Reverse-engineered where the high-edge wallets (edge_z > 2) on pm_short_term_trader_accuracy actually make their money. The naive “Binance leads, book lags, exploit the lag” thesis from short-term-accuracy and lag-probe failed M0 backtesting at 46% win rate. The real edge is not latency arb. This note replaces the strategy thesis.

Primary case: 0x75cc3b63a2f2423085e10706c78b494017b93ce1. Cross-validated on the other 8 wallets in the cohort.

headline

The book’s own structural under-pricing of residual volatility late in a 5-minute window is the edge — especially on the cheap-tail side. The book treats nearly-dead outcomes as deader than they are. BTC-vs-book lag is real (see lag-probe: p50 300 ms) but it isn’t what these wallets are harvesting.

what 0x75cc3b actually does — two lanes

Both lanes operate only in the last third of a 5-minute window (time_in_window > 0.66), 5m markets only, cross-asset (BTC + ETH + SOL + XRP).

Lane 1 — late-window longshot reversion

Buy at best-ask ≤ $0.30 when an outcome looks “almost dead.” The book over-prices the deadness; residual underlying volatility flips outcomes more often than the 5%-of-implied book suggests.

Dollar-weighted ROI by entry price band:

price bandROI
$0.00–0.10+132.8%
$0.10–0.30+25.0%
$0.30–0.50(decreasing)
$0.90–1.00~+1%

Monotonic from cheap to expensive.

The phase × price heatmap is the killer:

phase$0.00–0.10 ROI
late-window+222%
early-window−68%

Same band, same wallet, opposite sign. Timing is half the edge.

Lane 2 — late-window momentum-chase

When the book has bid an outcome up ≥ 2¢ in the last 30 s and we’re in the last third of the window, take the offer (cap ~$0.85).

  • Hit rate: 73.4%
  • Edge: +4.7¢

The book lags its own recent moves; consume the slow liquidity.

what was wrong about 0x75cc3b before

was believedactually
3,397 markets28,696 BUYs across 43,734 trades. pm_short_term_trader_accuracy.n_markets counts distinct outcomes touched, not trades.
BTC onlyBTC + ETH + SOL + XRP updown markets
Median entry 15% into windowMedian 41% for 5m, 44% for 15m — fairly uniform; edge is concentrated late, but trades are not
One strategyAt least two lanes (longshot + momentum), 5m-specific

generalizes — partially

walletpatternstrength
0xd189664cPUREST: 613 late-window 5m longshot trades at 9.4K PnL on $12K invested**strongest single-wallet validation
0x8c901f67, 0x20d2309c, 0xeebde7a0same pattern, weaker (0xeebde7a0 looks like spread-capturing MM)confirms lane 1
0x7523cafc, 0xb27bc932DIFFERENT strategy: favorites-only in 15m marketsat least 2 distinct edge-bearing strategies coexist in the cohort

what to avoid (per the data)

  • 15m BUY Up at any price — loses for every asset
  • 5m early-window low prices (early × $0–0.10 = −68% ROI)
  • 5m mid-window deep favorites — basically zero edge with capital tied up

strategy v2 implications

Redesign the bot around:

  • Signal source: book state + time-in-window. NOT Binance vs book.
  • Universe: cross-asset by default (BTC + ETH + SOL + XRP), 5m markets primarily.
  • Lanes: longshot reversion (price ≤ 0.85).
  • Infrastructure: less about Binance feed microseconds, more about staying connected to a fast Polymarket book feed and computing late-window reversal probabilities. The eu-west-2 colocation argument from short-term-accuracy still holds — we still need to be fast on the CLOB — but the signal is endogenous to the book, not the BTC tape.

This deprecates the M0 model from the lag-probe capture as the primary strategy. The lag measurement (p50 300 ms book-lags-Binance) is still a true fact about the market; it just isn’t where this cohort’s money comes from.

caveats

  • No external price tape used in this analysis — momentum was inferred from Polymarket’s own book activity. Whether “book lags its own activity” vs “book lags Chainlink/Binance” needs a synced feed to disambiguate.
  • Order-book depth/spread unobserved; only fills visible. Maker vs taker not distinguished — 0xeebde7a0’s 20+ trades/outcome suggests maker behavior (spread capture) rather than pure direction.
  • pm_trades is restricted to ~119 watched wallets; “momentum” computed over that subset is a proxy, not the full book.
  • 7-day observation window — niche cells (e.g. late deep-longshot, n=478) carry ~1–2¢ edge uncertainty per cell.