Strategy: Polymarket · Probability Mean Reversion

SkillDev tools

Use when a Polymarket outcome appears to overreact and then stall away from recent filled-price range.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Strategy: Polymarket · Probability Mean Reversion skill

What this skill tells your AI

The instructions your AI receives, as published by superior-trade/superior-skills in skills/probability-mean-reversion/SKILL.md and read by ahel’s review.

When to use

Use this when someone asks for fade, overreaction, mean reversion, range trading, panic buy, euphoria selloff, or probability jumps with weak follow-through.

What the agent should look for

  • Canonical Polymarket market from GET /context/markets?venue=polymarket.
  • A stable market with enough historical fills.
  • Probability significantly far from a rolling median.
  • Weak follow-through after the jump.
  • No fresh catalyst changing the thesis.
  • Enough time before resolution to allow drift back.

Backtest fit with filled data

Moderate fit. Filled TradeTick history can test whether probability moves have a measurable reversion pattern, while using actual fills as the execution proxy.

Limit: backtests cannot validate resting liquidity, spread paid, or what is missed in the maker queue.

Strategy logic

Enter when the outcome trades below a lower band and exit near the rolling median. If your implementation permits, do the inverse for above-band conditions when downside overextension appears.

Nautilus strategy shape

  • Keep a rolling window of trade prices.
  • Compute median and deviation thresholds.
  • Enter only after sufficient tick history is collected.
  • Exit on median reversion or max holding ticks.

Example strategyConfig

{
  "window_ticks": 40,
  "entry_deviation": 0.08,
  "exit_deviation": 0.02,
  "order_size": 10,
  "max_holding_ticks": 80
}

Iteration knobs

KnobEffect
window_ticksLarger windows produce a smoother baseline.
entry_deviationHigher values wait for stronger overreactions.
exit_deviationLower values demand tighter reversion before exit.
max_holding_ticksPrevents stale positions through stale conditions.

Failure modes

  1. Real information shocks rarely mean-revert.
  2. Markets near resolution can trend cleanly to 0 or 1.
  3. Low liquidity can create fake extremes.
  4. Backtests may look strong when spread and order-book pressure are ignored.

User-facing framing

"This is an overreaction fade. It works best in noisy markets without new decisive information. I’ll backtest it on filled prices first, then verify trade frequency and liquidity before suggesting live use."

Signals

GitHub stars
211
Forks
9
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
probability-mean-reversion
Source
github.com/superior-trade/superior-skills
Strategy: Polymarket · Probability Mean Reversion · ahel