JIP 2: Incentive Budget and Framework for Strategic Growth

Category: Treasury

Abstract

This proposal, written in collaboration with the Jito Foundation, outlines a rest-of-calendar-year budget of 7.5m JTO to be managed by the Foundation.

About Gauntlet

Gauntlet is a DeFi-native quantitative research firm specializing in risk management, incentive optimization, and mechanism design. Gauntlet uses battle-tested techniques from the algorithmic trading industry to help protocols manage risk, optimize revenue, and design better incentives. Our simulation models inform parameter decisions for protocols of all sizes, covering over 25% of aggregate DeFi TVL. Gauntlet is also one of 17 delegates to receive a cumulative 12 million in JTO token voting power from Jito Foundation wallets.

Motivation

Gauntlet has recently conducted an analysis of Jito’s incentive programs to identify and recommend strategies for long-term growth and efficiency. During the analysis, Gauntlet provided the Jito Foundation with empirical measurement tools, data-driven insights, and actionable strategies to ensure that Jito’s incentive programs will meet the dynamic needs of JitoSOL and the wider Solana ecosystem.

Following extensive research and analysis, we are pleased to present a summary of our findings from two pivotal studies: the Comprehensive Quantitative Evaluation Framework and the User Behavior Study. These studies provide robust historical data on the outcomes of past incentive programs funded by the Foundation and offer a model for assessing future initiatives.

Using these as a backdrop, we propose a strategic framework and budget that will direct Jito’s incentivization efforts towards the most effective liquidity pools and products, optimizing returns and user engagement with JitoSOL.

Context

Currently, Jito’s closest competitors – Marinade’s mSOL and Blaze’s bSOL – have significant incentive spend budgets to promote the adoption of their respective LSTs. Despite Jito DAO boasting a much larger treasury, to date the Jito Foundation has only undertaken a handful of incentive programs – programs which we can now analyze empirically as having been successful.

Since the cessation of a Points incentive program, JitoSOL’s TVL has grown from 6.75m SOL to over 10m (nearly quadrupling in dollar terms during that period), with the Foundation funding only a handful of small-scale JTO incentive programs totaling under 1m JTO spend, primarily on the Kamino platform. Our findings suggest a more aggressive incentive program funded by the DAO could amplify this growth.

This budget accounts for .75% of the total JTO supply and 3.1% of the DAO’s JTO supply. Because of Jito DAO’s strong financial position, this budget represents a smaller supply percentage spend relative to competitor programs, but likely a larger spend in dollar terms.

As new competitors begin to emerge, this is an ideal time to utilize a responsible portion of the DAO’s considerable resources to cement JitoSOL’s market-leading status.

Key Terms

  • ROI (Return on Investment): A performance measure used to evaluate the efficiency of an incentive program, measured in TVL gains on a dollar-spent basis.
  • TVL (Total Value Locked): The total amount of assets staked in a protocol.

Specification

Gauntlet conducted a detailed analysis to enhance the effectiveness of incentive programs for Jito. The main objectives were:

  1. Comprehensive Quantitative Evaluation Framework: Develop a quantitative framework specifically designed to base incentive spending on performance and KPIs so that Jito can evaluate the success or failure of any incentive program.
  2. User Behavior Study: Analyze staker dynamics and user behavior within the broader Solana ecosystem, focusing on why they stake and their responsiveness to different incentives. This will help future incentive strategies consider the elasticity of user responses to returns and competitive pressures.

Executive Summary of Comprehensive Quantitative Evaluation Framework:

The framework uses a composite Return on Investment (ROI) formula that accounts for changes in Jito’s Total Value Locked (TVL) as well as the recipient pool’s TVL. It adjusts for broader market movements and allows attribution of impact to overlapping incentive programs. Gauntlet’s team applied the formula to the incentive programs that Jito ran from December 2023 to March 2024.

