# Forecasting Cryptocurrency Staking Rewards

arXiv: https://arxiv.org/abs/2401.10931 · HTML: https://mlsanity.com/paper/2401.10931/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 20 references that are in the map.
- First posted on arXiv 16 Jan 2024.

## Builds on (most cited first, 2 of 2)

- [Reap the Harvest on Blockchain: A Survey of Yield Farming Protocols](https://mlsanity.com/paper/2210.04194/) (2022)
- [Staking Pools on Blockchains](https://mlsanity.com/paper/2203.05838/) (2022)

## Abstract (arXiv)

This research explores a relatively unexplored area of predicting cryptocurrency staking rewards, offering potential insights to researchers and investors. We investigate two predictive methodologies: a) a straightforward sliding-window average, and b) linear regression models predicated on historical data. The findings reveal that ETH staking rewards can be forecasted with an RMSE within 0.7% and 1.1% of the mean value for 1-day and 7-day look-aheads respectively, using a 7-day sliding-window average approach. Additionally, we discern diverse prediction accuracies across various cryptocurrencies, including SOL, XTZ, ATOM, and MATIC. Linear regression is identified as superior to the moving-window average for perdicting in the short term for XTZ and ATOM. The results underscore the generally stable and predictable nature of staking rewards for most assets, with MATIC presenting a noteworthy exception.