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A novel cryptocurrency price trend forecasting model based on LightGBM

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  1. Yamashiro, Hirochika & Nonaka, Hirofumi, 2021. "Estimation of processing time using machine learning and real factory data for optimization of parallel machine scheduling problem," Operations Research Perspectives, Elsevier, vol. 8(C).
  2. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
  3. Yilun Zhang & Yuping Song & Ying Peng & Hanchao Wang, 2024. "Volatility forecasting incorporating intraday positive and negative jumps based on deep learning model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2749-2765, November.
  4. Hakan Pabuccu & Adrian Barbu, 2023. "Feature Selection with Annealing for Forecasting Financial Time Series," Papers 2303.02223, arXiv.org, revised Feb 2024.
  5. Wu Junfeng & Li Yaoming & Tan Wenqing & Chen Yun, 2024. "Portfolio management based on a reinforcement learning framework," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2792-2808, November.
  6. Bouri, Elie & Christou, Christina & Gupta, Rangan, 2022. "Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models," Finance Research Letters, Elsevier, vol. 49(C).
  7. Hwang, Yoontae & Park, Junpyo & Lee, Yongjae & Lim, Dong-Young, 2023. "Stop-loss adjusted labels for machine learning-based trading of risky assets," Finance Research Letters, Elsevier, vol. 58(PA).
  8. Yang Zhou & Chi Xie & Gang-Jin Wang & Jue Gong & You Zhu, 2025. "Forecasting cryptocurrency volatility: a novel framework based on the evolving multiscale graph neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-52, December.
  9. 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.
  10. Yukai Chen & Khaled Sidahmed Sidahmed Alamin & Daniele Jahier Pagliari & Sara Vinco & Enrico Macii & Massimo Poncino, 2020. "Electric Vehicles Plug-In Duration Forecasting Using Machine Learning for Battery Optimization," Energies, MDPI, vol. 13(16), pages 1-19, August.
  11. Bouteska, Ahmed & Abedin, Mohammad Zoynul & Hajek, Petr & Yuan, Kunpeng, 2024. "Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods," International Review of Financial Analysis, Elsevier, vol. 92(C).
  12. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
  13. Qing Liu & Hosung Son, 2024. "Methods for aggregating investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-22, December.
  14. Chenlu Dang & Fan Wang & Zimo Yang & Hongxia Zhang & Yufeng Qian, 2022. "RETRACTED ARTICLE: Evaluating and forecasting the risks of small to medium-sized enterprises in the supply chain finance market using blockchain technology and deep learning model," Operations Management Research, Springer, vol. 15(3), pages 662-675, December.
  15. ANGHEL, Dan-Gabriel, 2021. "A reality check on trading rule performance in the cryptocurrency market: Machine learning vs. technical analysis," Finance Research Letters, Elsevier, vol. 39(C).
  16. 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).
  17. James Ming Chen & Mira Zovko & Nika Šimurina & Vatroslav Zovko, 2021. "Fear in a Handful of Dust: The Epidemiological, Environmental, and Economic Drivers of Death by PM 2.5 Pollution," IJERPH, MDPI, vol. 18(16), pages 1-59, August.
  18. Hakan Pabuccu & Adrian Barbu, 2024. "Feature selection with annealing for forecasting financial time series," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.
  19. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
  20. Qiyan Wang & Yuanyuan Jiang, 2023. "Leisure Time Prediction and Influencing Factors Analysis Based on LightGBM and SHAP," Mathematics, MDPI, vol. 11(10), pages 1-22, May.
  21. Zhang, Yan & Teoh, Bak Koon & Zhang, Limao, 2024. "Multi-objective optimization for energy-efficient building design considering urban heat island effects," Applied Energy, Elsevier, vol. 376(PA).
  22. Hoang Hiep Nguyen & Jean-Laurent Viviani & Sami Ben Jabeur, 2023. "Bankruptcy prediction using machine learning and Shapley additive explanations," Post-Print hal-04223161, HAL.
  23. Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis, 2023. "Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 852-871, July.
  24. Alireza Rezazadeh & Yasamin Jafarian & Ali Kord, 2022. "Explainable Ensemble Machine Learning for Breast Cancer Diagnosis Based on Ultrasound Image Texture Features," Forecasting, MDPI, vol. 4(1), pages 1-13, February.
  25. Yanbo Zhang & Mengkun Liang & Haiying Ou, 2024. "Prediction of Precious Metal Index Based on Ensemble Learning and SHAP Interpretable Method," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3243-3278, December.
  26. Federico D'Amario & Milos Ciganovic, 2022. "Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach," Papers 2210.00883, arXiv.org.
