Theory & History

This section explains why prediction markets matter beyond day-to-day trading. It covers the ideas, evidence, and historical context behind the category.

If you want to understand whether prediction markets are useful, how researchers evaluate them, or why resolution systems matter so much, this is the right section.

What this section covers

• Core theory such as information aggregation and incentives
• Accuracy, calibration, and how forecasts are evaluated
• Historical background from early markets to modern platforms
• Oracle and resolution design

Best pages to start with

How to use this section

If you are a beginner, do not start here first. Read the getting-started and trading fundamentals pages before coming to theory.

If you are already comfortable with the basics, this section will help you understand accuracy claims, research findings, and the deeper tradeoffs behind different resolution systems.

It is also the section that helps you separate durable ideas from platform hype. That matters if you want to use markets seriously instead of just reacting to headlines.

Common questions

Does theory matter for practical traders?

Yes. It helps you interpret prices, understand market quality, and avoid overstating what a market can really tell you.

Are prediction markets always accurate?

No. They can be informative, but accuracy depends on market design, participation, liquidity, and the event being measured.

What should I read next?

Start with Theoretical Foundations, then move to Accuracy and Polls vs Prediction Markets.

This section is also where we keep the deeper context that prevents overclaiming. A strong theory layer helps the rest of the site stay useful and honest.