Pricing Mechanism

At Lithium Finance, we believe in wisdom of the crowd and source pricing opinion from the #price-expert community through Pricing Quests, involving two major challenges, (i) sourcing and (ii) aggregating price predictions.

Protocol Design Challenges

Opinion Sourcing

One of the first questions we ask ourselves in the protocol design process was: If a user honestly believes that an NFT is worthless when the collection floor price is 100 ETH, should they be rewarded for their honesty? Apparently not.

To gather pricing insight from the community, we took guidance from one of the greatest economists John Maynard Keynes. Nobel Prize Laureate Richard Thaler believes Keynes' idea known as the Keynesian Beauty Contest, a theory suggesting that prices are derived from traders whom essentially attempt to estimate others’ interpretation of the world, remains an apt description of financial markets.

Inspired by Keynes and Thaler, we designed the Lithium Finance protocol by asking the community how they believe the market would trade an NFT. Our Reward Mechanism is also designed to align incentives with performance of Price Experts from Keynes' perspective.

Opinion Aggregation

In his article Warning: Do Not Just Average Predictions!, Ville Satopaa explained how averaging community predictions will lead to poor forecasting because each member has different access to information and performance.

To address that issue, a technique known as extremization to systematically transformed the aggregated prediction is well researched. Limited literature, however, has discussed extremization of real-valued, such as pricing predictions.

The other key challenge of the Lithium Finance protocol is to develop a process, the Reputation Clearing Mechanism, to reliably summarize community predictions into a single consensus.

Reputation Clearing Mechanism

Lithium devised a novel extremization process called Reputation Clearing Mechanism. The mechanism takes into consideration the confidence level and historical performance signaled by Reputation Points locked up when Price Experts submit their estimates.

Two Way Pricing Estimates

At every Pricing Quest, Price Experts are requested to estimate two prices:

• Price to Buy: the best price that a Price Expert believe a buyer could successfully convince the owner to sell on the date of valuation. To a seller, it is likely a less-than-ideal price that the seller may accept if he wishes to sell quickly.

• Price to Sell: the best price that a Price Expert believe the owner could get from successfully selling on the date of valuation by selling to the perfect buyer. To a buyer, it is likely a higher than reasonable price he will pay if he wishes to acquire the item expeditiously.

Prices are estimated in this format:

• (i) to help Price Expert consider pricing thoroughly as Nobel Prize Laureates Daniel Kahneman and Richard Thaler pointed out that people assign different value to buying and selling, especially for assets that are held for use or not regularly traded, and

• (ii) to enable our Reputation Clearing Process, aiming to address the Opinion Aggregation challenge.

All estimates are translated into a Premium-to-Floor Price figure at time of submission, to ensure all inputs are standardized for aggregation. For instance, if an Expert considers an NFT to be worth 120ETH while the current Floor Price is 100, his valuation is considered to be 1.2x the Floor Price.

Reputation Clearing Process

Each pair of estimates submitted by a Price Expert is tied to the Reputation Points the Expert has locked up for the Pricing Quest and are pooled with other estimates denominated in Reputation Points.

At the close of each Pricing Quest, we match all Price to Buy and Price to Sell estimates, starting from matching the lowest sell estimate to the lowest qualifying buy estimate. For example, a Price to Buy estimate of 1.0x Floor Price with 10 units of Reputation will be able to take up 10 units of Price to Sell estimate less than or equal to 1.0x Floor Price.

Output Valuation: Three Indicators

The three valuation indicators produced from the clearing mechanism are:

1. Consensus Value It is the price of the last matched buy and sell estimates from the Reputation Clearing Mechanism. It indicates the price level above which the community believes that there would be no buyers and sellers willing to transact further.

2. Low Value It indicates the price below which the community believes there would be plenty of interest in the market ready to buy. It is the last matched buying and selling estimates, starting from matching the highest buying interest with the highest qualifying selling estimates.

3. High Value It is the price above the Consensus Value that eager buyers could be willing to pay. It is the last matched buying and selling estimate from the Reputation Clearing excluding all estimates below or equal to the Consensus Value.

Illustrative Example Indicative Valuation: Consensus (108); Low (101); High (109);

Chart

Data

Price to Buy	RP	Price to Sell	RP
$84	1	$84	0
$85	1	$85	0
$86	2	$86	0
$87	1	$87	0
$88	1	$88	0
$89	1	$89	0
$90	4	$90	0
$91	4	$91	0
$92	1	$92	0
$93	0	$93	0
$94	5	$94	0
$95	7	$95	0
$96	2	$96	0
$97	4	$97	0
$98	9	$98	1
$99	10	$99	1
$100	4	$100	1
$101	10	$101	3
$102	5	$102	8
$103	1	$103	1
$104	6	$104	6
$105	8	$105	4
$106	2	$106	8
$107	4	$107	4
$108	7	$108	9
$109	0	$109	11
$110	1	$110	15
$111	1	$111	7
$112	2	$112	9
$113	0	$113	5
$114	1	$114	7
$115	2	$115	5
$116	1	$116	2
$117	0	$117	0
$118	0	$118	1
$119	0	$119	0

Bootstrapping Reputation Points

SinceReputation Points can only be earned through participations in the Ecosystem, no Price Expert will carry any Reputation Point initially at the protocol's mainnet launch.

For a limited time following the mainnet launch, Reputation Clearing Mechanism will process all price estimates at a minimum weight of 1 unit of Reputation Point (even if no Reputation Point is locked up for an estimate) to build a seed Price Expert community.

Eventually, the above bootstrap handling will be disabled. Price Estimates submitted by new users will not carry any weight in Reputation Clearing. They will, however, be entitled to the same privilege as all other Price Experts under Reward Mechanism to earn rewards. New users will also gain Reputation Points through active participation, and therefore enhance their influence in subsequent Reputation Clearing.

Commit-Reveal Mechanism

The protocol ensures data privacy through a commit-reveal mechanism. To maintain confidentiality, all pricing estimates are encrypted prior to submission, and randomness is injected into the data before being encrypted by the submitting Price Expert through their wallet's encryption function. Although the submission will be recorded on public blockchain, no other Price Experts will have access to any submission, regardless of whether the commit-reveal mechanism is enforced.

If the commit-reveal mechanism is enforced, the protocol operator will not have access to the submissions during the Submission Stage, further enhancing privacy and security. After the Submission Stage closes, Price Experts are required to reveal their submissions, ensuring that the protocol remains transparent and preventing any front running. However, if the protocol is operated by a trusted operator, Price Experts may delegate the reveal process to the operator, and the Reveal Stage can be skipped.

At the end of the Submission and Reveal Stage, the protocol operator decrypts all submissions, processes all estimates, and produces the output valuation. This approach ensures that the protocol remains fair and trustworthy, as all submissions are processed in a secure and transparent manner, and no participant has an unfair advantage over others.