The Predictive Power of Bitcoin Halving: Assessing Price Implications
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.
Authors
- Haolin Jia (ORCID: https://orcid.org/0009-0006-8089-4906)
- Sanxi Li (ORCID: https://orcid.org/0000-0003-1576-1315)
- Qianhong Wu (ORCID: https://orcid.org/0000-0003-4604-1142)
- Xinwei Liao
- Xingqiang Lü (ORCID: https://orcid.org/0000-0003-2698-2770)
- Bo Qin
Institutions
- Renmin University of China (CN)
- Beihang University (CN)
Publication Details
- Published
- 2025-06-20
- DOI
- https://doi.org/10.1109/gbc60041.2025.11134454
- Primary Topic
- Blockchain Technology Applications and Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China