> ## Documentation Index > Fetch the complete documentation index at: https://docs.cleopetra.fun/llms.txt > Use this file to discover all available pages before exploring further. # Thesis Index > Tokenised indices backed by binary event contracts A Thesis Index is a basket of prediction market positions, curated by a publisher to express one specific thesis. It avoids the structural problems every alternative carries: | Instrument | Drawback | Verdict | | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | **Stocks / ETFs** | Correlated assets come with unnecessary exposure to company earnings, management, and supply chain noise. AI could dominate and \$NVDA could still fail. | Noisy | | **Options** | Closest way to bet on directional conviction, but built for continuous price movement while macro outcomes are mostly binary. | Imperfect | | **Prediction Markets** | The correct underlying primitive, but managing 15 separate positions to express one thesis is operationally impossible for most. | Wrong UX | Here's a Thesis Index, end to end: ## Bullish AI, Bearish Regulation Example index — AI capability outpaces expectations through 2026 Publishers compose a basket of prediction market positions. The protocol deploys it across the underlying markets - Kalshi, Polymarket, and others. Traders hold index shares that represent the whole thesis. ## Publishers earn from conviction Fees vary per Thesis Index and are set by the publisher. They can include a performance fee on gains, a withdrawal fee on exits, or both. ## Jump right in Pricing, NAV and Mechanics.