OG-CAT: A Novel Algorithmic Trading Alternative to Investment in Crypto Market
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DOI: 10.1007/s10614-023-10380-9
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- Atsalakis, George S. & Atsalaki, Ioanna G. & Pasiouras, Fotios & Zopounidis, Constantin, 2019.
"Bitcoin price forecasting with neuro-fuzzy techniques,"
European Journal of Operational Research, Elsevier, vol. 276(2), pages 770-780.
- George S. Atsalakis & Ioanna G. Atsalaki & Fotios Pasiouras & Constantin Zopounidis, 2019. "Bitcoin price forecasting with neuro-fuzzy techniques," Post-Print hal-02879928, HAL.
- Michael Brennan & Feifei Li & Walter Torous, 2005.
"Dollar Cost Averaging,"
Review of Finance, Springer, vol. 9(4), pages 509-535, December.
- Brennan, Michael J & Li, Feifei & Torous, Walt, 2005. "Dollar Cost Averaging," University of California at Los Angeles, Anderson Graduate School of Management qt53p0r65q, Anderson Graduate School of Management, UCLA.
- Jin-Bom Han & Sun-Hak Kim & Myong-Hun Jang & Kum-Sun Ri, 2020. "Using Genetic Algorithm and NARX Neural Network to Forecast Daily Bitcoin Price," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 337-353, August.
- Yuze Li & Shangrong Jiang & Xuerong Li & Shouyang Wang, 2022. "Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
- Altan, Aytaç & Karasu, Seçkin & Bekiros, Stelios, 2019. "Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 325-336.
- Michael J. Brennan & Feifei Li & Walter N. Torous, 2005. "Dollar Cost Averaging," Review of Finance, European Finance Association, vol. 9(4), pages 509-535.
- 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.
- 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.
- 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.
- Adcock, Robert & Gradojevic, Nikola, 2019. "Non-fundamental, non-parametric Bitcoin forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
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Keywords
Algorithmic trading; Cryptocurrency; Trading strategy; Optimization; Dollar cost averaging; Blockchain; Bitcoin; Ethereum;All these keywords.
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