[DISCUSSION] Partner with Gamma Strategies on Treasury Management

Proposal Title: Partner with Gamma Strategies on Treasury Management

Authors: Brian

Date: 1/12/2022

Summary

Hi BitDAO Community!

I’m Brian from Gamma Strategies, which is an active liquidity manager on Uniswap v3. This proposal is an opportunity for a partnership between BitDAO and Gamma Strategies to generate yield on ETH, FTT, and USDC by providing these assets as liquidity on Uniswap v3 via the strategies developed by Gamma Strategies.

What is Gamma Strategies?

Gamma is an active liquidity manager on concentrated liquidity DEXs such as Uniswap v3, with plans to actively manage liquidity on Sushi Trident and Shell Protocol as well. We are utilizing machine learning algorithms to dynamically predict optimal price ranges for providing liquidity to a specific pair.

Our top-of-the-line strategy is an Autoregressive GARCH mode (https://github.com/GammaStrategies/active-strategy-framework/blob/main/2_AutoRegressive_Strategy_Example.ipynb), which predicts price movements and dynamically broadens liquidity ranges to mitigate impermanent loss by reducing the concentration of liquidity. During periods of low volatility, the liquidity ranges narrow in width to take advantage of a higher swap fee multiplier. Additionally, the algorithm uses mean reversion to predictively place liquidity bands in the direction that the model expects price to go.

We are currently managing liquidity for over 40 liquidity pairs on behalf of public LPs but manage over 10 liquidity pairs on behalf of DAOs and institutional investors.

What is the Earning Potential?

To determine earnings, we look at the Fees / TVL ratio as a metric to determine profitability. Based on BitDAO’s treasury of assets, we’ve determined that the best pairs to deploy liquidity would be for the 0.3% FTT-ETH pool and the 0.05% ETH-USDC pool. I will summarize our backtesting results for $4 million of liquidity invested in each pool for Q4’2021 below, but feel free to read the full reports here:

  1. 0.05% ETH-USDC Q4’2021 Backtesting Report
  2. 0.3% FTT-ETH Q4’2021 Backtesting Report

0.05% ETH-USDC Highlights:

  • Net return of 15.23% over a period of 91 days for an annualized return of 61%
  • The LP position of $2M of USDC and $2M of ETH outperformed holding the two assets by 6.2% over a period of 91 days, for an annualized outperformance of 24.8%

0.3% FTT-ETH Highlights:

  • Although the Net Return was strongly mitigated by the downward price action of FTT / ETH in Q4, the LP position vastly outperformed simply holding FTT & ETH by 10.27%, for an annualized outperformance of 41.08%

(see charts in the link above - was only able to embed one media image)

Infrastructure:

The management of liquidity would take place through our position manager contracts called the Hypervisor https://github.com/GammaStrategies/hypervisor

The Hypervisor contract manages both a base position and limit position at all times and as such, we maintain higher profitability due to not incurring the swap fees upon rebalancing price ranges.

Only the DAO’s multisig address provided will have the right to withdraw assets from the Hypervisor once deposited into the Hypervisor contract. The position manager contract has the right to a few functions which are to set liquidity ranges and to re-invest earned fees. The Hypervisor contract is non-custodial in that only the whitelisted address may withdraw assets from the Hypervisor. In that sense, this process is a lot more secure from external risks (such as flashloan attacks) which involve other parties depositing and withdrawing from the same position manager contract.

In terms of the business model, Gamma collects 10% of the fees returned from the position and distributes that to its stakers. 90% of the fees returned are re-invested back into BitDAO’s LP positions.

Potential Budget:

  1. Deploy $4 million of liquidity to the 0.3% FTT-ETH pool on Uniswap v3
  2. Deploy $4 million of liquidity to the 0.05% ETH-USDC pool on Uniswap v3

Next Steps:

Please let us know what you think of our proposal and ask us any questions! We’re happy to delve into more details.

2 Likes

bitDAO can do this on their own very easily, any benefits or advantages could your proposal bring to the bitDAO? How are you gonna to convince them?

Just curious, didn’t mean to offend :laughing:

Providing liquidity to Uniswap v3 is not something that one can do passively like on Sushi or Uni v2. The liquidity provider is discretionarily providing liquidity in select price bands.

To illustrate, when providing liquidity on Uni v2 or Sushi, you simply provide liquidity over the entire price range. That, I agree, doesn’t require any management or the need for an active manager.

Uniswap v3 allows for discretionary decision making as to how to provide liquidity. For example, for the ETH-USDC pair, I can choose to provide liquidity only when the price of ETH is between $2,500 and $4,000. This concentrated liquidity position earns multiple times in fees what a full-range liquidity position (a la Uni v2 & Sushi) would generate. The tradeoff is that, you have the potential to incur much higher impermanent loss if the price were to go out of range or if the liquidity ranges are not managed effectively. Bancor actually released a research paper about how most LPs on Uniswap v3 are not able to generate fees in excess of impermanent loss.

For that reason, there became a need for active managers such as Gamma Strategies and Gelato (G-UNI) to manage ranges when Uniswap v3 was released. The main difference between Gamma and G-UNI is that we utilize machine learning algorithms to dynamically and predictively determine the width and placement of the liquidity bands as well as the timing of the rebalances. G-UNI utilizes a much more simplistic / heuristic rebalancing strategy, which arbitrarily chooses a range at +/- x% around current price and rebalances when the price moves +/- y% in either direction. This is far less optimal than our current Autoregressive Strategy, which dynamically widens the price bands during times of high volatility to lessen the impact of impermanent loss, but narrows the price bands during low volatility times to take advantage of the higher fee multiplier.

Please let me know if that makes sense. The tl;dr is that managing liquidity on Uni v3, although it can be very profitable, requires expertise in terms of how to provide liquidity to maximize yields and reduce impermanent loss because you can choose the price ranges to provide liquidity.