78 lines
4.4 KiB
Markdown
78 lines
4.4 KiB
Markdown
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# Findings — what works and what doesn't on Polymarket
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A research log of an honest attempt to find a systematic, automatable edge on
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Polymarket using public data. The short version: **almost nothing works** — the
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market is efficient — and the one thing that does isn't a money-printer, it's a
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detection signal.
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## The goal
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Find a repeatable way to make money on Polymarket: identify "smart money"
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wallets, copy them, farm rewards, or arbitrage — anything systematic and
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automatable from public data.
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## Scorecard
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| Approach | Verdict | Why |
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|----------|---------|-----|
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| **Copy high-win-rate wallets** | ❌ dead | Win rate was an illusion (see below). True rates ~50%. Flat-size copying backtested **−48%** over a week. |
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| **Rank by leaderboard / PnL** | ❌ dead | Raw PnL is variance; top wallets win ~50% and profit via sizing/timing you can't copy. |
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| **LP reward farming** | ❌ dead | The fat "thin-book" APRs are illusory — Polymarket **refunds unearned pool to the sponsor** when liquidity is low. Real yield is modest and adverse-selection-dominated. |
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| **Binary YES+NO arbitrage** | ❌ dead | Efficient — min observed sum was 1.001 (the spread). Closed instantly by the engine. |
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| **Multi-outcome logical arb** | ❌ dead | True partitions priced efficiently (min sum 0.999). Apparent "arbs" were non-exclusive market groupings. |
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| **Cross-venue arb (Polymarket↔Kalshi)** | ❌ dead | Venues agree to ~1¢; locking both legs costs **>$1 after fees**. Real gaps last ~seconds and are taken by bots. |
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| **Insider / sharp detection** | ✅ **works** | Statistical improbability (z-score of wins vs. odds) is a real, hard-to-fake edge signal. See `insider.py`. |
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## The big technical findings
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**1. Win rate on Polymarket is survivorship-biased — badly.**
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The platform only redeems *winning* shares; losing shares are worth $0 and sit
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unredeemed in `/positions` at `curPrice 0` forever, never entering
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`/closed-positions`. Measuring win rate over `/closed-positions` alone counts
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almost only winners. We saw a wallet read **90.6%** that was truly **48.3%**.
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A correct win rate must union both endpoints. *Lesson: a high reported win rate
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is a red flag for a measurement bug, not a sharp.*
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**2. Win rate ≠ profit, and PnL ≠ reliability.**
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A wallet winning 54% made millions; the all-time #1 wallet (43% win) was −$3.8M
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over 90 days. Profit comes from sizing and entry prices, not hit rate.
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**3. The market is efficient.** Six systematic public-data edges, all closed or
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illusory. There is no turnkey retail edge sitting in public data in 2026 —
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durable edge requires *speed/infrastructure* (arb bots), *private information*,
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or *getting paid to provide liquidity* (modest, adverse-selection-dominated).
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**4. The one real signal: statistical improbability (z-score).**
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Each bet entered at price `p` has an odds-implied win probability `p`. A wallet
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winning far more than `Σp` is beating the market's own pricing — measured as a
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z-score and one-sided p-value. This is the rigorous version of the edge metric
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the whole project was chasing. It distinguishes:
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- **Sharps** — high z, normal entry timing (skill over many bets).
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- **Insiders** — high z **+** late (pre-resolution) entry **+** fresh wallet.
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Plus **funding-cluster linking** (à la Bubblemaps / the 2026 *60 Minutes*
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investigation): trace each wallet's USDC funders on Polygon and link wallets
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that share a *personal* funding hub — judged by the funder's own outbound degree
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so shared exchanges don't false-link everyone. (See `insider.py`.)
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## Practical conclusion
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- **Don't** fund copy-trading, LP farming, or arb based on this work — we tested
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them and they don't clear.
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- **Do** use `insider.py`'s z-score as a rigorous "who actually has edge" filter,
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far better than leaderboard or win rate.
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- A genuine money-making edge has to come from *you* — a niche you understand
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better than the market — with tooling built around it, not from a public-data
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scanner.
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- **Legal note:** *detecting* suspected insider trading is fine; *trading on*
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material nonpublic information is illegal, and blindly following a suspected
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insider is not a safe strategy.
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## Repo layout
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- `insider.py` — the keeper: z-score/p-value detection, timing/freshness/sizing
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signals, and Alchemy funding-cluster ring detection.
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- `smart_money.py` — data foundation + dashboard (true-win-rate scanner).
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- `archive/` — the strategies that didn't work, kept for reference. See
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`archive/README.md`.
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