@inproceedings{3db569c47c684376ac345fdf2e4da435,
title = "The Predictive Power of Bitcoin Halving: Assessing Price Implications",
abstract = "This study investigates the effect of Bitcoin mining reward halvings on price fluctuations and enhances prediction models by incorporating a novel factor termed {"}halving impact weight{"}. This weight quantifies the delayed influence of halving events on Bitcoin prices with an exponentially decaying model. Incorporating this factor significantly enhances forecast accuracy: Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) decrease by 12.05\% and 12.49\%, respectively. Our findings demonstrate the critical importance of accounting for mining reward halvings in predictive models of Bitcoin prices.",
keywords = "Bitcoin, Halving, LSTM, Prediction, Random Forest",
author = "Na Luo and Haolin Jia and Xingyue Liao and Bo Qin and Qianhong Wu and Sanxi Li",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE Global Blockchain Conference, GBC 2025 ; Conference date: 20-06-2025 Through 22-06-2025",
year = "2025",
doi = "10.1109/GBC60041.2025.11134454",
language = "英语",
series = "2025 IEEE Global Blockchain Conference, GBC 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2025 IEEE Global Blockchain Conference, GBC 2025",
address = "美国",
}