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Polymarket Twitter Cross Contagion Trader

Trades post-count bin markets by detecting cross-person contagion where one public figure posting heavily causes correlated figures to increase their rate. R...
通过检测跨人物传染,在后计数二元市场中进行交易,即当某位公众人物大量发帖时会带动相关人物提高发帖频率。
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未分类 clawhub v0.0.3 1 版本 100000 Key: 需要
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概述

Twitter Cross-Contagion Trader

> This is a template.

> The default signal detects cross-person posting correlation from market prices — remix it with real-time Twitter API monitoring, topic co-occurrence tracking, or network graph analysis of reply/quote-tweet chains.

> The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Public figures don't post in isolation. When Elon Musk enters a political debate, Trump often responds on Truth Social. When crypto crashes, both CZ and Vitalik spike their posting rates.

Markets price each person's bins independently. This skill exploits the cross-person correlation that markets miss.

Signal Logic

Phase 1: Detect Contagion

  1. Group all post-count bin markets by person
  2. Compute each person's "heat" — are the market prices shifted toward higher bins?
  3. Positive heat = market expects more posts than baseline (person is "hot")

Phase 2: Apply Contagion Coefficients

SourceTargetBetaWhy
---------------------------
ElonTrump0.15Political overlap, mutual commentary
TrumpElon0.12Elon reacts to executive orders
ElonVitalik0.08Crypto topic overlap
VitalikElon0.06Elon sometimes responds to ETH news
ElonCZ0.05Crypto/exchange overlap

Phase 3: Trade with Adjusted Conviction

When person A is hot and beta(A->B) > 0, boost conviction on person B's higher bins.

Remix Ideas

  • Real-time monitoring: Track actual post counts in real-time instead of inferring from market prices
  • Reply chain analysis: @-mention graphs show direct contagion paths
  • Topic clustering: NLP on recent posts to detect shared topics driving correlation
  • Dynamic beta: Re-estimate contagion coefficients weekly from observed data

Risk Parameters

ParameterDefaultNotes
---------------------------
Max position size$40 USDCPer market
Min market volume$1,000Standard filter
Max bid-ask spread10%Default threshold
Min days to resolution0Post-count markets are short-lived
Max open positions8Diversify across persons

Installation & Setup

clawhub install polymarket-twitter-cross-contagion-trader

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Cron is set to null — the skill does not run on a schedule until you configure it in the Simmer UI.

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only execute when --live is passed explicitly.

ScenarioModeFinancial risk
--------------------------------
python trader.pyPaper (sim)None
Cron / automatonPaper (sim)None
python trader.py --liveLive (polymarket)Real USDC

The automaton cron is set to null — it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.

Required Credentials

VariableRequiredNotes
---------------------------
SIMMER_API_KEYYesTrading authority — keep this credential private. Do not place a live-capable key in any environment where automated code could call --live.

Tunables (Risk Parameters)

All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes. They use SIMMER_-prefixed env vars so apply_skill_config() can load them securely.

VariableDefaultPurpose
----------------------------
SIMMER_MAX_POSITION40Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_VOLUME1000Min market volume filter (USD)
SIMMER_MAX_SPREAD0.10Max bid-ask spread (0.10 = 10%)
SIMMER_MIN_DAYS0Min days until market resolves
SIMMER_MAX_POSITIONS8Max concurrent open positions
SIMMER_YES_THRESHOLD0.38Buy YES if market price ≤ this value
SIMMER_NO_THRESHOLD0.62Sell NO if market price ≥ this value
SIMMER_MIN_TRADE5Floor for any trade (min USDC regardless of conviction)

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

  • PyPI: https://pypi.org/project/simmer-sdk/
  • GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
  • Publisher: hello@simmer.markets

Review the source before providing live credentials if you require full auditability.

版本历史

共 1 个版本

  • v0.0.3 当前
    2026-05-03 06:56 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
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腾讯云安全 (Sanbu)

安全,无风险
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