Polymarket Supply Chain Trader

Trades Polymarket prediction markets focused on supply chain disruptions, port congestion, shipping delays, commodity prices, and logistics outcomes. Use when you want to capture alpha on global trade flow events, raw material price markets, and demand spike predictions.

Supply Chain & Logistics Trader

This is a template.
The default signal is keyword-based market discovery (shipping, port, logistics, commodity, supply chain) — remix it with freight index APIs (Baltic Dry Index), satellite AIS vessel tracking data, or real-time port authority feeds.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Supply chain prediction markets are among the most underserved categories on Polymarket. This skill identifies and trades markets related to:

• Port congestion — Rotterdam, Suez Canal, LA/Long Beach delays
• Commodity prices — Brent crude, steel, lithium thresholds
• Demand spikes — GPU/chip shortages, EV battery supply
• Company logistics — Tesla delivery delays, Maersk shipping times, Amazon Prime SLAs

Research shows prediction markets can reduce supply chain forecasting errors by 20–50% vs traditional methods (CFTC data). This makes these markets both tradable AND informative.

Signal Logic

Default Signal: Conviction-Based Sizing with Disruption Bias

1. Discover active supply chain markets on Polymarket
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply disruption_bias() — combines seasonal shipping cycles with commodity predictability
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

Disruption Bias (built-in, no API required)

disruption_bias() multiplies conviction using two independent factors simultaneously:

Factor 1 — Seasonal Shipping Cycle

Container shipping has a well-documented Q4 crunch (Oct–Dec) driven by pre-holiday inventory builds. Congestion and delay markets are structurally more likely to resolve YES in peak season.

Period	Multiplier	Why
Q4: Oct–Dec	1.25x	Peak season — pre-holiday crunch, port congestion likely
Q1: Jan–Mar	0.85x	Off-season — lower disruption probability
Apr–Sep	1.05x	Mild mid-year activity

Only applied when the question contains shipping/port/freight/cargo keywords.

Factor 2 — Commodity Predictability

Commodity type	Multiplier	Why
Crude oil / energy / LNG	1.20x	Most liquid commodity — highly modeled, information-rich
Semiconductors / chips / GPU	1.15x	Documented cycles, policy-driven — trackable
Lithium / cobalt / EV battery	1.15x	China-concentrated supply — export data publicly trackable
Chokepoints (Suez, Red Sea, Panama)	1.10x	Geopolitical risk well-documented and persistent
Agricultural / grain / harvest	0.85x	Weather-dependent, high variance — hard to model

Combined multiplier capped at 1.40x. A Q4 container shipping market mentioning Suez would score 1.25 × 1.10 = 1.375x.

Remix Ideas

• Baltic Dry Index: BDI weekly change as direct conviction input — rising BDI = lean into shipping disruption YES
• AIS vessel tracking (MarineTraffic): Real vessel queue counts at LA/Long Beach as direct oracle for port congestion markets
• USDA crop reports: Trade agricultural supply markets in the 48h window before/after report release
• Port authority RSS feeds: Rotterdam, Singapore, Shanghai real-time congestion data as entry trigger

Market Categories Tracked

python

KEYWORDS = [
    'shipping', 'port', 'container', 'supply chain', 'logistics',
    'commodity', 'crude oil', 'Brent', 'natural gas', 'LNG',
    'steel price', 'lithium', 'cobalt', 'critical mineral',
    'semiconductor', 'chip shortage', 'TSMC', 'GPU',
    'delivery delay', 'Maersk', 'Rotterdam', 'Suez', 'Panama Canal',
    'Red Sea', 'freight', 'Baltic Dry', 'EV battery',
]

Risk Parameters

Parameter	Default	Notes
Max position size	$25 USDC	Per market
Min market volume	$5,000	Liquidity filter
Max bid-ask spread	10%	Slippage guard
Min days to resolution	7	Avoid last-minute noise
Max open positions	5	Concentration limit

Installation & Setup

bash

clawhub install polymarket-supply-chain-trader

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Runs every 15 minutes (*/15 * * * *). Markets are slow-moving enough that high-frequency execution is unnecessary.

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	25	Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_VOLUME	5000	Min market volume filter (USD)
SIMMER_MAX_SPREAD	0.10	Max bid-ask spread (0.10 = 10%)
SIMMER_MIN_DAYS	7	Min days until market resolves
SIMMER_MAX_POSITIONS	5	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.