probability-mean-reversion

Strategy: Polymarket · Probability Mean Reversion

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

Knob	Effect
window_ticks	Larger windows produce a smoother baseline.
entry_deviation	Higher values wait for stronger overreactions.
exit_deviation	Lower values demand tighter reversion before exit.
max_holding_ticks	Prevents 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.