Polymarket Music Entertainment Trader
by @diagnostikon
Trades Polymarket prediction markets on music streaming milestones, album chart performance, Grammy nominations, concert tour revenues, and music industry de...
clawhub install polymarket-music-entertainment-traderπ About This Skill
name: polymarket-music-entertainment-trader description: 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. metadata: author: Diagnostikon version: '1.0' displayName: Music & Entertainment Trader difficulty: beginner
Music & Entertainment Trader
> This is a template. > The default signal is keyword discovery + Spotify Charts API momentum β 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 β as real-time demand signals for artist momentum. This creates an unusual information flow:
This skill trades:
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 β 100% at p=0/p=1)
3. Apply sentiment_bias() multiplier based on market type and artist category
4. Size = max(MIN_TRADE, conviction Γ bias Γ MAX_POSITION) β 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, BeyoncΓ©, 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 β 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% β conviction 34% Γ 1.2x = 41% β $6 position. Same market for a BeyoncΓ© milestone β 34% Γ 0.75x = 26% β $5 (floor, trade cautiously).
Remix Ideas
market.current_probability with stream velocity-implied probability β trade the divergence between real-time data and market priceMarket Categories Tracked
KEYWORDS = [
'Taylor Swift', 'Bad Bunny', 'BeyoncΓ©', '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 8β15% 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 48β72 hours before mainstream media coverage. Early entry on breakout markets captures the lag.Key Data Sources
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 β 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 β 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 β€ this value |
| SIMMER_NO_THRESHOLD | 0.62 | Sell NO if market price β₯ 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.
Review the source before providing live credentials if you require full auditability.