Beyond Anonymous Order Flow: Wallet Identity as a Feature for Short-Horizon Return Prediction

Conventional public order-book data summarize trading without identifying the accounts behind it. Hyperliquid's Level-4 record also exposes persistent pseudonymous wallet addresses. We reconstruct full-depth books from consensus-ordered messages and evaluate wallet identity as a feature for short-horizon return prediction. The July 1-27, 2026 record covers 17.1 billion messages, 14.3 million aggressive orders by 147,113 wallets, and $84.3 billion in taker notional across ten markets. In the three model markets, notional-weighted ten-second markout rankings persist across adjacent ten-day windows (Spearman rho = 0.52); covariate-adjusted validation markouts reach 3.11 basis points in the top ventile. On a 100-millisecond grid, eleven features describing previously scored top-decile wallets raise one-second out-of-sample R2 from 10.88% to 12.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-03
DOI
https://doi.org/10.48550/arxiv.2611.05218
Primary Topic
Financial Markets and Investment Strategies
Type
preprint
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preprint

Beyond Anonymous Order Flow: Wallet Identity as a Feature for Short-Horizon Return Prediction

Jingqiu Ding, Daojing Zhai
arXiv (Cornell University)
Financial Markets and Investment Strategies
preprint

Beyond Anonymous Order Flow: Wallet Identity as a Feature for Short-Horizon Return Prediction

Jingqiu Ding, Daojing Zhai
preprint en

Abstract

Conventional public order-book data summarize trading without identifying the accounts behind it. Hyperliquid's Level-4 record also exposes persistent pseudonymous wallet addresses. We reconstruct full-depth books from consensus-ordered messages and evaluate wallet identity as a feature for short-horizon return prediction. The July 1-27, 2026 record covers 17.1 billion messages, 14.3 million aggressive orders by 147,113 wallets, and $84.3 billion in taker notional across ten markets. In the three model markets, notional-weighted ten-second markout rankings persist across adjacent ten-day windows (Spearman rho = 0.52); covariate-adjusted validation markouts reach 3.11 basis points in the top ventile. On a 100-millisecond grid, eleven features describing previously scored top-decile wallets raise one-second out-of-sample R2 from 10.88% to 12.

arXiv (Cornell University)
Financial Markets and Investment Strategies
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Beyond Anonymous Order Flow: Wallet Identity as a Feature for Short-Horizon Return Prediction — Jingqiu Ding, Daojing Zhai · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS