
  32. Zhang, J., Wang, H., Chen, J. & Liu, A. Cryptocurrency price bubble detection using log-periodic power law model and wavelet analysis. IEEE Transactions on Engineering Management, (71).
  33. Zhang, W., Wang P., Li, X., & Shen, D. (2018). Some stylized facts of the cryptocurrency market. Applied Economics, 50(55), 5950–5965.
  34. Zhang, X.Z., Liu, J.J., & Xu, Z.W. (2015). Tencent and Facebook data validate Metcalfe’s law. Journal of Computer Science and Technology, 30(2), 246–251.
  35. Zhu, Y., Dickinson, D., & Li, J. (2017). Analysis on the influence factors of Bitcoin’s price based on the VEC model. Financial Innovation 3(3).
  36. Andria, M. (2019). An economic assessment of risks in Bitcoin as an alternate asset class. Studies in Applied Finance SAF(27).
  37. Patrick, W. & Wolfgang, K.H. (2023). Metcalfe’s Law and Cryptocurrencies. Quantinar.
  38. European Banking Authority. (2022, March 16). EU financial regulators warn consumers on the risks of crypto-assets.
  39. European Securities and Markets Authority. (2022, March 17). EU financial regulators warn consumers on the risks of crypto-assets.
  40. European Supervisory Authorities. (2016, November 17). Guidelines on the characteristics of a risk-based approach to anti-money laundering and counter-terrorist financing supervision.
Language: English
Page range: 490 - 505
Published on: Jul 24, 2025
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Andrei-Theodor Ginavar, Alexandra Ioana Conda, Daniel Traian Pele, Miruna Mazurencu-Marinescu-Pele, Daniela-Ioana Manea, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.