polymarket-equity-markets-traderTrades Polymarket prediction markets on stock index milestones, major IPOs, earnings surprises, analyst upgrades, and company-specific financial events. Expl...
Install via ClawdBot CLI:
clawdbot install diagnostikon/polymarket-equity-markets-traderGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://pypi.org/project/simmer-sdk/Audited Apr 16, 2026 · audit v1.0
Generated Mar 21, 2026
An agent uses the skill to trade Polymarket markets on S&P 500 earnings beats during peak seasons like October, exploiting the 73-75% historical beat rate mispriced by retail as 50-50. It applies equity bias multipliers for large-cap tech (e.g., Nvidia at 1.25x) and calendar timing (1.20x) to size positions, targeting markets with high conviction and low spreads.
During quarter-start months like January, the agent trades index milestone markets (e.g., S&P 500 reaching a level) by leveraging the 20-60 minute lag between futures repricing after CPI/FOMC data and Polymarket updates. It uses a 1.15x market type multiplier and 1.10x calendar multiplier to exploit timing inefficiencies in pre-market hours.
The agent identifies overpriced crash prediction markets (e.g., S&P 500 falling 20% by a date) where retail fear anchors prices to 15-30% despite low base rates. It applies a 0.75x dampening multiplier to reduce position sizes or skip trades, focusing on more reliable earnings or index opportunities instead.
For markets on IPOs or corporate events like stock splits, the agent uses lower multipliers (0.85x for IPOs, 0.90x for dividends) due to higher uncertainty. It sizes positions conservatively, prioritizing markets with clear earnings or macro edges to maintain profitability amid variable timing and banker influences.
A firm deploys this skill in automated trading bots to capitalize on structural edges in Polymarket, generating profits from earnings base rate mispricing and macro timing lags. Revenue comes from consistent returns on trades, scaled across multiple agents and markets during high-density catalyst periods.
A hedge fund integrates the skill as a complementary strategy to traditional equity trading, using it to exploit retail inefficiencies in prediction markets for additional alpha. Revenue is derived from enhanced portfolio returns, particularly during earnings seasons and macro events, with risk managed through position capping.
A company offers this skill as a SaaS tool to clients, providing real-time trading signals and bias adjustments for Polymarket based on earnings and macro data. Revenue streams include subscription fees for access to the skill's logic and automated trade execution features.
💬 Integration Tip
Ensure the agent has access to real-time market data for accurate timing and set MAX_POSITION and MAX_SPREAD parameters to manage risk according to user capital and tolerance.
Scored Apr 19, 2026
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财务分析 CLI 技能 - 财报分析、股票估值、风险评估