1. Proposal Details

1.1 Background

As a key leader in the DeFi space, Aave has consistently been at the forefront of innovation and technological development. The introduction of $GHO, Aave's native stablecoin, is a pivotal strategy aimed at driving mass adoption of the Aave ecosystem and potentially scaling DeFi to onboard the next billion users. However, as a relatively new stablecoin, GHO still has substantial growth potential. This necessitates the rapid iteration, validation, and deployment of a subsequent series of innovative solutions.

While AAVE & GHO are striving to maximize innovation, it is crucial to rapidly and comprehensively optimize design, identify risks, and make scientifically informed decisions in a transparent and efficient manner with the community.

1.2 Project Overview

This proposal aims to leverage the advanced no-code, visual modeling and simulation tool, HoloBit, to create a high-fidelity GHO simulation model that is accessible, usable, and verifiable by the broader community. This will bring simulation from the hands of a few to the hands of many-the broader community and the general public. ("off-chain simulations" uses machine learning and statistical models to analyze off-chain data, efficiently evaluating economic mechanisms and potential risks by running a massive number of Monte Carlo simulations without direct blockchain interaction; "on-chain simulations" involves forking the blockchain at a specified block height to create a test environment similar to the mainnet for high-precision protocol simulation).

We will construct key "building blocks" such as Users, Facilitators (AAVE Pool, FlashMinter, GSM), GHO, Market, and Governance. These building blocks can be organized and linked through simple actions like drag-and-drop, making it easy to build the GHO model, similar to assembling LEGO. Additionally, we will rigorously validate the model. This validation will ensure it accurately replicates the GHO protocol ecosystem.

The model's future applications include, but are not limited to, the following areas:

• Providing Insights: Capturing and analyzing key mechanisms and parameters within the GHO ecosystem to reveal main factors influencing system behavior, helping users understand complex systems.
• Optimizing Design: Offering an experimental platform where users can adjust and optimize protocol mechanisms and parameters based on simulation results, validating various design schemes, and enhancing innovation efficiency.
• Anticipating Risks: Testing different scenarios and assumptions to identify potential system vulnerabilities and risks in advance, enabling the development of strategies to reduce uncertainties in actual operations.
• Supporting Decision-Making: Providing data and analysis to offer valuable references for decision-makers, aiding them in making informed decisions in complex environments.

The simulation model is highly transparent and shareable. Its flexible and user-friendly "Lego-like" construction allows non-technical users to easily access and innovate. It promises to be a powerful education, governance, and outreach tool for the GHO protocol. Additionally, the model can complement and enhance existing protocol design and risk management frameworks, offering new approaches for the next generation of community-driven innovation and security solutions.

1.3 Project Value

Specifically, this new solution will deliver several key benefits:

Rapid Prototyping, Bold Innovation, Efficient Iteration in Protocol Design

The GHO model is a powerful tool for innovation validation and design optimization. It offers a unique experimental space for users to brainstorm freely. Whether exploring optimal parameter combinations or testing new mechanisms, this user-friendly and flexible model allows for rapid prototyping and iterative optimization. For example, you can efficiently test various GHO integration schemes, such as different "soft-liquidatio" mechanisms or emergency redemption mechanisms. By analyzing simulation results, you can identify feasible and promising innovations using this approach. This approach significantly shortens the time from concept to implementation and reduces trial-and-error costs.

Consequently, the GHO model enhances the speed and quality of design iterations. It further facilitates AAVE and GHO's innovation in protocol functionality and expansion into new chains and use cases, maintaining a clear edge in technical and service innovation.

Thoroughly screen for economic security risks and efficiently narrow the simulation scope

We propose adding an off-chain simulation phase before smart contract development. By doing so, security is embedded into the design stage. With a verified off-chain model, we can simulate the protocol system's "action space" under new design schemes. This allows us to quickly and thoroughly pinpoint potential risk areas. Feedback from the OffChain model can then lead to iterative design enhancements, effectively reducing the "problem domain" of economic safety and saving considerable time and resources for future on-chain simulations.

Early identification and optimization of design flaws is a cost-effective approach. For ecosystems like AAVE and GHO, a combination of OffChain and OnChain simulations may present the most economically efficient safety solution.

Interactive Dynamic Education and Outreach Tool

The GHO model is user-friendly, allowing even non-technical users to easily understand its mechanisms, and engage in innovative operations such as validation, experimentation, customization, and expansion.

This model serves as an interactive, dynamic educational tool for GHO. If embedded in the GHO Concept introduction page, users can gain a deeper understanding beyond just reading documents. They can see the design, interactions, and simulation results through an intuitive, dynamic visual model. This achieves 'dual transparency' of protocol mechanisms and risks. Users can interact with the model, adjust parameters, and even add or remove mechanisms to better understand the system impacts of different decisions.

