How to trade

This page explains how to think about trading in conditional markets, and how branch prices relate to the asset’s spot price, the event's probability and size of its impact on the asset price.

What you are forecasting

Each conditional market relates to an asset e.g. BTCUSD, conditional on an event, e.g. a Fed rate decision.

Trading in a conditional market requires you to select which outcome of the event you would like to trade in. You can trade in one or many of event outcome branches. E.g.

  • BTCUSD if the Fed hikes rates by at least 25 bps.

  • BTCUSD if the Fed keeps rates unchanged.

  • BTCUSD if the Fed cuts by at least 25 bps.

An outcome branch represents the price of the asset, in the event that the specified outcome occurs. Hence, each branch's price is the market’s forecast of the asset’s price if that branch’s outcome occurs.

Trading screen showing selected branch, branch price, spot price, spread, and open positions
The trading screen displays the selected branch together with its branch price, spot price, spread, and your open positions.

Settlement occurs after the event occurs or when the market’s expiry date is reached, whichever happens first.

Your goal as a trader is to form your own forecast of the asset's price in each outcome branch, compare it with the branch's current price, and then decide whether to open a long (if you believe the branch price is too low) or short position (if you believe the branch price is too high).

Simple way to form a view

You do not need any formulas to trade conditionals effectively. A practical workflow is:

  1. Look at the current spot price of the asset.

  2. For a given branch, ask what you think the asset’s price will be if that outcome actually happens.

  3. Compare your forecast for that branch with its current branch price.

If your forecast for BTCUSD if the Fed hikes is higher than the BTCUSD|Hike branch price, going long in that branch expresses the view that the market underestimates how high BTCUSD will be if the hike occurs. If your forecast is lower than the branch price, going short in that branch expresses the view that the market overestimates BTCUSD under that outcome.

You can also check how different the branch prices are from each other. If BTCUSD|Fed Rate Cut trades at only 5% above BTCUSD|Fed Rate Hike, but you expect BTCUSD will be 20% higher in a cut scenario than in a hike scenario, you can profit by either going long in BTCUSD|Cut or short in BTCUSD|Hike, depending on which of these two branches you believe is currently mispriced. This way you can correct its price and increase the spread between to bring it closer to your expectation of 20%.

Finally, you can also consider how likely each branch's outcome is. The more probable a branch is, the closer its price should be to the spot price, because spot should mostly be "pricing in" the impact of a likely outcome. Hence if you consider a branch's outcome to be likely but its price is far from spot, you can profit by going long if its price is below, or short if its price is above spot, to bring its price closer to spot.

For example, if a hike is already seen as highly probable, the BTCUSD|Hike branch price should sit only slightly below the BTCUSD spot price.

How branch prices, spot, and probabilities relate

This section describes how branch prices relate to the asset’s spot price, the size of the event’s impact, and the probability that the event occurs. You do not need to use these equations to trade, but they help you understand how conditional prices behave.

Consider an event with two outcomes:

  • Outcome A: the event happens (for example, the Fed hikes rates).

  • Outcome B: the event does not happen (for example, the Fed does not hike rates).

Define:

  • spotPrice\text{spotPrice}: current spot price of the asset.

  • eventProbability\text{eventProbability}: probability that the event happens (Outcome A).

  • noEventProbability=1−eventProbability\text{noEventProbability} = 1 - \text{eventProbability}: probability that the event does not happen (Outcome B).

  • impactSize\text{impactSize}: the “impact size”, defined as the price if the event happens minus the price if it does not happen.

Let:

  • eventPrice\text{eventPrice}: your forecast of the asset price if the event happens.

  • noEventPrice\text{noEventPrice}: your forecast of the asset price if the event does not happen.

By definition of impact size:

  • eventPrice=noEventPrice+impactSize\text{eventPrice} = \text{noEventPrice} + \text{impactSize}.

The current spot price can be thought of as the probability‑weighted average of these two conditional prices:

  • spotPrice=eventProbability⋅eventPrice+noEventProbability⋅noEventPrice\text{spotPrice} = \text{eventProbability} \cdot \text{eventPrice} + \text{noEventProbability} \cdot \text{noEventPrice}.

Substituting eventPrice=noEventPrice+impactSize\text{eventPrice} = \text{noEventPrice} + \text{impactSize} and rearranging gives:

  • noEventPrice=spotPrice−eventProbability⋅impactSize\text{noEventPrice} = \text{spotPrice} - \text{eventProbability} \cdot \text{impactSize}

  • eventPrice=spotPrice+noEventProbability⋅impactSize\text{eventPrice} = \text{spotPrice} + \text{noEventProbability} \cdot \text{impactSize}

In words:

  • The conditional price in the “event happens” branch equals the spot price plus the event’s impact, scaled by how unlikely the event is (i.e. how "un-priced-in" its impact is in the spot price).

  • The conditional price in the “event does not happen” branch equals the spot price minus the same impact, scaled by how likely the event is.

This explains why you cannot arrive at branch price forecasts by naively adding or subtracting your impact forecast from spot. If a hike is already seen as very probable, most of its effect is already baked into spot, so the BTCUSD|Hike price will be only slightly above spot, while BTCUSD|No change will sit at a much further distance from spot, but in the opposite direction.

Example

Assume BTCUSD trades at a spot price spotPrice=$100\text{spotPrice} = \$100. You expect that if the Fed hikes, BTCUSD will end up 30 points higher than if it does not, so the impact size is impactSize=+30\text{impactSize} = +30. You think the probability of a hike is eventProbability=10%\text{eventProbability} = 10\%.

Using the equations above:

  • Price if the hike happens (Outcome A):

    • eventPrice=$100+(1−0.10)⋅30=$100+27=$127\text{eventPrice} = \$100 + (1 - 0.10) \cdot 30 = \$100 + 27 = \$127.

  • Price if the hike does not happen (Outcome B):

    • noEventPrice=$100−0.10⋅30=$100−3=$97\text{noEventPrice} = \$100 - 0.10 \cdot 30 = \$100 - 3 = \$97.

In this case the market would be consistent with your beliefs if:

  • BTCUSD|Hike trades around $127.

  • BTCUSD|No change trades around $97.

  • Spot trades around $100.

If instead you observe BTCUSD|Hike at $115 and BTCUSD|No change at $90, then the market’s implied combination of impact and probability differs from your view. You can then trade against those prices by opening a long position in both the Hike and No change branches, to bring them more inline with your forecasts.

Using the framework in practice

There are several ways to apply this framework without doing algebra on every trade.

You can:

  • Start from spot, form an intuition for how much higher or lower the asset should be in each outcome, and check whether the current branch prices match that intuition.

  • Look at the gap between branch prices and spot to understand how much of the event’s impact the market believes is already priced in.

  • Compare the price difference between branches to your own sense of how far apart the asset should trade under each outcome.

When the observed branch prices imply a pattern that does not match your expectations of impact and probability, you have a potential trading opportunity.

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