humarb ResearchMethods and position preprint · 011 · Preprint published on Zenodo

Ranking Cross-Venue Funding Carries under an Estimation-Error Budget

Scenario ranking, joint realization error, and post-selection evaluation

Perpetual futuresFunding ratesEstimation errorRankingPost-selection biasForecast evaluation
Abstract173 words

A current scenario is an error budget—not a probability of profit.

Cross-venue funding-carry rankings compare noisy current scenarios, and selecting the maximum can change the relevant error distribution. We derive an accounting error budget: for current scenario value S0, realized net accounting Pi and overestimation D=S0-Pi, Pi>0 if and only if D

阅读中文摘要

跨场所资金费排序比较的是含噪声的当前情景,而选择最大值本身会改变需要评估的误差分布。本文从同一数量、同一事件与成本合同出发,推导误差预算恒等式:设当前净情景值为 S0,后续闭合头寸净核算为 Π,净高估误差为 D=S0-Π,则 Π>0 当且仅当 D<S0。因此,S0 是头寸在符号改变前能够承受的全部联合高估,而不是收益概率、条件期望或置信区间。本文进一步区分描述性 S0 排序与包含损失厌恶和资本占用的决策目标 J;联合误差分布或资本合同缺失时,J 为不可用,而不是零。

回顾性样本包含 9,192 条连续小时资金费记录和 3,720 条时间外预测。上一已结算费率基准在六个场所—资产序列上的 MAE 为 0.0126—0.0298 个基点。校准期 90% 中央区间在 Hyperliquid ETH 时间外样本中的覆盖率仅为 68.39%;单侧校准规则对全部时间外候选的覆盖率为 94.03%,对选中最大值的覆盖率降至 88.39%。前向五条完整纸面路线的当前与后续值均为负,XMR 因深度不足保留为未完成。全部合并金额采用一比一 USDC/USD parity 情景,不是已实现的账户盈亏。本文不构成投资建议。

下载一页中文摘要 PDF

08Original vector figures
22Numbered equations
26Checked bibliography records
3,720Holdout predictions
Paper contents

I · Research question

Ranking by funding gap is not ranking by complete scenario value.

Current rates, order books, funding schedules, valuation prices and fees describe a conditional scenario. Future rates, exit basis and execution costs need not remain unchanged. Selecting the largest displayed spread adds a second problem: the selected estimate belongs to a different error population from the full candidate set.

The research question is deliberately narrow: how should current cross-venue funding scenarios be ranked, how much joint overestimation can a selected scenario tolerate, and what additional evidence is required before that ranking becomes a defensible decision rule?

Research 01 measures executable net carry; Research 02 frames net-carry evidence; Research 10 supplies the event-time ledger. Research 11 begins after that ledger closes and studies its error budget and selection layer.

Read Research 02: Framing Net Carry

II · Framework

One accounting boundary. Two distinct ranking layers.

Current scenario and realization error
S0 = C0 + B0 − X0 − Φ0 − O0
D = S0 − Π  ⇒  (Π > 0 ⇔ D < S0)
I

Current scenario baseline

Complete scenarios share quantity, currency and reporting basis, holding view, event schedule, fee basis and information version. Same-book funding, basis, crossing, fees and other costs enter once.

S₀ ranking
II

Joint realization error

The error budget decomposes funding-rate, funding-price, rate–price interaction, basis, crossing and fee differences. Missing evidence remains NA; covariance is never assumed to be zero.

D decomposition
III

Preference-dependent decision layer

J requires the joint error distribution, a loss weight and a declared capital-hour contract. If these inputs are unavailable, J is unavailable—not zero and not a reason to suppress the descriptive S₀ ranking.

J = NA here
IV

Evaluation after selection

Chronological holdouts, interval scores, Newey–West comparisons and Holm adjustment are reported alongside selected-subset errors. Overall marginal coverage does not automatically cover the selected maximum.

Post-selection
Research decision objective, not validated here
J = E[Π | Ft] − λE[(−Π)+ | Ft] − ρA

Expectations require a joint distribution; A is reserved capital integrated over time. λ and ρ are not calibrated in this paper.

NA is not zero, and marginal coverage is not selected coverage.

A missing book, record or official account cash flow cannot be replaced by zero. A verified empty event set is different from a scheduled event with missing evidence. Combined amounts use an explicit one-for-one USDC/USD parity scenario, not realized account P&L.

