Lithium Finance is set out to deliver several key desired outcomes:
- Genuine and Decentralized: Estimation of market pricing based on large sample size of market participants (rather than valuation based on small number of insider).
- Fair and Secure: Pricing estimates will be safeguarded from manipulation and external attacks.
- Reward Accuracy: Price Experts will primarily be rewarded based on precision of their pricing estimates.
- Reward Reputation: Price Experts that produce accurate price estimates consistently will be further rewarded with increased reputation score and greater influence over pricing output.
- Encourage Participation by New Users: New pricing providers will not be disincentivized from participating. Although new users do not command high reputation or market influence initially, the Lithium Protocol is an inclusive system that embraces both new and existing price providers.
Given these objectives, the Lithium protocol design is premised on the following key elements:
- Two Currencies Separate economics and reputation tokens are developed to handle compensation and signal reputation.
- Staking Limits: Thresholds and relative limits in economics and reputation token staking designed to ensure protocol integrity and prevent bad actors.
- Two Way Pricing Estimates: Nobel Prize Laureates Prof. Daniel Kahneman and Prof. Richard Thaler pointed out that people assign a different value to buying and selling; especially for assets that are held for use or not traded infrequently. The Lithium protocol assists Price Experts to consider pricing thoroughly by requesting estimates in a two-way bid and ask format.
- Clearing Mechanism: All submissions are aggregated to produce a hypothetical order book weighted by staked reputation tokens. The hypothetical order book will be cleared by the Market Clearing Mechanism to produce an indicative market-clearing price.
- Reward Mechanism: The protocol incentivizes accurate estimation of market sentiment or the mean of what other Price Experts are estimating. Our Reward Mechanism compensates Price Experts primarily based on the precision level of their pricing estimate inputs (as measured by proximity to the mean bid or ask estimate among all other inputs). Price Experts are not rewarded based on output market-clearing price to prevent mis-incentives.