  27. Feng, Qianqian & Sun, Xiaolei & Hao, Jun & Li, Jianping, 2021. "Predictability dynamics of multifactor-influenced installed capacity: A perspective of country clustering," Energy, Elsevier, vol. 214(C).
  28. Zheng, Yi, 2023. "Community resilience and house prices: A machine learning approach," Finance Research Letters, Elsevier, vol. 58(PB).
  29. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
  30. Shuo Sun & Rundong Wang & Bo An, 2021. "Reinforcement Learning for Quantitative Trading," Papers 2109.13851, arXiv.org.
  31. Yanxi Zhao & Dengpan Xiao & Huizi Bai & Jianzhao Tang & De Li Liu & Yongqing Qi & Yanjun Shen, 2022. "The Prediction of Wheat Yield in the North China Plain by Coupling Crop Model with Machine Learning Algorithms," Agriculture, MDPI, vol. 13(1), pages 1-19, December.
  32. Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
  33. Ben Jabeur, Sami & Bakkar, Yassine & Cepni, Oguzhan, 2025. "Do global COVOL and geopolitical risks affect clean energy prices? Evidence from explainable artificial intelligence models," Energy Economics, Elsevier, vol. 141(C).
  34. Sheng, Yankai & Qu, Yuanyu & Ma, Ding, 2024. "Stock price crash prediction based on multimodal data machine learning models," Finance Research Letters, Elsevier, vol. 62(PA).
  35. Kaijian He & Qian Yang & Lei Ji & Jingcheng Pan & Yingchao Zou, 2023. "Financial Time Series Forecasting with the Deep Learning Ensemble Model," Mathematics, MDPI, vol. 11(4), pages 1-15, February.
  36. Xinyu Gu & KW See & Yunpeng Wang & Liang Zhao & Wenwen Pu, 2021. "The Sliding Window and SHAP Theory—An Improved System with a Long Short-Term Memory Network Model for State of Charge Prediction in Electric Vehicle Application," Energies, MDPI, vol. 14(12), pages 1-15, June.
  37. Ghallabi, Fahmi & Souissi, Bilel & Du, Anna Min & Ali, Shoaib, 2025. "ESG stock markets and clean energy prices prediction: Insights from advanced machine learning," International Review of Financial Analysis, Elsevier, vol. 97(C).
  38. Yan, Qin & Lu, Zhiying & Liu, Hong & He, Xingtang & Zhang, Xihai & Guo, Jianlin, 2024. "Short-term prediction of integrated energy load aggregation using a bi-directional simple recurrent unit network with feature-temporal attention mechanism ensemble learning model," Applied Energy, Elsevier, vol. 355(C).
  39. Rabeh Khalfaoui & Sami Ben Jabeur & Shawkat Hammoudeh & Wissal Ben Arfi, 2025. "The role of political risk, uncertainty, and crude oil in predicting stock markets: evidence from the UAE economy," Annals of Operations Research, Springer, vol. 345(2), pages 1105-1135, February.
  40. Shang, Gang & Xu, Liyun & Tian, Jinzhu & Cai, Dongwei & Xu, Zhun & Zhou, Zhuo, 2023. "A real-time green construction optimization strategy for engineering vessels considering fuel consumption and productivity: A case study on a cutter suction dredger," Energy, Elsevier, vol. 274(C).
  41. Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
  42. Ayush Singh & Anshu K. Jha & Amit N. Kumar, 2024. "Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation," Papers 2405.12988, arXiv.org.
  43. Amina Ladhari & Heni Boubaker, 2024. "Deep Learning Models for Bitcoin Prediction Using Hybrid Approaches with Gradient-Specific Optimization," Forecasting, MDPI, vol. 6(2), pages 1-17, April.
  44. Prof. Reepu & Prof.Bijesh Dhyani & Ms. Ayushi & Dr. Sudhi Sharma & Dr. Manish Kumar, 2022. "Predictive Modelling Of Select Cryptocurrencies And Identifying The Best Suitable Model - With Reference To Arima And Anns," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 11-19, December.
  45. Vaia I. Kontopoulou & Athanasios D. Panagopoulos & Ioannis Kakkos & George K. Matsopoulos, 2023. "A Review of ARIMA vs. Machine Learning Approaches for Time Series Forecasting in Data Driven Networks," Future Internet, MDPI, vol. 15(8), pages 1-31, July.
  46. Liu, Mingxi & Li, Guowen & Li, Jianping & Zhu, Xiaoqian & Yao, Yinhong, 2021. "Forecasting the price of Bitcoin using deep learning," Finance Research Letters, Elsevier, vol. 40(C).
  47. Konstantinos-Leonidas Bisdoulis, 2024. "Assets Forecasting with Feature Engineering and Transformation Methods for LightGBM," Papers 2501.07580, arXiv.org.
