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Hazard rates and by-date probability literacy

Many prediction markets ask whether something will happen by a date: a ceasefire, a resignation, a product launch, a rate cut. Readers often treat these as single coin flips. A more useful lens is the hazard rate, the chance of the event in each small slice of time. Thinking this way explains why by-date prices drift as the calendar moves and why two markets with different deadlines must be related. This SoftCta guide introduces the idea without heavy math.

From per-period to by-deadline

Suppose an event has roughly a 5 percent chance of happening in any given month and each month is independent. The chance it does not happen in a month is 95 percent. Over six months, the chance of no event is 0.95 to the sixth power, about 74 percent, so the chance of Yes is about 26 percent. Over twelve months it is about 46 percent. The deadline changes the answer a lot.

Why prices should decay

If nothing happens for three of those six months and the monthly rate is unchanged, only three months remain and the by-date chance drops to about 14 percent. Our time decay guide describes this drift. A price that stays flat while time passes implies the reader believes the hazard rate went up.

Consistency across deadlines

When a venue lists the same event with several deadlines, the probabilities must rise with later deadlines. A March contract cannot reasonably be priced above a June contract on the same event. Comparing the implied monthly rate between adjacent deadlines is a quick check for stale or inconsistent quotes.

Rates that change

Real hazards are rarely constant. Resignation risk spikes after a scandal, legislation clusters before recesses and storms follow seasons. Our deadline guide and status quo guide discuss how scheduled events and inertia shape timing.

Where the rate comes from

A base rate from similar past situations is the usual starting point; our base rates guide covers reference classes. For events without precedent, the rule of succession guide shows one way to start from limited data.

Common errors

Readers sometimes add monthly chances instead of combining them, which overstates probabilities over long periods. Others ignore that a price includes fees and spread. Converting quotes with the implied probability tool before doing the math keeps the comparison clean.

A simple reading habit

For any by-date market, write down your estimate of the chance per month, then compute the by-deadline probability using the no-event method. Compare that with the price. Each week, redo the calculation with the remaining time. If the market price does not move as time runs down, ask what new information would explain it.

Primary sources SoftCta readers open

• Historical event timelines from official records for base rates.
• The venue's listing of related markets with different deadlines.
• The venue rulebook defining deadline, time zone and qualifying event.

Reading the quote step by step

• Read the full title and rules, including the named settlement source and the time zone.
• Convert the Yes and No prices to implied probabilities and note the gap between them.
• Subtract fees and spread to see the effective price you would actually face.
• Write your own probability range and the evidence behind it, then compare.
• Check related and near-duplicate markets on other venues for consistency.

Closing SoftCta checklist

• Re-read the venue definition in your own words before reacting to a price.
• Convert prices with fee and spread awareness; verify live cents on the operator.
• Prefer primary settlement sources over secondary headlines and social summaries.
• Treat ChanceWire hubs, movers, and tools as orientation — not order entry.
• Confirm age, location, and product eligibility; SoftCta pages will not suggest location spoofing.
• If clarity is incomplete, watching is a complete SoftCta outcome — no pick-selling urgency required.

SoftCta habits

• Write your own probability range before checking the crowd price.
• Prefer dated primary sources over social summaries.
• Compare related markets when a single book looks extreme.
• Size curiosity with fees and depth in mind; substantial risk of loss.