Microstructure/docs/PUBLIC_TRADE_PROTOCOL.md

Public aggregate-trade exploratory protocol

Evidence status

This protocol governs the first real-data research run built from the fixed, capped Binance Spot aggregate-trade sample already acquired for 2024-01-02. It is retrospective and exploratory, not a preregistered confirmatory study. The data availability, per-symbol coverage, and class balance were inspected before this document was frozen; model comparison and held-out results were not.

Every output must retain the PUBLIC_SAMPLE_PARTIAL evidence tier. The run may support a sample-specific data and predictability diagnostic, but it cannot support a claim about persistent alpha, statistical significance, execution, profitability, or capacity.

Question and hypotheses

The narrow question is whether recently observed aggregate-trade direction and size contain out-of-time information about the sign of the trade price 20 aggregate trades later.

• H0: the transparent model ladder does not improve held-out log loss over a historical-prior classifier in this capped sample.
• H1 (exploratory): causal signed-volume and trade-imbalance features improve held-out log loss relative to that prior.

All tested model rows are published. The final test is not used for feature, hyperparameter, calibration, or model selection. A favorable point estimate is not called significant; the block bootstrap is a dependence diagnostic, not a confirmatory p-value procedure.

Data and coverage policy

• Instruments are BTCUSDT and ETHUSDT, evaluated separately because the fixed 5,000-row caps produce different observed clock-time endpoints.
• The exact ingestion manifest and normalized part hashes are inputs to the run.
• Internal aggregate-trade IDs must be unique and step by one within each symbol; the availability clock must not reverse. Only after those checks may the derived research view assign one continuity epoch per symbol. Raw normalized rows remain unchanged.
• Exchange event time is the only historical availability proxy. No local receipt-time or colocated-latency claim is allowed.
• Tied exchange timestamps retain aggregate-trade-ID ordering and remain in the same time split.

Causal feature and label contract

At decision trade i, features may use trade i and earlier trades from the same verified continuity epoch:

• signed trade volume and absolute volume over 5, 20, and 100 trades;
• signed-volume imbalance over the same windows;
• trade count and event-time intensity;
• one-trade log return;
• realized trade-price volatility over 100 trades.

The target is 1 when the trade price at i + 20 is above the price at i, and 0 otherwise. The target trade ID and availability timestamp are serialized. Segment tails are right-censored. Feature-ready rows require the full longest lookback.

Evaluation

• Each instrument receives its own expanding time-ordered walk-forward plan.
• Configuration: 1,200 initial decision-time buckets, 400 validation buckets, 400 final-test buckets, 400-bucket steps, and a 20-bucket embargo.
• Label information ending at or after an evaluation boundary is purged.
• The model ladder is historical prior, unpenalized logistic regression, the declared L2 grid, and the declared shallow-tree grid.
• Selection metric is validation log loss. Calibration is trained only from the chronological training/calibration region.
• The primary H0/H1 diagnostic is the paired difference in held-out log loss: validation-selected model minus historical prior on identical row_id observations. It uses the same seeded resample draw for both models within each fixed, contiguous 40-trade block (twice the label horizon), separately by instrument. Five hundred draws, the seed, row count, block count, point difference, and percentile interval are serialized. Marginal per-model intervals are secondary and are never compared as a substitute for the paired loss difference.

Explicit exclusions

There is no contemporaneous bid/ask, depth, cancellation, queue, or local receipt-time history in this dataset. Therefore this run does not calculate:

• order-book imbalance, microprice, spread, or liquidity recovery;
• limit-fill probability or queue position;
• market/limit execution, fees-to-alpha conversion, P&L, or capacity.

Those analyses require continuous snapshot-plus-delta L2 epochs collected and validated separately.

Promotion criteria

This exploratory run cannot be promoted to FULL_DATA. A later confirmatory study must freeze its protocol before model outcomes are inspected, use multiple complete nontruncated dates, preserve adjacent untouched dates for final testing, report per-date and cross-instrument stability, and add continuous L2 evidence before making book-dependent or execution claims.