  48. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "How well do investor sentiment and ensemble learning predict Bitcoin prices?," Research in International Business and Finance, Elsevier, vol. 64(C).
  49. Laszlo Vancsura & Tibor Tatay & Tibor Bareith, 2024. "Investigating the Role of Activation Functions in Predicting the Price of Cryptocurrencies during Critical Economic Periods," Virtual Economics, The London Academy of Science and Business, vol. 7(4), pages 64-91, December.
  50. Weige Huang & Xiang Gao, 2023. "Forecasting Bitcoin Futures: A Lasso-BMA Two-Step Predictor Selection for Investment and Hedging Strategies," SAGE Open, , vol. 13(1), pages 21582440231, January.
  51. Tomas Pečiulis & Nisar Ahmad & Angeliki N. Menegaki & Aqsa Bibi, 2024. "Forecasting of cryptocurrencies: Mapping trends, influential sources, and research themes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1880-1901, September.
  52. Xu Gong & Mengjie Li & Keqin Guan & Chuanwang Sun, 2023. "Climate change attention and carbon futures return prediction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1261-1288, September.
  53. Wei Liu & Yoshihisa Suzuki & Shuyi Du, 2024. "Forecasting the Stock Price of Listed Innovative SMEs Using Machine Learning Methods Based on Bayesian optimization: Evidence from China," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 2035-2068, May.
  54. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
  55. Artee Bhadauria & Rohit Rajwanshi & Richa Agarwal, 2024. "The crypto-market bubble burst: identifying the risk factors that prohibit cryptocurrency investments," SN Business & Economics, Springer, vol. 4(5), pages 1-30, May.
  56. Kerolly Kedma Felix do Nascimento & Fábio Sandro dos Santos & Jader Silva Jale & Silvio Fernando Alves Xavier Júnior & Tiago A. E. Ferreira, 2023. "Extracting Rules via Markov Chains for Cryptocurrencies Returns Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1095-1114, March.
  57. Wang, Yang & Xiuping, Sui & Zhang, Qi, 2021. "Can fintech improve the efficiency of commercial banks? —An analysis based on big data," Research in International Business and Finance, Elsevier, vol. 55(C).
  58. Alexey Yu. Mikhaylov & Vikas Khare & Solomon Eghosa Uhunamure & Tsangyao Chang & Diana I. Stepanova, 2023. "Bitcoin Price Short-term Forecast Using Twitter Sentiment Analysis," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 123-137, August.
  59. Jinxin Wang & Chaoran Gao & Manman Wang & Yan Zhang, 2023. "Identification of Urban Functional Areas and Urban Spatial Structure Analysis by Fusing Multi-Source Data Features: A Case Study of Zhengzhou, China," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
  60. Mengkun Liang & Renjing Guo & Hongyu Li & Jiaqi Wu & Xiangdong Sun, 2023. "T-LGBKS: An Interpretable Machine Learning Framework for Electricity Consumption Forecasting," Energies, MDPI, vol. 16(11), pages 1-27, May.
  61. Junfeng Kang & Xinyi Zou & Jianlin Tan & Jun Li & Hamed Karimian, 2023. "Short-Term PM 2.5 Concentration Changes Prediction: A Comparison of Meteorological and Historical Data," Sustainability, MDPI, vol. 15(14), pages 1-24, July.
  62. Jirou, Ismail & Jebabli, Ikram & Lahiani, Amine, 2025. "A hybrid deep learning model for cryptocurrency returns forecasting: Comparison of the performance of financial markets and impact of external variables," Research in International Business and Finance, Elsevier, vol. 73(PA).
  63. Yan Guo & Dezhao Tang & Wei Tang & Senqi Yang & Qichao Tang & Yang Feng & Fang Zhang, 2022. "Agricultural Price Prediction Based on Combined Forecasting Model under Spatial-Temporal Influencing Factors," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
  64. Liu, Yujun & Li, Zhongfei & Nekhili, Ramzi & Sultan, Jahangir, 2023. "Forecasting cryptocurrency returns with machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
  65. 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.
  66. Xiang Gao & Weige Huang & Hua Wang, 2021. "Financial Twitter Sentiment on Bitcoin Return and High-Frequency Volatility," Virtual Economics, The London Academy of Science and Business, vol. 4(1), pages 7-18, January.
  67. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
  68. Walid Ben Omrane & Khaled Guesmi & Qi Qianru & Samir Saadi, 2023. "The high-frequency impact of macroeconomic news on jumps and co-jumps in the cryptocurrency markets," Annals of Operations Research, Springer, vol. 330(1), pages 177-209, November.
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