VSP#2: Economic Incentives to Liquidity Providers

DAO Proposals
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VIP#2: DAO Proposal - VSP#2: Economic Incentives to Liquidity Providers - June 15th, 2023

Proposal Summary:

30% of the total VRSW cap (300,000,000 tokens) is dedicated to incentivizing liquidity provision and growth of the protocol by allocating newly emitted VRSW tokens to Liquidity Providers (“LPs”).

VirtuSwap has developed an AI-based optimization engine (“Minerva Engine”), which analyzes past trading activities to maximize an objective function, or a linear combination of such (e.g. cumulative trading fees, cumulative trading volume, TVL, etc).

This proposal aims to determine that for the first 6 months, starting from the launch of VirtuSwap DEX and approval of this proposal, economic incentives will be determined by the Minerva engine to support the overall growth of VirtuSwap protocol.

Motivation:

This proposal aims to assert the method by which economic incentives will be allocated to LPs.

Proposal specification:

On most DEXes that have a native token associated with them, part of the emission of newly minted tokens is dedicated to incentivizing liquidity provision (or “Economic Incentives”).

Economic incentives serve two purposes. Firstly, they provide compensation for members of the community who create value for the protocol, providing liquidity and thus enabling trades. And secondly, they incentivize allocating liquidity to the pools that will nourish the growth of the protocol.

The prominent method by which the community decides how to split the economic incentives between pools is determined by Gauge Voting. In gauge voting, every epoch, all token holders can split their voting power between pools they want to promote with economic incentives. While gauge voting is considered successful in driving the value of the native tokens by providing utility to their holders; there are at least three downsides of the method:

  1. First, gauge voting reflects un-informed decision-making. Thus, the main consideration for an LP is to gain the maximum economic incentives possible for the pools they provided liquidity to. As such, data and understanding of allocation that would best serve the second goal - i.e. incentivizing liquidity provision to the pools that will benefit the protocol as a whole, is largely irrelevant for Gauge voters.
  2. Second, since each token holder wants to promote the pools he has an egoistic interest in, the actual allocation of economic incentives may not reflect the overall interest of the protocol, which could result in misalignment between the economic incentives and the general community interest (e.g. general growth of TVL or cumulative fees across pools). Consider for example a liquidity provider that has a large share of ownership in a pool that is not popular among traders. If she has a significant amount of voting power in gauge voting, she can direct a disproportionate part of the emission to the pool she has ownership in – an action that would not lead to significant growth in protocol trading volume (as the pool is not popular among traders).
  3. Third, and as a result of egoistic incentives and uninformed decision-making, gauge voting might lead to misalignment between the interest of the protocol as a whole and the economic incentives that the protocol produces.

In light of the above, it seems that while the method of Gauge voting is successful in serving the first goal, i.e. compensating community members that contribute value to the protocol; it may fail in serving the second goal, i.e. allocating liquidity to the pools that would benefit the protocol as a whole.

VirtuSwap has developed “Minerva” - an AI Liquidity Optimization engine that analyzes trading data on a near-real-life basis, and suggests the optimal emission strategy that maximizes a certain protocol-level objective function. The engine answers the following question: “Given a certain amount of liquidity, and assuming that VirtuSwap DEX is accessible through aggregators, what is the best configuration of VirtuSwap DEX that maximizes the total served trading volume and/or maximizes fees for our LPs?”

Extensive simulations of the Minerva engine using real-life trading data demonstrate that allocating economic incentives using the engine provides up to 5x higher fee-based return to LPs. This is expected tocreate stronger incentives for providing liquidity, which, in turn, would result in lower trading costs, thus creating a virtuous self-feeding cycle. For more information about the Minerva engine, please see the following Medium article: “Introducing Minerva - VirtuSwap AI for Liquidity Optimization”.

Following the above discussion, it is proposed that economic incentives will be allocated using Minerva engine suggestions. It is possible that a future VirtuSwapDAO proposal will split decision making about incentives allocation between Gauge voting and the Minerva engine, to benefit from the best of both worlds.

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