Reward Mechanism
Last updated
Last updated
The objective of the protocol is to incentivize accurate estimation of market price (or accurate estimation of what everyone is estimating).
We evaluate performance of #price-expert on how good their estimates are. Price Experts are judged by the proximity of their estimates to the final results, being the three indicators collectively produced by the community:
Consensus Value
Low Value, and
High Value
Price Experts are rewarded with (i)LITH Prize Pool and (ii) Reputation Points according to their respective performance.
Price Experts would be contributing to multiple NFT valuations in a Pricing Quest. One of the experts will win in each of these valuations. All winners in a Pricing Quest will share the $LITH Prize Pool, based on the relative amount of $LITH tokens staked.
Note that staked tokens and RPs apply to all NFT pricings in a Pricing Quest. No additional stake or RP is required from a Price Expert to further participate in other pricings within the same Quest. Price Experts are encouraged to make good use of the stake and multiply their chances to win by pricing more NFT.
For purpose of Prize Pool distribution, performance of each Price Expert is defined by its best performance between the two estimates submitted: (a) Price to Buy and (b) Price to Sell. In each valuation, the winning Price Expert is the one with closest and unique submission. The winner is the Price Expert with the highest Final Score according to the rules below, PROVIDED his submission is unique (no other expert having submitted the same).
Performance Scoring (Prize Pool)
| Score | Proximity Benchmark | Scoring |
|---|---|---|
(a) Price to Buy | (i) Low Value; and (ii) Consensus Value | Best of (a)(i) or (a)(ii) |
(b) Price to Sell | (i) High Value; and (ii) Consensus Value | Best of (b)(i) or (b)(ii) |
Final | Best of (a) or (b) |
Asides from $LITH tokens, another reward issued after every Pricing Quest are Reputation Points. Good estimates will be rewarded with a positive point adjustment. Similarly, bad estimates will cause the Price Expert’s reputation to be slashed.
Similar to scoring for the $LITH Prize Pool, Price Experts are scored based on performance. For purpose of Prize Pool distribution, performance of each Price Expert is defined by its worst performance between the two estimates submitted: (a) Price to Buy and (b) Price to Sell. Unlike the $LITH Prize Pool though, all Price Experts will receive Reputation Points adjustments in every Pricing Quest.
Performance Scoring (RP)
| Score | Proximity Benchmark | Scoring |
|---|---|---|
(a) Price to Buy | (i) Low Value; and (ii) Consensus Value | Best of (a)(i) or (a)(ii) |
(b) Price to Sell | (i) High Value; and (ii) Consensus Value | Best of (b)(i) or (b)(ii) |
Final | Worst of (a) or (b) |
With their final score, which is measured in the number of standard deviations from the respective indicators on a Z-score table, Price Experts are grouped in increments of ±0.1 points. The smaller the distance is from the indicators, the more accurate the prediction is, and the higher the reward in Reputation Points will be. Now that we have Price Experts grouped by performance, each Price Expert i will receive Reputation Point adjustment according to the formula below:
Where
rpStaked denotes the amount of Reputation Point a Price Expert_i has locked up for the relevant Pricing Quest
Z_i denotes the final Performance Score (Reputation) of Price Expert_i, measured in the number of standard deviations from the applicable Proximity Benchmark as rounded up to 1 decimal point
Round() denotes rounding function to 1 decimal point
Provided
rpAdjustment (i) shall be -100% * rpStaked if Z_i> 2.0, and (ii) shall never exceed rpAdjustmentCap, certain maximum cap as set in the protocol smart contract.
Illustrative Example of Reputation Adjustment by Performance Score
Experts whose submissions are very good (in absolute Z-score distance ≤ 0.1) will be rewarded 100% of their staked Reputation Points, subject to a cap. Experts whose submissions are reasonable (in absolute Z-score distance of around 1.0) will not receive any adjustment. Any submission in absolute Z-score distance further than 1.0 will see the expert’s Reputation Points being slashed.
To help new users get started, Reward Mechanism will consider new users having locked in 10 Reputation Points in a Pricing Quest for purpose of reward entitlement.
All Price Experts with less than 10 Reputation Points in wallet and in all active Pricing Quests at time of a Reputation Clearing process will qualify.
