Over the summer we built an optimization algorithm for liquidity allocation on Sushi Swap (https://twitter.com/eljhfx/status/1426389242096328705). It decides which liquidity pools should exist and how much liquidity to allocate into each pool. Our initial results eliminated approximately 100,000$ in slippage and gas fees for traders in a 24 hour period (relative to the current allocation method) while maintaining or increasing fees earned by liquidity providers.
Our immediate action items for this grant are as follows:
- Improve the readability and runtime of the liquidity allocation optimization algorithm
- Scale up the algorithm to consider more tokens and pools (eventually the entire DEX)
- Use more data for training and separate training from testing data to prevent overfitting
- Design mechanisms for implementing the findings to tangibly improve SushiSwap by lowering gas fees and slippage
- Formalizing the results in an academic journal style article submitting it for publication
We think that our backgrounds would be helpful for optimizing SushiSwap in other areas in the future. Specifically, we have already spoken at length about concentrated liquidity, impermanent loss and efficient routing algorithms. Although these are outside the primary scope of this initial grant, we would like to help SushiSwap on these items in the long term and will continue making progress on them throughout our time funded by the grant.
- Both of us are currently in school and working in blockchain so our additional available hours are limited. To supplement the hours that we will put into this, we plan to bring on a couple of talented researchers with similar backgrounds to help speed up the process.
- Building, training, and running Combinatorial optimization algorithms is expensive, both in terms of time and computational resources. The first iteration of our algorithm ran on a MacBook; however, as we scale up the size of the inputs, we will need far more computing power. We plan to use some of the grant funding to pay for cloud computing units and local computing resources.
Office Supplies and Office Space
- Research, unlike development, lends itself more naturally to an office environment. Asynchronous and remote work in research often inhibits the types of helpful collaboration that are essential to excellent research. For that reason, we would like to rent a small office space to facilitate collaboration.
Elijah Fox – @eljhfx is a 4th year undergraduate at the University of Michigan studying Computation, Cognition, and Complex Systems. He plans to pursue a graduate degree in Systems Engineering or Computer Science.
Max Resnick – @MaxResnick1 is a 4th year undergraduate studying Pure Math and Complex Systems at the University of Michigan, he will be pursuing a master’s degree at MIT in Economics next year.