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Probability Mean Reversion

核心功能为基于滚动中位数识别Polymarket市场的概率偏离,捕捉过度反应后的均值回补机会,通过进出场阈值、持仓时长等参数控制交易。典型场景包括恐慌买入、亢奋抛售、无催化剂的概率跳涨且跟进疲软的情况,需选择有足够历史成交、离结算时间充足的稳定市场。输入含市场标识及策略配置参数,输出交易信号;回测适配成交数据,但需注意信息冲击等失效模式。

superior-ai
superior-ai
热度 21.10
最近更新 2026-06-22 20:16:37
分类:数据依赖:第三方 API / 代码执行 / 内部调用大模型应用场景:数据处理 / 市场分析 / 财务

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add probability-mean-reversion
Metadata
name
probability-mean-reversion
description
Use when a Polymarket outcome appears to overreact and then stall away from recent filled-price range.
version
0.1.0
updated
"2026-06-17T00:00:00.000Z"

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

  • Exact market slug from POST /v3/markets/search.
  • 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.

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."