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Classification-based financial markets prediction using deep neural networks

Citations

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Cited by:

  1. Salman Bahoo & Marco Cucculelli & Xhoana Goga & Jasmine Mondolo, 2024. "Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis," SN Business & Economics, Springer, vol. 4(2), pages 1-46, February.
  2. Zhi Su & Heliang Xie & Lu Han, 2021. "Multi-Factor RFG-LSTM Algorithm for Stock Sequence Predicting," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1041-1058, April.
  3. Kim, A. & Yang, Y. & Lessmann, S. & Ma, T. & Sung, M.-C. & Johnson, J.E.V., 2020. "Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 217-234.
  4. 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.
  5. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
  6. Takuya Shintate & Lukáš Pichl, 2019. "Trend Prediction Classification for High Frequency Bitcoin Time Series with Deep Learning," JRFM, MDPI, vol. 12(1), pages 1-15, January.
  7. Peter B. Lerner, 2022. "Fourier Integral Operator Model of Market Liquidity: The Chinese Experience 2009–2010," Mathematics, MDPI, vol. 10(14), pages 1-25, July.
  8. Jireh Yi-Le Chan & Seuk Wai Phoong & Wai Khuen Cheng & Yen-Lin Chen, 2022. "Support Resistance Levels towards Profitability in Intelligent Algorithmic Trading Models," Mathematics, MDPI, vol. 10(20), pages 1-17, October.
  9. Lei Ruan & Heng Liu, 2021. "Financial Distress Prediction Using GA-BP Neural Network Model," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(3), pages 1-1, March.
  10. Yang Qiao & Yiping Xia & Xiang Li & Zheng Li & Yan Ge, 2023. "Higher-order Graph Attention Network for Stock Selection with Joint Analysis," Papers 2306.15526, arXiv.org.
  11. Yoojeong Song & Jae Won Lee & Jongwoo Lee, 2022. "Development of Intelligent Stock Trading System Using Pattern Independent Predictor and Turning Point Matrix," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 27-38, January.
  12. Zineb Lanbouri & Saaid Achchab, 2019. "A new approach for Trading based on Long-Short Term memory technique [Une nouvelle approche pour le Trading basée sur la technique Long-Short Term Memory]," Post-Print hal-02396905, HAL.
  13. Şirin Özlem & Omer Faruk Tan, 2022. "Predicting cash holdings using supervised machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-19, December.
  14. Zihao Zhang & Stefan Zohren & Stephen Roberts, 2018. "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books," Papers 1808.03668, arXiv.org, revised Jan 2020.
  15. Ben Moews & Gbenga Ibikunle, 2020. "Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning," Papers 2002.10385, arXiv.org.
  16. Yoshiyuki Suimon & Hiroki Sakaji & Kiyoshi Izumi & Hiroyasu Matsushima, 2020. "Autoencoder-Based Three-Factor Model for the Yield Curve of Japanese Government Bonds and a Trading Strategy," JRFM, MDPI, vol. 13(4), pages 1-21, April.
  17. Kolesnikova, A. & Yang, Y. & Lessmann, S. & Ma, T. & Sung, M.-C. & Johnson, J.E.V., 2019. "Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting," IRTG 1792 Discussion Papers 2019-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  18. Moews, Ben & Ibikunle, Gbenga, 2020. "Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
  19. Sheng Xiang & Dawei Cheng & Chencheng Shang & Ying Zhang & Yuqi Liang, 2023. "Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction," Papers 2305.08740, arXiv.org.
  20. S M Raju & Ali Mohammad Tarif, 2020. "Real-Time Prediction of BITCOIN Price using Machine Learning Techniques and Public Sentiment Analysis," Papers 2006.14473, arXiv.org.
  21. Fabian Waldow & Matthias Schnaubelt & Christopher Krauss & Thomas Günter Fischer, 2021. "Machine Learning in Futures Markets," JRFM, MDPI, vol. 14(3), pages 1-14, March.
  22. Parisa Golbayani & Dan Wang & Ionut Florescu, 2020. "Application of Deep Neural Networks to assess corporate Credit Rating," Papers 2003.02334, arXiv.org.
  23. Hyeong Kyu Choi, 2018. "Stock Price Correlation Coefficient Prediction with ARIMA-LSTM Hybrid Model," Papers 1808.01560, arXiv.org, revised Oct 2018.
  24. Mohammad El Hajj & Jamil Hammoud, 2023. "Unveiling the Influence of Artificial Intelligence and Machine Learning on Financial Markets: A Comprehensive Analysis of AI Applications in Trading, Risk Management, and Financial Operations," JRFM, MDPI, vol. 16(10), pages 1-16, October.
  25. Artur Sokolovsky & Luca Arnaboldi & Jaume Bacardit & Thomas Gross, 2021. "Volume-Centred Range Bars: Novel Interpretable Representation of Financial Markets Designed for Machine Learning Applications," Papers 2103.12419, arXiv.org, revised May 2022.
  26. Reza Yarbakhsh & Mahdieh Soleymani Baghshah & Hamidreza Karimaghaie, 2023. "Predicting risk/reward ratio in financial markets for asset management using machine learning," Papers 2311.09148, arXiv.org.
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