Challenges and Solutions (Technical)

(i) Auto Compounding on CLMM (Uniswap V3):

The main and initial challenge we aim to tackle concerns the optimal reinvestment of trading fees. Current Liquidity Market Maker models allow fees generated from trades to accumulate within the pool without contributing to its liquidity. This accumulation, indicative of successful trades, represents a static resource—not actively participating in market dynamics or augmenting the pool's liquidity until manually reinvested by liquidity providers (LPs).

At its core, this challenge revolves around the idle nature of accumulated fees. Essentially, fees that could be working to increase the pool's liquidity and enhance its trading volume remain dormant. This static approach to fee management limits the growth potential of LP investments to a linear trajectory, significantly underutilizing the compounding potential inherent in these accumulated fees.

The solution envisages an auto-compounding mechanism that transforms these idle fees into an active component of the pool's liquidity. This transition from a passive to an active reinvestment strategy not only places LPs on a path to exponential growth but also increases the pool's trading volume capability. Automating the reinvestment process ensures that the pool’s liquidity is continuously optimized, responding dynamically to market conditions and trading activities.

This proposed mechanism introduces two key benefits:

Exponential Growth for LPs: By automatically reinvesting trading fees, LPs remove the necessity to micromanage their positions, which reduces the time spent collecting and reinvesting fees and increases yield over time due to the compounding effect on their investments. Enhanced Trading Volume and Liquidity: The continuous reinvestment of fees into the pool increases its liquidity, decreasing slippage for traders and allowing for higher trading volumes, thanks to an exponential fee growth that gets added back into the pool at every swap.

Our initiative is centered on addressing this inefficiency by leveraging the inherent dynamics of CLMMs. Our goal is to implement an innovative auto-compounding mechanism that actively utilizes trading fees to bolster the pool’s liquidity, thereby facilitating a more fluid trading environment. This approach is designed to enhance the yield potential for LPs through a more efficient fee reinvestment strategy and contribute to overall market efficiency by ensuring liquidity is dynamically aligned with market needs.

By focusing on this technical enhancement, we aim to set a new standard in the management and optimization of liquidity pools, ensuring that the DeFi ecosystem evolves to meet the sophisticated needs of its participants.

(ii) Dynamic Fee Rate on CLMM (Uniswap V3):

Defi Market Makers offer LPs (Liquidity providers) the opportunity to generate profits through liquidity provision fees. Currently in Uniswap V3 this fee is set as a static value. Generally a user would have to choose between many different pools of the same trading pair with the only differentiator between them being “Fee Rate”.

This change creates 3 main problems.

During times of volatility impermanent loss (The difference between the amount of tokens a user would have had if the user only kept his tokens solely in one asset) is felt more significantly for users who set a lower fee rate with hopes of capturing larger volume. During more stable periods the Fee is too high making it less probably for his liquidity to be used by other users thus hurting profitability. With Fixed Rate user is forced to observe and actively manage his account switching between different fee rates to suit the right environment.

Currently the addition of a dynamic algorithm to CLMM model is not a trivial matter. Infact some of the earliest designers of the AMM’s and their primitive versions have had quite a hard time coming with an adequate solution. Its best to visit Guillaume Lamber’s paper in order to get familiarized with the issue and its underlying impacts. One of the articles can be found here : https://lambert-guillaume.medium.com/designing-a-constant-volatility-amm-e167278b5d61

Liquid Lama deals with this issue by tracking the volatility directly from inside the pool, and compares current volatility against 2 past time points. Such an approach helps to get a smoother reference of “Volatility” without having too much weight being put on immediate volatility spikes. This in turn maintains a friendlier UX experience for the Liquidity provider as well as much richer liquidity which mitigates slippage. Less pools means deeper liquidity. (iii) Leverage on top of DLMM/CLMM

Enabling Leverage feature on DLMM as well as CLMM would automatically promote liquidity onchain- specifically giving deeper liquidity for users to be able to swap between tokens. Instead of fragmenting liquidity across derivatives , all liquidity gets to rest in one place. This however does involve challenges such as creating Lending pools that will act as Leverage providers, writing from scratch a liquidation bot that will promote decentralisation as well as creating a comfortable UX/UI around our product.