Research Article
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Bitcoin Price Prediction with Fuzzy Logic

Year 2024, Volume: 28 Issue: 2, 259 - 269, 30.04.2024

Gulcihan Ozdemir

https://doi.org/10.16984/saufenbilder.1250302

Abstract

Due to cryptocurrencies' rising prices, like bitcoin, more and more people are becoming interested in them. Success in this business depends on a good price prediction. Several methods, including heuristic and machine-learning-based ones, can currently estimate the price with varied degrees of success. This study will use the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) model to predict the price's general direction over the next 10 days. Along with popular traders' indicators, the previous day's price will be used. The findings demonstrated that, despite errors, price direction predictions—an increase, a drop, or a stable price—are typically accurate.

Keywords

Bitcoin Cryptocurrency ANFIS Price Prediction Trend Analysis

References

  • [1] S. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System,” 2008. [Online]. Available: www.bitcoin.org.
  • [2] M. Bartoletti, S. Lande, A. Loddo, L. Pompianu, S. Serusi, “Cryptocurrency scams: Analysis and perspectives,” IEEE Access, vol. 9, pp. 148353–148373, 2021.
  • [3] G. S. Atsalakis, I. G. Atsalaki, F. Pasiouras, C. Zopounidis, “Bitcoin price forecasting with neuro-fuzzy techniques,” European Journal of Operational Research, vol. 276, no. 2, pp. 770–780, Jul. 2019.
  • [4] “Coin Market Cap.” Accessed: Sep. 19, 2023. [Online]. Available: https://coinmarketcap.com/currencies/bitcoin/
  • [5] G. S. Atsalakis, K. P. Valavanis, “Forecasting stock market short-term trends using a neuro-fuzzy based methodology,” Expert Systems with Applications, vol. 36, no. 7, pp. 10696–10707, Sep. 2009.
  • [6] L. Catania, S. Grassi, F. Ravazzolo, “Forecasting cryptocurrencies under model and parameter instability,” International Journal of Forecasting, vol. 35, no. 2, pp. 485–501, Apr. 2019.
  • [7] B. Kutlu Karabıyık and Z. Can Ergün, “Forecasting Bitcoin Prices with the ANFIS Model,” 2021.
  • [8] N. Maleki, A. Nikoubin, M. Rabbani, Y. Zeinali, “Bitcoin Price Prediction Based on Other Cryptocurrencies Using Machine Learning and Time Series Analysis,” Sharif University of Technology, Scientia Iranica, Transactions E: Industrial Engineering, Vol. 30, no. 1, 285-301, 2023.
  • [9] P. Jaquart, D. Dann, C. Weinhardt, “Short-term bitcoin market prediction via machine learning,” Journal of Finance and Data Science, vol. 7, pp. 45–66, Nov. 2021.
  • [10] S. E. Charandabi and K. Kamyar, “Prediction of Cryptocurrency Price Index Using Artificial Neural Networks: A Survey of the Literature,” European Journal of Business and Management Research, vol. 6, no. 6, pp. 17–20, Nov. 2021.
  • [11] Y. Liu, Institute of Electrical and Electronics Engineers, and IEEE Circuits and Systems Society, “Bitcoin price prediction using ensembles of neural networks,” in ICNC-FSKD 2017 : 13th International Conference on Natural Computation, Fuzzy Systems, and Knowledge Discovery : Guilin, Guangxi, China, 29-31 Jul, 2017, 2018.
  • [12] R. Sujatha, V. Mareeswari, J. M. Chatterjee, A. A. A. Mousa, A. E. Hassanien, “A Bayesian regularized neural network for analyzing bitcoin trends,” IEEE Access, vol. 9, pp. 37989–38000, 2021.
  • [13] A. Mikhaylov, “Cryptocurrency market analysis from the open innovation perspective,” Journal of Open Innovation: Technology, Market, and Complexity, vol. 6, no. 4, pp. 1–19, Dec. 2020.
  • [14] B. Aygun, E. Kabakci Gunay, “Comparison of Statistical and Machine Learning Algorithms for Forecasting Daily Bitcoin Returns,” European Journal of Science and Technology, Jan. 2021.
  • [15] T. G. Andersen, T. Bollerslev, F. X. Diebold, “w8160_ModellingandForecastingRealizedVolatility_2003,” 2001.
  • [16] O. Liashenko, T. Kravets, Y. Repetskyi, “Neural Networks in Application to Cryptocurrency Exchange Modeling,” 2021.
  • [17] C. H. Su, C. H. Cheng, “A hybrid fuzzy time series model based on ANFIS and integrated nonlinear feature selection method for forecasting stock,” Neurocomputing, vol. 205, pp. 264–273, Sep. 2016.
  • [18] O. Liashenko, T. Kravets, Y. Repetskyi, “Neural Networks in Application to Cryptocurrency Exchange Modeling,” 2020.
  • [19] B. Yang, Y. Sun, S. Wang, “A novel two-stage approach for cryptocurrency analysis,” International Review of Financial Analysis, vol. 72, Nov. 2020.
  • [20] İ. Daş, “Bitcoin Price Forecasting Under the Influences of Network Metrics and Other Financial Assets, M.Sc. Dissertation, Middle East Technical University of Applied Mathematics, Ankara,” 2022.
  • [21] “Historical Data.” Accessed: Feb. 08, 2023. [Online]. Available: https://web-api.coinmarketcap.com/v1/cryptocurrency/ohlcv/historical?convert=USD&slug=bitcoin&time_end=1589946400&time_start=1589000000
  • [22] J. S. R. Jang, “ANFIS: Adaptive-Network-Based Fuzzy Inference System,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 23, no. 3, pp. 665–685, 1993.

