Arb signals & audit

PolyQuantLab continuously scans the Polymarket book for mispricings. Every signal we surface is logged to arb_audit_log (Postgres) at detection time, then reconciled to resolution outcome the instant the market closes. The aggregate is queryable via GET /v1/arb/audit/aggregate or browsable at the public audit page.

Four tiers

Tier	Trigger	Direction	What it claims
`logical`	`yes_ask + no_ask < $1.00`	BUY_BOTH	Math-guaranteed profit at resolution.
`endgame`	model says near-certain + dual-oracle agreement, in final 0–120 s	BUY_YES or BUY_NO	High empirical hit-rate from book-lag in the last seconds.
`stable`	probability-arb on the maker-zone book (fill ≥ $0.30)	BUY_YES or BUY_NO	Where the maker bot is parked — usually well-calibrated.
`stale`	probability-arb on a thin / deep book (fill < $0.30)	BUY_YES or BUY_NO	Deep mispricings, often already arbed by HFT.

The /v1/arb/live endpoint returns currently- firing opportunities across all four tiers in real time.

Audit record per detection

When the detector emits an opportunity, the following is logged before any user sees it:

Column	Type	Notes
`detected_at`	timestamptz	Wall-clock at detection.
`market_id`	text	The CLOB market hash.
`ticker` / `event_type`	text	`BTC` / `5m`, etc.
`tier`	text	`logical`, `endgame`, `stable`, `stale`.
`direction`	text	`BUY_YES`, `BUY_NO`, `BUY_BOTH`.
`fill_price`	numeric	Real ask we’d hit.
`model_yes_prob`	numeric	Our log-normal model’s P(YES).
`model_ev_per_share`	numeric	Net EV after entry fees.
`est_fee_per_share`	numeric	Polymarket 2026 taker fee.
`resolution_at`	timestamptz	When the market will resolve.

On resolution the settler joins to events.resolution_outcome and fills in:

Column	Type	Notes
`resolved_at`	timestamptz	Reconciliation time.
`resolved_outcome`	text	`yes_won` / `no_won`.
`realized_pnl_per_share`	numeric	`payoff − fill_price − est_fee`, computed correctly for each direction (BUY_YES, BUY_NO, BUY_BOTH).

Nothing is deleted. The aggregate you read from /v1/arb/audit/aggregate is unfiltered count(*), avg(realized_pnl_per_share), etc.

Calibration

The aggregate returns both avg_model_ev and avg_realized per tier so you can compare. A model whose avg_realized ≈ avg_model_ev is well-calibrated; the gap is the engine’s honest blind-spot. For BTC/ETH/SOL Up/Down markets across our entire log, the probability arb (stable + stale) tiers have realised ~zero edge — Polymarket’s maker bots are well-calibrated for crypto. The logical tier is positive by construction, and the endgame tier has shown ~95 % empirical win rate from book lag in the final seconds. Read more on the public audit page — same numbers, no signin required.

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Concepts

Recipes

Live data

Four tiers

Audit record per detection

Calibration

​Four tiers

​Audit record per detection

​Calibration

Four tiers

Audit record per detection

Calibration