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Polymarket up/down crypto markets — what actually has edge (honest findings)

Companion to the polymarket-updown-microstructure dataset. 2026-06-25.

This is a negative-results report, written to the standard that matters on an efficient venue: every edge claim is graded against the price you could actually transact at, not win-rate. On a market where the ask already encodes P(win), a high win-rate is not edge — edge_real = realized_WR − avg_price_paid is.

TL;DR

Across an exhaustive search of taker signals, a full physics-regional sweep of the maker side, an active cancel-race simulation, and replication against two independent external corpora, no signal-based strategy clears the realizable bar — taker or maker, passive or active. The informed flow leads the settlement oracle, so even a perfect, zero-latency oracle-based maker cancel does not help. What edge exists on this venue belongs to actors racing inside the inter-trade gap on non-public signals; it is not reachable from price/oracle data, at any latency we measured.

1. Method

  • edge_real = (won ? 1 : 0) − price_paid, per fill, bootstrap-CI'd.
  • Realizable (fillable) lens: a backtest "fill" counts only if a real trade print corroborates it (tape) or the quote survives our measured latency (persistence). Paper-fills at the displayed quote overstate edge ~10× via fill self-selection (you fill the losers, get rejected on the winners).
  • Ground-truth resolution from the settlement oracle, never from spot capture.
  • Calibration anchor: a strategy with a known live edge_real ≈ −0.004 reproduces to that value under the lens before any verdict is trusted.

2. Taker side — closed

An exhaustive grid (5,161 configurations: entry-timing × price-band × move × fade/decisive, across BTC/ETH/SOL/XRP, 5m/15m) graded on the realizable lens, then an adversarial verification stage (pooled-CI + persistence-agreement + date-holdout OOS):

  • The overfit cells evaporate under pooling (a family at +0.12 on n≈50 per cell is −0.017 pooled to n=1752).
  • Most apparent survivors die on persistence-vs-tape disagreement (tape says +, the resting book says −: the fills are phantom/adverse).
  • Exactly one configuration survived the full gauntlet, and it was carried entirely by a single coin at n=63 — a pocket, not an edge — and fires ~1×/day (economically negligible even if real).

Live confirmation: every directional taker we shipped died live (momentum, entropy, velrider, flip), each time because the backtest measured corr(signal, observed price) while live fills self-select into the losing side.

3. Maker side — no physics region

The passive (post-and-rest) maker, simulated against the real trade tape (same adverse selection a live maker eats), across 17 physics regions (favorite/underdog × distance-to-strike in bps × realized-σ × seconds-to-close):

region (favorite) bid P(win | fill) gap edge_real
dist <20bp, ≤60s 0.957 85.4% −10pp −0.089
dist <10bp, ≤60s 0.904 70.8% −20pp −0.179
dist <5bp, ≤60s 0.704 44.2% −26pp −0.227

Zero of 17 regions are positive. A resting bid always fills ~10–20pp below its true win probability — you are filled precisely when price is moving against you. The rebate (hundredths of a cent) cannot close a 10–20pp gap. This holds near and far from strike, early and late.

4. The cancel race — also closed

The passive maker is adversely selected everywhere, so the active maker's hope is to cancel an about-to-be-adverse quote before the informed taker hits it. We simulated exactly that on the microsecond book-delta firehose: post the favorite bid, fire a cancel when the oracle-fair drops below the bid, and let the cancel land L ms later. Sweeping L from 0 (perfect) to ∞ (never cancel):

cancel latency edge_real $ROI
0 ms (perfect) −0.1898 −42.4%
190 ms (ours) −0.1897 −42.3%
∞ (never cancel) −0.1894 −42.3%

The cancel does nothing — not even at 0 ms. This is not a "we lose the latency race" result; it is sharper. The cancel signal fires too late: the informed taker hits the bid before the data-streams oracle reflects the move. The adverse flow leads the oracle, so no oracle-based cancel can help at any latency. The only untested variant is a flow-based cancel (detect the informed taker mid-arrival and pull within the inter-trade gap) — which is the same sub-latency race a live attempt already lost. Maker is closed: passive (no region) and active (cancel useless).

5. External replication (independent corpora)

  • Academic ("Who Wins and Who Loses in Prediction Markets", 588M trades): ~70% of users lose; winners provide liquidity with limit orders, losers take liquidity with market orders; only ~12% of top winners beat a coin-flip benchmark and ~60% of "lucky winners" become losers out-of-sample.
  • Other people's bots (a public arena of 4.77M paper trades, gamma-resolved): taker edge_real −0.031 / ROI −6.0%; maker −0.136 / ROI −8.9%. Even the maker families with positive edge_real still lose on realized ROI once fees and early exits are counted.

Both land where our own data does: the taker space is closed; the maker space only opens on execution speed.

6. Takeaway for anyone using this dataset

Grade against the transactable price. If you find a +edge in a backtest here, before believing it: (1) pool across coins to kill multiple-comparison luck, (2) require the persistence lens to agree with the tape lens, (3) hold out by date, (4) check it isn't a once-a-day pocket. We did, on everything, and the honest answer is that the signal is already in the price.