Year 2024, Volume: 28 Issue: 2, 259 - 269, 30.04.2024

Gulcihan Ozdemir

https://doi.org/10.16984/saufenbilder.1250302

Abstract

Keywords

Bitcoin cryptocurrency ANFIS price prediction

References

  • [1] S. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System,” 2008. [Online]. Available: www.bitcoin.org.
  • [2] M. Bartoletti, S. Lande, A. Loddo, L. Pompianu, S. Serusi, “Cryptocurrency scams: Analysis and perspectives,” IEEE Access, vol. 9, pp. 148353–148373, 2021.
  • [3] G. S. Atsalakis, I. G. Atsalaki, F. Pasiouras, C. Zopounidis, “Bitcoin price forecasting with neuro-fuzzy techniques,” European Journal of Operational Research, vol. 276, no. 2, pp. 770–780, Jul. 2019.
  • [4] “Coin Market Cap.” Accessed: Sep. 19, 2023. [Online]. Available: https://coinmarketcap.com/currencies/bitcoin/
  • [5] G. S. Atsalakis, K. P. Valavanis, “Forecasting stock market short-term trends using a neuro-fuzzy based methodology,” Expert Systems with Applications, vol. 36, no. 7, pp. 10696–10707, Sep. 2009.
  • [6] L. Catania, S. Grassi, F. Ravazzolo, “Forecasting cryptocurrencies under model and parameter instability,” International Journal of Forecasting, vol. 35, no. 2, pp. 485–501, Apr. 2019.
  • [7] B. Kutlu Karabıyık and Z. Can Ergün, “Forecasting Bitcoin Prices with the ANFIS Model,” 2021.
  • [8] N. Maleki, A. Nikoubin, M. Rabbani, Y. Zeinali, “Bitcoin Price Prediction Based on Other Cryptocurrencies Using Machine Learning and Time Series Analysis,” Sharif University of Technology, Scientia Iranica, Transactions E: Industrial Engineering, Vol. 30, no. 1, 285-301, 2023.
  • [9] P. Jaquart, D. Dann, C. Weinhardt, “Short-term bitcoin market prediction via machine learning,” Journal of Finance and Data Science, vol. 7, pp. 45–66, Nov. 2021.
  • [10] S. E. Charandabi and K. Kamyar, “Prediction of Cryptocurrency Price Index Using Artificial Neural Networks: A Survey of the Literature,” European Journal of Business and Management Research, vol. 6, no. 6, pp. 17–20, Nov. 2021.
  • [11] Y. Liu, Institute of Electrical and Electronics Engineers, and IEEE Circuits and Systems Society, “Bitcoin price prediction using ensembles of neural networks,” in ICNC-FSKD 2017 : 13th International Conference on Natural Computation, Fuzzy Systems, and Knowledge Discovery : Guilin, Guangxi, China, 29-31 Jul, 2017, 2018.
  • [12] R. Sujatha, V. Mareeswari, J. M. Chatterjee, A. A. A. Mousa, A. E. Hassanien, “A Bayesian regularized neural network for analyzing bitcoin trends,” IEEE Access, vol. 9, pp. 37989–38000, 2021.
  • [13] A. Mikhaylov, “Cryptocurrency market analysis from the open innovation perspective,” Journal of Open Innovation: Technology, Market, and Complexity, vol. 6, no. 4, pp. 1–19, Dec. 2020.
  • [14] B. Aygun, E. Kabakci Gunay, “Comparison of Statistical and Machine Learning Algorithms for Forecasting Daily Bitcoin Returns,” European Journal of Science and Technology, Jan. 2021.
  • [15] T. G. Andersen, T. Bollerslev, F. X. Diebold, “w8160_ModellingandForecastingRealizedVolatility_2003,” 2001.
  • [16] O. Liashenko, T. Kravets, Y. Repetskyi, “Neural Networks in Application to Cryptocurrency Exchange Modeling,” 2021.
  • [17] C. H. Su, C. H. Cheng, “A hybrid fuzzy time series model based on ANFIS and integrated nonlinear feature selection method for forecasting stock,” Neurocomputing, vol. 205, pp. 264–273, Sep. 2016.
  • [18] O. Liashenko, T. Kravets, Y. Repetskyi, “Neural Networks in Application to Cryptocurrency Exchange Modeling,” 2020.
  • [19] B. Yang, Y. Sun, S. Wang, “A novel two-stage approach for cryptocurrency analysis,” International Review of Financial Analysis, vol. 72, Nov. 2020.
  • [20] İ. Daş, “Bitcoin Price Forecasting Under the Influences of Network Metrics and Other Financial Assets, M.Sc. Dissertation, Middle East Technical University of Applied Mathematics, Ankara,” 2022.
  • [21] “Historical Data.” Accessed: Feb. 08, 2023. [Online]. Available: https://web-api.coinmarketcap.com/v1/cryptocurrency/ohlcv/historical?convert=USD&slug=bitcoin&time_end=1589946400&time_start=1589000000
  • [22] J. S. R. Jang, “ANFIS: Adaptive-Network-Based Fuzzy Inference System,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 23, no. 3, pp. 665–685, 1993.
There are 22 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other)
Journal Section Research Articles
Authors

