Prediction Market Trading

How prediction-market contracts resemble digital, corridor, and barrier options—and where the analogy breaks down.

Reviewed and updated 20 July 2026

Hello,

Welcome back to another paid-subscriber only post. Today, I will discuss how prediction markets can be modeled using familiar option structures, and what those analogies can—and cannot—tell us about prices.

Let’s get into it.

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Modeling Prediction Markets as Exotic Options

Prediction markets are often misunderstood by retail traders as simple sports-betting parlors for geopolitical or macroeconomic events. From a structural standpoint, many of their contracts resemble familiar option payoffs. Mapping prediction contracts to those traditional counterparts can help us understand their pricing dynamics and the risks involved in trading them.

Digital Option

A digital option, also known as a binary or cash-or-nothing option, provides a fixed payout if the underlying asset is trading above (for a call) or below (for a put) the strike price precisely at expiration. It is a European-style option with a strictly binary outcome: $1 or $0.

Payoff: $1 if S_T > K; otherwise $0.

In the standard Black–Scholes–Merton framework, the value of a $1 digital call is the discounted risk-neutral probability that the option expires in the money:

V₀ = e^−rTN(d₂)

For a short-dated contract, the discount factor may be close to one. Even then, N(d₂) is a risk-neutral probability inside the model—not automatically the true real-world probability of the event. Prediction-market prices also reflect the contract’s settlement rules, fees, liquidity, and any risk premium demanded by traders.

For example, a contract that pays $1 if an index finishes above a stated level resembles a digital call. Its price can be read as a price-implied probability only after accounting for those qualifications.

Digital Range (Corridor) Option

A digital range, or corridor option, pays a fixed cash amount only if the underlying asset’s price settles within a specifically defined lower and upper boundary at expiration. Structurally, you can create a range option by going long a digital call at the lower boundary (K₁) and short a digital call at the upper boundary (K₂).

Payoff: $1 if K₁ < S_T ≤ K₂; otherwise $0.

In the same model, the price is the difference between the two discounted digital-call values:

V₀ = e^−rT[N(d₂(K₁)) − N(d₂(K₂))]

Prediction markets sometimes use a series of mutually exclusive brackets for a count or economic release. Together, those bracket prices form a discrete probability mass function—not a continuous probability density function. The exact inclusivity of each boundary and the settlement source come from the market’s resolution rules, so those rules must be checked before trading.

One-Touch Option

A one-touch option is a path-dependent barrier option. Unlike a standard digital that only examines the underlying price at expiration, a one-touch pays if the underlying breaches a predefined barrier at any point during the contract’s monitoring window.

Pricing a one-touch is more complex because it depends on the path of the asset, including volatility, time to expiration, carry, monitoring conventions, and payout timing. Under otherwise matching terms, the probability of touching a barrier is at least as high as the probability of finishing beyond it.

The often repeated shortcut that a one-touch is worth roughly twice a digital at the same strike holds only under restrictive assumptions. It is not a general pricing rule, even in Black–Scholes–Merton, because drift, carry, payout timing, and the monitoring convention matter.

That was a lot, and I could discuss this with much more depth if it is of interest.

Below, I turn from payoff mechanics to what recent research says about prediction markets as forecasting tools.