Outcome-Classified Precision Auditing of Filter Rules in Algorithmic DEX Trading: Evidence from 2,400 Rejection Events

Arati Kamat

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Abstract: This paper reports a precision audit of a production filter stack against a 13-day window of post-rejection forward-market observations on Solana DEX trading (2026-04-10 to 2026-04-23, UTC). The audit yielded 99,510 follow-up samples across 2,402 unique rejection events spanning eight active filter rules. We classify each event under a five-tier outcome rule and report per-filter distributions. The descriptive result is a save-to-miss ratio of 3.7 : 1 (418 windowed measured-drawdown saves against 112 misses). This ratio is a descriptive count, not by itself evidence of filter skill: a fair-game price path also reaches a 50 percent drawdown before a 100 percent rise more often than the reverse, and a rebuilt analysis supersedes it. Correction (October 2026): I withdraw the early-death tier, the wider 14.8 : 1 ratio that rested on it, and the matched lifecycle comparison (48.9 versus 57.6 percent of mints reaching the gone state). In 1,235 of the 1,236 single-sample "early-death" events the same token was rejected again about 10 minutes later and the tracker restarted its record, so these events are tracker artefacts, not token deaths, and gone is a tracker state, not confirmation of a rug pull. I also withdraw the claim that every adequately sampled filter is individually net-positive (filter_7 has 3 saves and 3 misses). Per-filter estimates may be affected because follow-up records are keyed by token rather than by rejection decision. Details are in the correction notice on page 1.

Date: 2026-07, Revised 2026-10
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