Structural#018

Conditional-Market Trading

Conditional markets ask 'if X happens, does Y follow?' (e.g. 'if Newsom is the nominee, does he win?'). They give you a clean conditional probability that you can compare against the plain, unconditional markets using basic probability math: the chance of being nominee, times the chance of winning given the nomination, should equal the chance of winning outright. When those pieces don't multiply out correctly, you trade the legs against each other. The edge is the inconsistency between the conditional price and its parent markets.

What you need to run it

  • Understanding of Bayes/conditional-probability math
  • Scanner for conditional markets and their unconditional parents
  • Capital to deploy across multi-leg positions

Where this applies

Markets on Polymarket where conditional-market trading is the natural play:

  • If Newsom is the 2028 Dem nominee, will he win the presidency? vs the standalone 'Newsom wins presidency' market
  • If the Fed Chair is replaced in 2026, will rates be cut by year-end? vs 'rates cut by year-end'
  • If a given team reaches the 2027 NBA Finals, will they win the title? vs 'wins the title'

Capabilities this demands

Model / quantManual researchCustom code / API

At a glance

CategoryStructural
Requirements3
CapabilitiesModel / quant, Manual research, Custom code / API
VenuePolymarket (CLOB, Polygon)

Build it

Related structural strategies

This is documentation, not advice. Poly Research & Robotics publishes how these strategies work because the method should be checkable — not as a recommendation to trade them. See the full strategy database (147 strategies) or the data resources directory.
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