Strategy Guide

Aggregate vs Components

Relative value · Kalshi Macro / Sports · High risk

What does it do?

Compare aggregate events — seat ranges, season win totals, inflation buckets — against the single events that compose them.

Why might it work?

Aggregate and component markets are traded by different populations, producing model-detectable pricing gaps.

Simplified example

Season wins marketOver 50.5

Single gamesremaining win/loss markets

Focussum of component probabilities

Tradeaggregate against component basket

Strategy structure

Aggregatewin totals / seat ranges / CPI buckets

Componentssingle games or events

Tradehedge the basket vs components

Best venueKalshi macro/statistics markets

Main risks

Model riskCoverage riskTail correlation

The basket may be incomplete; models can also be thrown off by schedule changes, policy paths or data revisions.

Active signals

No open signals — the engine rescans every 60 seconds and surfaces opportunities automatically.

Model opinions, historical returns and community scores are no guarantee of results. Before trading, consider fees, liquidity, resolution rules, jurisdiction and your own risk tolerance.