Is It Possible to Understand the Dynamics of Cryptocurrency Markets Using Econophysics? Crypto-Econophysics

  • Tolga UlusoyEmail author
  • Mehmet Yunus Çelik
Part of the Contributions to Economics book series (CE)


Closely related to the entire humanity, Finance, as a scientific field, seeks to meet humanity’s endless needs and to continue its race against time. While doing so, it also benefits from other branches of science. Since speed, reliability, accessibility are at the forefront of model structures, finance continuously improves itself and tries to achieve the best interaction with other disciplines. Financial physics, also known as Econophysics, has brought new statistical methods and insights into the studies. Since thermodynamic laws, one of the most frequently used simulation systems, can explain the basics of all physical movements, the crypto money market, the stock market, and the dynamics of the foreign exchange market have been introduced. Thermodynamics describes heat movements; explain internal energy of economic systems, heat and jobs created (also called wealth or profits), and open a new page in quantitative/qualitative Economic Research. In this study, following the second law of thermodynamics, the Carnot cycle was written with a new point of view from the question of whether the amount of work given to the system in the crypto currency reserve can explain the possible trading (exchange) prices that occur or are likely to occur with the exchange of money.


  1. Boness, A. J. (1964). Elements of a theory of stock-option value. Journal of Political Economy, 72(2), 163–175.CrossRefGoogle Scholar
  2. Chakrabarti, B. K. (2005). Econophys-Kolkata: A short story. In A. Chatterjee, S. Yarlagadda, & B. K. Chakrabarti (Eds.), Econophysics of wealth distributions (pp. 225–228). Milan: Springer.CrossRefGoogle Scholar
  3. Coco, L., Concas, G., & Marchesi, M. (2014). Using an artificial financial market for studying a cryptocurrency market. University of Cagliari, Italy Dipartimento Ingegneria Elettrica ed Elettronicaar Xiv:1406.6496v1 [q-fin.TR].Google Scholar
  4. Derman, E. (2004). My life as a quant – reflections on physics and finance. Hoboken, NJ: Wiley.Google Scholar
  5. Donmez, C. C. (2018). An econophysics approach to introduction uncertainty in dynamics of complex market structural models. In I. Nekrasova, O. Karnaukhova, & B. Christiansen (Eds.), Fractal approaches for modeling financial assets and predicting crises (pp. 1–22). Hershey, PA: IGI Global. CrossRefGoogle Scholar
  6. Easwaran, S., Dixit, M., & Sinha, S. (2015). Bitcoin dynamics: The inverse square law of price fluctuations and other stylized facts. In F. Abergel, H. Aoyama, B. Chakrabarti, A. Chakraborti, & A. Ghosh (Eds.), Econophysics and data driven modelling of market dynamics (pp. 121–128). Cham: Springer. CrossRefGoogle Scholar
  7. Fama, E. F. (1998). Market efficiency, long-term returns, and behavioral finance. Journal of Financial Economics, 49(3), 283–306.CrossRefGoogle Scholar
  8. Ghosh, B., & Kozarević, E. (2018). Identifying explosive behavioral trace in the CNX Nifty Index: A quantum finance approach. Investment Management and Financial Innovations, 15(1), 208–223. CrossRefGoogle Scholar
  9. Ghosh, B., Krishna, M. C., Shrikanth, R., Kozarević, E., & Pandey, R. K. (2018). Predictability and herding of bourse volatility: An econophysics analogue. Investment Management and Financial Innovations, 15(2), 317–326. CrossRefGoogle Scholar
  10. Heukelom, F., Dopfer, K., Frantz, R., Mousavi, S., & Chen, S. H. (2016). Routledge handbook of behavioral economics. London: Taylor and Francis.Google Scholar
  11. Ivanov, A. I. (2018). Condensed lagrange equations. XVIII International Scientific Conference, VSU’2018, Sofia, Bulgaria.Google Scholar
  12. Külahoglu, T. (2001). Termodinamik entropi ve iletişim teorisi. Ankara: TMMOB Makine Mühendisleri Odası Yayınları.Google Scholar
  13. Levy, M., Levy, H., & Solomon, S. (1994, May). A microscopic model of the stock market: Cycles, booms, and crashes. Economics Letters, Elsevier, 45(1), 103–111.Google Scholar
  14. Li, Z. Z., Tao, R., Su, C. W., & Lobonţ, O. R. (2019). Does Bitcoin bubble burst? Quality & Quantity, 53(1), 91–105.CrossRefGoogle Scholar
  15. Mandelbrot, B. (1963). The variation of certain speculative prices. Journal of Business, 36(4), 394–419.CrossRefGoogle Scholar
  16. Mantegna, R. N., & Stanley, H. E. (1999). Introduction to econophysics: Correlations and complexity in finance. New York: Cambridge University Press.CrossRefGoogle Scholar
  17. Merton, R., & Scholes, B. (1972). The valuation of options contracts and a test of market efficiency. Journal of Finance, 27(2), 399–417.CrossRefGoogle Scholar
  18. Mimkes, J. (2004). A thermodynamic formulation of econophysics. In B. K. Chakrabarti, A. Chakraborti, & A. Chatterjee (Eds.), Econophysics and sociophysics: Trends and perspectives. Weinheim: Wiley.Google Scholar
  19. Oliveira, S. M., & Stauffer, D. (1999). Evolution, money, war, and computers – non-traditional applications of computational statistical physics. Stuttgart-Leipzig: Teubner.Google Scholar
  20. Sharma, B. G., Agrawal, S., Sharma, M., Bisen, D. P., & Sharma, R. (2011). Econophysics: A brief review of historical development, present status and future trends. arXiv preprint arXiv:1108.0977.Google Scholar
  21. Silva, A. C. (2005). Applications of physics to finance and economics: Returns, trading activity and income. arXiv:physics/0507022v1 [physics.soc-ph]Google Scholar
  22. Sornette, D. (2004). A complex system view of why stock markets crash. New Thesis, 1(1), 5–18.Google Scholar
  23. Stanley, H. E., Amaral, L. A. N., Canning, D., Gopikrishnan, P., Lee, Y., & Liu, Y. (1999). Econophysics: Can physicists contribute to the science of economics? Physica A: Statistical Mechanics and its Applications, 269(1), 156–169.CrossRefGoogle Scholar
  24. ul Haq, M. A., Usman, R. M., Bursa, N., & Özel, G. (2018). McDonald power function distribution with theory and applications. International Journal of Statistics and Economics, 19(2).Google Scholar
  25. Ulusoy, T. (2008). Ekonofizik ve finans: İMKB üzerine görgül bir çalışma/Econophysics and finance: An empirical study on ISE. Yayınlanmamış Doktora Tezi, Ankara Universitesi, PhD. Thesis, Ankara University.Google Scholar
  26. Ulusoy, T. (2017). Price fluctuations in econophysics. In Ü. Hacioğlu & H. Dinçer (Eds.), Global financial crisis and its ramifications on capital markets (pp. 459–474). Cham: Springer.CrossRefGoogle Scholar
  27. Venegas, P. (2017). Ethereum price prediction: The value investor’s guide initial coin offering (ICOS). In: Blockchain trustless crypto markets.Google Scholar
  28. Zhou, W. X., & Sornette, D. (2004). Antibubble and prediction of China’s stock market and real-estate. Physica A, 337(1–2), 243–268.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Economics and Administrative Sciences, Department of Banking and FinanceKastamonu University, Kuzeykent CampusKastamonuTurkey
  2. 2.Faculty of Economics and Administrative Sciences, Department of EconomicsKastamonu University, Kuzeykent CampusKastamonuTurkey

Personalised recommendations