Gulcihan Ozdemir 0000-0003-2073-9366

Early Pub Date April 22, 2024
Publication Date April 30, 2024
Submission Date February 12, 2023
Acceptance Date December 28, 2023
Published in Issue Year 2024 Volume: 28 Issue: 2

Cite

APA Ozdemir, G. (2024). Bitcoin Price Prediction with Fuzzy Logic. Sakarya University Journal of Science, 28(2), 259-269. https://doi.org/10.16984/saufenbilder.1250302
AMA Ozdemir G. Bitcoin Price Prediction with Fuzzy Logic. SAUJS. April 2024;28(2):259-269. doi:10.16984/saufenbilder.1250302
Chicago Ozdemir, Gulcihan. “Bitcoin Price Prediction With Fuzzy Logic”. Sakarya University Journal of Science 28, no. 2 (April 2024): 259-69. https://doi.org/10.16984/saufenbilder.1250302.
EndNote Ozdemir G (April 1, 2024) Bitcoin Price Prediction with Fuzzy Logic. Sakarya University Journal of Science 28 2 259–269.
IEEE G. Ozdemir, “Bitcoin Price Prediction with Fuzzy Logic”, SAUJS, vol. 28, no. 2, pp. 259–269, 2024, doi: 10.16984/saufenbilder.1250302.
ISNAD Ozdemir, Gulcihan. “Bitcoin Price Prediction With Fuzzy Logic”. Sakarya University Journal of Science 28/2 (April 2024), 259-269. https://doi.org/10.16984/saufenbilder.1250302.
JAMA Ozdemir G. Bitcoin Price Prediction with Fuzzy Logic. SAUJS. 2024;28:259–269.
MLA Ozdemir, Gulcihan. “Bitcoin Price Prediction With Fuzzy Logic”. Sakarya University Journal of Science, vol. 28, no. 2, 2024, pp. 259-6, doi:10.16984/saufenbilder.1250302.
Vancouver Ozdemir G. Bitcoin Price Prediction with Fuzzy Logic. SAUJS. 2024;28(2):259-6.
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