Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction

TL;DR

This paper introduces MineROI-Net, a Transformer-based deep learning framework that predicts the profitability of Bitcoin mining hardware acquisitions, helping miners make data-driven timing decisions to reduce financial risks.

Contribution

It formulates hardware acquisition timing as a time series classification problem and develops MineROI-Net, a novel Transformer architecture tailored for profitability prediction in mining markets.

Findings

MineROI-Net achieves 83.7% accuracy in profitability classification.

The model attains 93.6% precision in detecting unprofitable periods.

It outperforms LSTM and TSLANet baselines across diverse market regimes.

Abstract

Bitcoin mining hardware acquisition requires strategic timing due to volatile markets, rapid technological obsolescence, and protocol-driven revenue cycles. Despite mining's evolution into a capital-intensive industry, there is little guidance on when to purchase new Application-Specific Integrated Circuit (ASIC) hardware, and no prior computational frameworks address this decision problem. We address this gap by formulating hardware acquisition as a time series classification task, predicting whether purchasing ASIC machines yields profitable (Return on Investment (ROI) >= 1), marginal (0 < ROI < 1), or unprofitable (ROI <= 0) returns within one year. We propose MineROI-Net, an open source Transformer-based architecture designed to capture multi-scale temporal patterns in mining profitability. Evaluated on data from 20 ASIC miners released between 2015 and 2024 across diverse market regimes, MineROI-Net outperforms LSTM-based and TSLANet baselines, achieving 83.7% accuracy and 83.1% macro F1-score. The model demonstrates strong economic relevance, achieving 93.6% precision in detecting unprofitable periods and 98.5% precision for profitable ones, while avoiding misclassification of profitable scenarios as unprofitable and vice versa. These results indicate that MineROI-Net offers a practical, data-driven tool for timing mining hardware acquisitions, potentially reducing financial risk in capital-intensive mining operations. The model is available through: https://github.com/AMAAI-Lab/MineROI-Net.