III · Figures

The identity holds; calibration and selection require separate evidence.

Figure 1

The scenario value is the total overestimation a position can tolerate before its sign changes. Algebraic boundary; no probability mass or coverage claim.

Figure 2

Previous-settled MAE is 0.0126–0.0298 basis points across six series. Source: 3,720 holdout predictions; funding components, not complete P&L.

Figure 3

Calibration-period 90% intervals fail on later Hyperliquid ETH observations. Nominal coverage is not a per-route promise.

Figure 4

The one-sided rule covers 94.03% of all holdout counterfactuals but 88.39% of selected maxima. Fixed-notional funding proxies only.

Figure 5

Current costs reorder the candidates. Five subsequent public paper proxies are negative; XMR is explicitly NA. Source: 2026-11-03 22:41/23:00 UTC.

Figure 6

Basis improvements and deteriorations dominate different routes. Components reconcile to D with a maximum residual of 9.1×10−15 scenario units.

IV · Evaluation and robustness

Funding-rate evidence is not complete strategy evidence.

The paper uses chronological prediction only to measure funding-rate components. It does not convert those results into a complete backtest, a probability of profit, or a calibrated decision objective. Every attempted specification remains in the reproduction outputs.

Chronological component evaluation

There are 3,720 holdout predictions across six venue–asset series. The analysis reports MAE/RMSE, 23-lag Newey–West Diebold–Mariano tests, interval scores, Kupiec and Christoffersen diagnostics, and Holm-adjusted families.

Robustness and post-selection checks

Two holdout halves, two venues, three assets, five rolling windows, absolute and squared loss, four dependence lags, and four one-sided levels are retained. Selected maxima are reported separately from all candidates.

Prospective requirement, not completed D3

A future confirmation must freeze D0/D1/D2/D3, purge overlapping labels, preserve shared-event blocks, and score complete capital paths. The present retrospective sample and one-hour snapshot do not meet that standard.

Evidence boundary
S0: computable  ·  D: auditable ex post  ·  J: NA

The first two statements concern accounting and measurement. The third requires joint error, loss preference and capital inputs that this study does not have.

V · Limitations

Public proxies and reproducible arithmetic—not live performance.

  • Decision scope. No joint closed-position error distribution, λ, ρ, capital contract, positive-expectation estimate, market-wide optimum, or validated J is supplied.
  • Statistical scope. The retrospective sample covers two venues, three continuing assets and about two months. Asymptotic tests and chosen lags do not eliminate regime shift or shared-event dependence.
  • Execution scope. Public-book VWAP excludes queue position, reaction, hidden liquidity, partial fills, financing, transfer, liquidation and account-specific fees.
  • Currency and evidence scope. Combined amounts are parity-denominated scenario units, not realized USD, USDT or USDC account cash. Public oracle/mark snapshots are not official account funding records.
  • Protocol and review scope. The forward snapshot is locally hashed, not externally preregistered. Internal multi-role review and local similarity screening are not external peer review or commercial plagiarism certification.

This paper is for research and methodological information only. It does not provide investment, legal, accounting, or tax advice; does not recommend any trade, venue, leverage, or position size; and does not promise income, execution, capital protection, or protection from liquidation.

VI · Conclusion

A testable error budget—not a validated arbitrage recommendation.

The exact contribution is a reconciliation rule: Π > 0 if and only if D < S0. The evaluation contribution is equally important: current-scenario ranking remains separate from decision-ready J selection, and selected-subset error remains visible rather than hidden inside a full-candidate average.

The appropriate next step is a frozen, complete forward evaluation—not another universal threshold. Validate the scenario and error ledger first, estimate joint error only on isolated data, and test J on locked capital paths only after the required distributions and preferences exist.

VII · Citation

Cite the error budget.
Preserve the evidence boundary.

Cite the concept DOI 10.5281/zenodo.23938429; the version DOI 10.5281/zenodo.23938430 identifies v1.

Concept DOI10.5281/zenodo.23938429Version DOI · 10.5281/zenodo.23938430  |  Record · zenodo.org/records/23938430  |  Status · preprint, not peer reviewed

Liu, H. (2026). Ranking cross-venue funding carries under an estimation-error budget [Preprint]. humarb Research. https://doi.org/10.5281/zenodo.23938429

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