# Introduction
Over the past two years, Liquid Staking has experienced extraordinary growth, with a cumulative total value locked across all liquid staking protocols on Ethereum reaching $44 billion in May 2024. This innovation has revolutionised DeFi by democratising access to native staking yields, previously limited to validators. Furthermore, it has facilitated compatibility across various protocols, offering enhanced yield opportunities. This rapid adoption has elevated Liquid Staking Tokens to a standard within DeFi.
![[LST TVL.png]]

> Liquid Staking Token definition: *A liquid staking token is **a tokenised representation of staked assets**. When a user stakes their assets, they receive an equivalent amount of Liquid Staking Tokens. These LSTs can then be traded, sold, or used in other DeFi protocols, providing liquidity to the staker even while their original assets remain staked.*

# Conventional Methods for Crypto-Asset Valuation
In the current state of Oracle pricing, Liquid Staking Tokens (LSTs) are valued similarly to standard crypto-assets. The price is determined by aggregating data from various markets, including CEX and DEX, where the asset is traded. This approach is accurate and robust due to the market's deep liquidity. The high ratio between an asset's overall daily volume to its market capitalisation (Vol to MC) supports this method.

Understanding the ratio between market capitalisation and daily volume is crucial for determining the robustness of an asset's price and its potential manipulation risk. Oracle prices are primarily used to calculate collateral amounts, such as in money market protocols.

>**Note**: that in the following example, the total circulating supply remains fixed to facilitate the explanation.

Consider a token with a market cap of $300 million and an overall daily volume of $25 million, resulting in a Vol to MC ratio of 8.334%. In the money market, a total of $20 million is used as collateral within the protocol.

The next week, the market cap increases by 25%, bringing it to $375 million. Consequently, the total collateral for this asset in the money market also increases by 25%, rising to $25 million. Some money market users take advantage of this opportunity and increase their risk, getting closer to the maximum loan-to-value ratio. This increase in the asset's value attracts investor interest, raising the daily volume to $35 million.

A few days later, the token's market cap drops by 10%, triggering a liquidation of $500,000 in the money market protocol. Thanks to its market deep liquidity, it can absorb the liquidation smoothly with minimal price impact. This liquidity limits the risk of bad debt for the protocol and reduces potential losses for lenders.

Moreover we can state that the higher the MC grow, therefore the higher is the collateral opportunity but as the liquidity grows too, potential liquidation in that increase in collateral can be smoothly absorbed.
# Contrasting with Liquid Staking/Restaking Tokens (LSTs/LRTs)

> **Note**: For simplicity, the term ‘LSTs’ will be used to refer to both LSTs and LRTs throughout this document.

However, when we turn to Liquid Staking Tokens (LSTs), the situation differs significantly. LSTs, while also traded on various markets, typically show lower Vol to MC ratios compared to standard crypto-assets. This suggests that increases in market cap do not necessarily correspond to proportional increases in liquidity. Therefore, pricing LSTs using the same methodology as standard crypto-assets might not be appropriate. LSTs often represent staked cryptocurrencies which are locked and thus may not contribute to trading volume as fluidly as unstaked assets. This can result in a liquidity profile that is markedly different from that of typical crypto-assets, necessitating a distinct approach to Oracle pricing that considers these unique characteristics.

==Graph with the top 50 crypto et top 20 LST/LRT==

This difference in the ratio has a significant impact on the ability to liquidate position. Let's take another example to clarify the statement.

- Standard token: as the MC grow, the national collateral amount in $ grows too but its liquidity.

This research explores different methods to provide a more robust & efficient way of LST/LRT pricing.

First it exist two different LST pricing mechanism:
1. Appreciation-based redistribution (mSOL, stSOL, wstETH)
- Staking rewards are added to the pool, but the number of tokens remains constant. Each token represents the same share of a pool that increases in value over time due to the added rewards. As a result, the value of an individual token appreciates over time, mechanically increasing its price in the secondary market.
2. Issuance-based redistribution (stETH)
- Staking rewards are paid out by increasing the supply of outstanding tokens, with the newly issued tokens being proportionally distributed among the staking participants. As a result, the price of each token is not directly impacted by the payout, as the rewards are distributed through the issuance of new tokens.

## Appreciation-based redistribution Method
The mechanism for this type of LSTs is straightforward, as the staking rewards are automatically added to the pool. The price of an LST can be calculated by dividing the total number of staked tokens in the pool (totalStakedTokens) by the total number of LSTs in circulation (totalLSTInCirculation). This ratio represents the value of a single LST in terms of the underlying staked token:

$$\frac{totalStakedTokens}{totalLSTInCirculation}$$
### Pragma Approach

## Issuance-based redistribution Method

- As the initial liquidity of ETH is not moved to its derivative LST or LRT, it means that their is a lower ETH is circulation meaning lower overall liquidity.

Potential partners
- [Rated](https://www.rated.network/home)
- [Kiln](https://www.kiln.fi)