Music & Entertainment Trader

> This is a template.

> The default signal is keyword discovery + Spotify Charts API momentum — remix it with Billboard chart position tracking, TikTok trending audio API, Apple Music chart feeds, or social media velocity metrics for artist momentum.

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

Strategy Overview

Record labels now monitor Polymarket the way Wall Street monitors stocks — as real-time demand signals for artist momentum. This creates an unusual information flow:

• Artists/labels with inside momentum push prices UP before numbers confirm
• Retail fans bid on emotional attachment, often overpaying for beloved artists
• Data-driven traders can fade fan-driven overpricing and capture industry-informed flows

This skill trades:

• Streaming milestones — First-week equivalents, billion-stream thresholds
• Chart performance — Billboard 200 #1, Hot 100 chart positions
• Awards — Grammy nominations/wins, VMAs, AMAs outcomes
• Tour revenue — Gross threshold markets for major arena tours
• Industry deals — Catalog sales, platform launches, licensing deals

Signal Logic

Default Signal: Conviction-Based Sizing with Sentiment Bias

1. Discover active music/entertainment markets on Polymarket
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply sentiment_bias() multiplier based on market type and artist category
4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAX_POSITION
5. Skip markets with spread > MAX_SPREAD or fewer than MIN_DAYS to resolution

Sentiment Bias (built-in, no API required)

Different market types have systematic mispricing patterns in music. sentiment_bias() adjusts conviction based on known retail behavior:

Example: Afrobeats streaming milestone at 25% → conviction 34% × 1.2x = 41% → $6 position. Same market for a Beyoncé milestone → 34% × 0.75x = 26% → $5 (floor, trade cautiously).

Remix Ideas

• Spotify Charts API / Chartmetric: Replace market.current_probability with stream velocity-implied probability — trade the divergence between real-time data and market price
• TikTok Trending: Viral audio as leading indicator for streaming momentum (48–72h lag to market)
• Ticketmaster/StubHub: Secondary ticket prices as proxy for tour gross markets
• RIAA certification tracker: Monitor certifications approaching milestone thresholds

Market Categories Tracked

KEYWORDS = [
    'Taylor Swift', 'Bad Bunny', 'Beyoncé', 'Drake', 'Kendrick',
    'Spotify', 'Billboard', 'Grammy', 'streaming', 'album',
    'chart', 'tour', 'concert', 'certification', 'RIAA',
    'K-pop', 'Afrobeats', 'Latin music', 'country', 'TikTok music',
    'music catalog', 'record label', 'music deal',
]

Risk Parameters

Behavioral Edge

Fan Bias

Music fans are strongly emotionally attached. For beloved artists (Taylor Swift, BTS), markets consistently overprice YES outcomes by 8–15% vs streaming data expectations. Short-term this means NO positions on fan-favorite markets are structurally profitable.

Recency Momentum

Conversely, artists trending hard on TikTok are underpriced for 48–72 hours before mainstream media coverage. Early entry on breakout markets captures the lag.

Key Data Sources

• Spotify Charts: https://charts.spotify.com/charts/overview/global
• Billboard API: https://www.billboard.com/charts/
• Chartmetric: https://chartmetric.com/ (paid, powerful)
• RIAA Database: https://www.riaa.com/gold-platinum/

Installation & Setup

clawhub install polymarket-music-entertainment-trader

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Runs every 30 minutes (/30 *). Chart data updates weekly; streaming data daily. No need for tight polling.

Safety & Execution Mode

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

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

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.

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.