Polymarket Music Entertainment Trader

Trades Polymarket prediction markets on music streaming milestones, album chart performance, Grammy nominations, concert tour revenues, and music industry deals. Use when you want to capture alpha on entertainment markets using Spotify/Billboard data signals and artist momentum indicators.

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:

Market type	Bias	Why
Megastar fan markets (Taylor Swift, Beyoncé, BTS)	0.75x	Fan bias inflates YES; emotionally driven, high noise
Awards ceremonies (Grammy, Oscar, VMA)	0.85x	Fan voting + label politics = hard to model reliably
Streaming / chart milestones (Spotify, Billboard)	1.15x	Data available before market reprices — lean in
Emerging global genres (Afrobeats, K-pop, Latin)	1.20x	Systematically underweighted by US-centric retail traders
Other	1.00x	No systematic bias detected

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

Parameter	Default	Notes
Max position size	$15 USDC	Entertainment markets are retail-driven
Min market volume	$2,000	Lower bar; community markets matter
Max bid-ask spread	15%	Entertainment markets can be illiquid
Min days to resolution	7	Streaming data needs time to settle
Max open positions	10	Diversify across artists and categories

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.

Scenario	Mode	Financial risk
python trader.py	Paper (sim)	None
Cron / automaton	Paper (sim)	None
python trader.py --live	Live (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

Variable	Required	Notes
SIMMER_API_KEY	Yes	Trading 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.

Variable	Default	Purpose
SIMMER_MAX_POSITION	15	Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_VOLUME	2000	Min market volume filter (USD)
SIMMER_MAX_SPREAD	0.15	Max bid-ask spread (0.15 = 15%)
SIMMER_MIN_DAYS	7	Min days until market resolves
SIMMER_MAX_POSITIONS	10	Max concurrent open positions
SIMMER_YES_THRESHOLD	0.38	Buy YES if market price ≤ this value
SIMMER_NO_THRESHOLD	0.62	Sell NO if market price ≥ this value
SIMMER_MIN_TRADE	5	Floor 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: [e-mail]

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