ROI(I,p) - ROI of the incentive program I in a pool p is determined by the following formula:

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Definitions:

  • I: The specific incentive program.
  • A: The total amount of incentives distributed in JTO over the period[t−n,t].
  • p: The specific liquidity pool within a DeFi protocol.
  • α = 0.6: Weighting factor emphasizing the importance of Jito’s TVL changes relative to pool-specific TVL changes.
  • L: The LST market adjustment, defined as the ratio of the TVL (in SOL) of Solana’s non-Jito LST market at the end vs. the beginning of the evaluation window.
  • S: Market adjustment for the Solana non-LST market, defined as the ratio of the TVL in USD at the end of the period (t+14) to the beginning (t−n).

Key Findings:

  1. The Kamino JitoSOL/JTO 3 pool had the highest daily ROI of 0.15 SOL/JTO, benefiting from well-calibrated incentives and medium-term engagement.
  2. Successful programs balanced incentive levels with pool TVL to attract participation without diluting value for existing pools.
  3. Program duration flexibility is important to adapt to changing market conditions and user behavior.

The full report includes mathematical derivations, example calculations, and implementation details to support the adoption of this ROI-based evaluation methodology.

Executive Summary of User Behavior Study:

Gauntlet conducted a detailed statistical analysis of user behavior on Jito and compared it with Marinade, BlazeStake, and LST (Marginfi). The study focused on different user groups based on stake size and status to identify trends and gauge the success of Jito’s incentive schemes.

Key findings:

  1. The current incentive campaign needed to be more effective in attracting and retaining small-to-large users but effectively generated sustained staking growth among whales.
  2. Jito users have a higher average number of withdrawal operations per account than competitors; however, a low 17% withdrawal rate (the percentage of accounts that withdraw at least once) suggests strong holder retention.
  3. Jito has the highest wallet net-worth average among competitors but one of the lowest LST DeFi utilization rates, indicating that it has the most risk-averse users overall.
  4. Many wallets hold at least two kinds of LSTs, reflecting a tendency for diversification among stakers.

Recommendations include:

  1. Redesigning the incentive program to target distinct user cohorts
  2. Considering targeted staking yields for medium to large stakers
  3. Developing strategies to leverage high net-worth users
  4. Exploring cross-platform partnerships or features to cater to users who diversify their holdings.

Program construction:

Based on the results and key findings of these two reports, Gauntlet believes that the following program is optimal:

The Jito DAO allocates 7.5m JTO tokens to a Foundation multisig (address 8sjM83a4u2M8YZYshLGKzYxh1VHFfbgtaytwaoEg4bUJ) to spend on a discretionary basis in order to pursue a variety of liquidity mining strategies. The Foundation will have a mandate to pursue pools and strategies, such as the previous Kamino programs, that maximize TVL returns and JitoSOL liquidity depth using Gauntlet’s evaluation framework, and will return any unspent JTO at the end of the calendar year. The funds to be managed by a 3/5 multisig of three Foundation members and two Jito Labs members.

This allocation is preferable to having the DAO vote on specific programs in that it enables the overall liquidity mining strategy to maintain flexibility and adjust to changes in user behavior and market conditions.

Additionally, as competitor protocols begin to adjust their liquidity mining strategies in response to Jito’s success, a discretionary budget will allow the Foundation to not just move quickly, but maintain competitive advantage relative to the delays and transparency demanded by the nearly 40-day discussion and voting period mandated by the DAO.

Benefits/Risks

Benefits:

  • JitoSOL TVL growth

Risks:

  • Overspending on inefficient LM programs

Outcomes

The desired outcomes include:

  • Sustainable, accelerated growth in TVL
  • Clear tracking of the success or failure of specific programs
  • Growing JitoSOL dominance measured as a percentage of total Solana LST TVL

Cost Summary

This proposal would cost the DAO 7.5m of its 240m JTO tokens. The Foundation will return any unspent tokens at the end of the year, and if the program is overall deemed to be successful, the Foundation will likely initiate DAO proceedings for a 2025 liquidity mining budget.

Performance Milestones

  • Quarterly review of incentive program effectiveness.
  • Adjustments based on empirical data and community feedback.

Appendix

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