Expected Revenue, Risk, and Grid Impact of Bitcoin Mining: A Decision-Theoretic Perspective
Abstract
Most current assessments use ex post proxies that miss uncertainty and fail to consistently capture the rapid change in bitcoin mining. We introduce a unified, ex ante statistical model that derives expected return, downside risk, and upside potential profit from the first principles of mining: Each hash is a Bernoulli trial with a Bitcoin block difficulty-based success probability. The model yields closed-form expected revenue per hash-rate unit, risk metrics in different scenarios, and upside-profit probabilities for different fleet sizes. Empirical calibration closely matches previously reported observations, yielding a unified, faithful quantification across hardware, pools, and operating conditions. This foundation enables more reliable analysis of mining impacts and behavior.
Cite
@article{arxiv.2512.20518,
title = {Expected Revenue, Risk, and Grid Impact of Bitcoin Mining: A Decision-Theoretic Perspective},
author = {Yuting Cai and Ruthav Sadali and Korok Ray and Chao Tian},
journal= {arXiv preprint arXiv:2512.20518},
year = {2025}
}