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Bitcoin Technical Trading with Articial Neural Network

Citations

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Cited by:

  1. Erdinc Akyildirim & Oguzhan Cepni & Shaen Corbet & Gazi Salah Uddin, 2023. "Forecasting mid-price movement of Bitcoin futures using machine learning," Annals of Operations Research, Springer, vol. 330(1), pages 553-584, November.
  2. Zura Kakushadze & Willie Yu, 2019. "Altcoin-Bitcoin Arbitrage," Papers 1903.06033, arXiv.org, revised Apr 2019.
  3. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
  4. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Forecasting, MDPI, vol. 3(2), pages 1-44, May.
  5. Alessandra Cretarola & Gianna Figà-Talamanca & Cyril Grunspan, 2021. "Blockchain and cryptocurrencies: economic and financial research," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 781-787, December.
  6. Suhwan Ji & Jongmin Kim & Hyeonseung Im, 2019. "A Comparative Study of Bitcoin Price Prediction Using Deep Learning," Mathematics, MDPI, vol. 7(10), pages 1-20, September.
  7. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
  8. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
  9. Krzysztof Piasecki & Michał Dominik Stasiak, 2020. "Optimization Parameters of Trading System with Constant Modulus of Unit Return," Mathematics, MDPI, vol. 8(8), pages 1-17, August.
  10. Zura Kakushadze & Willie Yu, 2019. "Altcoin-Bitcoin Arbitrage," Bulletin of Applied Economics, Risk Market Journals, vol. 6(1), pages 87-110.
  11. Yue, Yao & Li, Xuerong & Zhang, Dingxuan & Wang, Shouyang, 2021. "How cryptocurrency affects economy? A network analysis using bibliometric methods," International Review of Financial Analysis, Elsevier, vol. 77(C).
  12. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
  13. Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
  14. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
  15. Masafumi Nakano & Akihiko Takahashi, 2019. "A New Investment Method with AutoEncoder: Applications to Cryptocurrencies," CIRJE F-Series CIRJE-F-1128, CIRJE, Faculty of Economics, University of Tokyo.
  16. Ao Kong & Hongliang Zhu & Robert Azencott, 2021. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 416-438, April.
  17. Jlassi, Nabila Boukef & Jeribi, Ahmed & Lahiani, Amine & Mefteh-Wali, Salma, 2023. "Subsample analysis of stock market – cryptocurrency returns tail dependence: A copula approach for the tails," Finance Research Letters, Elsevier, vol. 58(PA).
  18. Vasu Kalariya & Pushpendra Parmar & Patel Jay & Sudeep Tanwar & Maria Simona Raboaca & Fayez Alqahtani & Amr Tolba & Bogdan-Constantin Neagu, 2022. "Stochastic Neural Networks-Based Algorithmic Trading for the Cryptocurrency Market," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
  19. Qiutong Guo & Shun Lei & Qing Ye & Zhiyang Fang, 2021. "MRC-LSTM: A Hybrid Approach of Multi-scale Residual CNN and LSTM to Predict Bitcoin Price," Papers 2105.00707, arXiv.org.
  20. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
  21. Zura Kakushadze, 2018. "Cryptoasset Factor Models," Papers 1811.07860, arXiv.org, revised Feb 2019.
  22. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
  23. Sanjib Kumar Nayak & Sarat Chandra Nayak & Subhranginee Das, 2021. "Modeling and Forecasting Cryptocurrency Closing Prices with Rao Algorithm-Based Artificial Neural Networks: A Machine Learning Approach," FinTech, MDPI, vol. 1(1), pages 1-16, December.
  24. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
  25. Zvonko Merkaš & Vlasta Roška, 2021. "The Impact of Unsystematic Factors on Bitcoin Value," JRFM, MDPI, vol. 14(11), pages 1-17, November.
  26. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
  27. Helder Sebastião & Pedro Godinho, 2021. "Forecasting and trading cryptocurrencies with machine learning under changing market conditions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
  28. R. K. Jana & Indranil Ghosh & Debojyoti Das, 2021. "A differential evolution-based regression framework for forecasting Bitcoin price," Annals of Operations Research, Springer, vol. 306(1), pages 295-320, November.
  29. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
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