Staking/Reward model:
Assets:
- non-fungible token (an NFT asset)
- fungible token (a digital coin)
Problem statement:
We need to create a model for an efficient NFT staking/reward model. An investor will buy a non-fungible token as an asset. If they plan to Hold it for a longer period of time they can Stake it to get rewards against it (I guess it equates to a fixed deposit in traditional banking).
We will have a stacking pool where we will deposit % of earnings from NFT secondary sales. When a participant stakes their NFT's we allocate fungible tokens as an intermediary reward. The amount each participant gets from the pool depends on the fungible token accumulated. (Not sure if this intermediary token is even required in this solution)
Due to high network transaction fees, we can not push the reward payments to each participant and have to follow a pull model where the participant draws their rewards or withdraws NFT staking when they desire.
Now the main issue is coming up with a mathematical algorithm to accomplish this. There seem to be many factors that come into play to determine a scalable reward system like
- The price of NFT at which the participant stakes the NFT.
- Price change of the NFT along the course of the staking period (inflation/deflation).
- Amount of time it is staked for.
- Number of NFT's one has staked.
- Compounding affect.
What can be the best possible way to make a mathematical formula to determine a scalable reward Distribution system here?