The rapid iteration and updates of the model ensure that educational content remains current, maintaining relative synchronization with the smart contract code of the protocol, thereby achieving 'real-time transparency' of protocol mechanisms and risks.

Additionally, the model can be shared with a single click. This means that if the GHO model becomes widespread in the community, it will promote broader user education and deeper engagement, enhancing public recognition, trust, and acceptance of the AAVE and GHO systems. This is a crucial step for AAVE and GHO to broaden their market and achieve mass adoption.

Enhancing Decentralization and Responsiveness in Governance, Boosting Community Innovation

The GHO model's high usability and scalability allow users from various backgrounds to participate in AAVE and GHO ecosystem governance. When the community has a high enough level of understanding of the mechanisms and risks of GHO, everyone can experiment based on the initial model. Not only can they deduce the potential consequences and risks under various extreme scenarios or assumptions, but they can also innovatively optimize and iterate mechanisms and parameters. At the same time, everyone can share their findings in the community and submit proposals for protocol improvements.

This model empowers deep participation in protocol governance, enhancing responsiveness and maintaining high engagement and decision-making quality. It also sparks community creativity. Taking Facilitator as an example, any user can build a new model that adds a Facilitator module based on this initial model, and show the community the operation results, risks and potential impacts of the new model. If he submits a proposal to the community, this method can help the proposal get more community recognition and support. Therefore, each user has the potential to shape the protocol's future. This not only encourages community members to participate in governance but also creates more possibilities for protocol's future development.

1.4 Project Innovations

• Not just for mitigating risks, but also for fostering better innovation
• Genuine and real-time transparency of mechanisms and risks
• Built for Community, accessible to everyone (user-friendly for everyone)
• An unprecedented tool for governance, education, and outreach related to the stablecoin

1.5 Project Goals

Short-term Goals

• Efficiently build the GHO model to accurately replicate the protocol ecosystem, laying the groundwork for community-driven design optimization and risk screening.
• Propose potential methods for education, governance, and outreach based on the existing successful experiences from the AAVE community. With the GHO off-chain model at its core, we'll develop a clear educational plan that empowers the community to understand, use, validate, customize, and expand the model, thereby strengthening community-driven governance and outreach.

Long-term Goals

• Contribute to building a more robust GHO ecosystem: Use the model to assist the community in exploring optimization options and collaborate with service providers to enhance system stability and resilience to market volatility.
• Explore the application of off-chain models within the AAVE ecosystem: If this approach proves successful in the GHO ecosystem, we aspire to implement it within the AAVE ecosystem. This contribution is expected to further propel AAVE's progress towards achieving mass adoption.

2. Feasibility Study

2.1 Feasibility of Protocol Simulation

The famous statistician George Box once said, "All models are wrong, but some are useful." Fundamentally, every model is a simplification and abstraction of the real world. Hence, all models, whether OffChain or OnChain, inevitably rely on certain assumptions. However, these assumptions do not invalidate the model. Instead, they help us understand and analyze complex systems by simplifying and highlighting key elements.

Leading risk management teams like ChaosLabs, Llamarisk, and Gauntlet, who have significantly contributed to the ecosystem, have made numerous assumptions in their protocol simulations. Such assumptions include 'Only DEX Liquidity', 'Price correlations', and 'At most one liquidation per account per block'. While these assumptions simplify real-world scenarios, they do not diminish the model's practicality and usefulness in solving specific problems.

The results are evident. These skilled teams consistently provide sophisticated economic security management advice, such as parameter optimization and mechanism iteration for the sustainable growth of the AAVE protocol ecosystem. This, to a certain extent, confirms the feasibility of protocol simulation. These successful cases show that although both off-chain and on-chain models are assumption-based, they can be adjusted flexibly according to the simulation goals to ensure the model's effectiveness. Their experiences offer valuable insights for the model construction work proposed here.

2.2 Feasibility of Team Using HoloBit for Protocol Simulation

About the Team

Our team has interdisciplinary expertise in computer science, economics, systems engineering, and blockchain. We have deep academic knowledge and extensive project experience in complex system modeling and protocol simulation. Our past project has been recognized by the TokenEngineering Commons grant program, showcasing our ability to complete this proposal. The profiles of our team members are as follow.

• Elaine: Researcher with strong skills in ABM modeling and financial quantitative analysis. She successfully replicated financial physics in high-frequency trading in a limit order book using models. Elaine has extensive experience in modeling and protocol simulation, and currently focuses on token engineering and protocol modeling research.
• Dirk: Token engineer with five TEA NFTs, specializing in crypto protocol design and optimization. He has in-depth expertise in tokenomics and token engineering, and extensive experience in customizing and optimizing token economic models for various projects to enhance their stability and performance.
• Jereyme: Token engineer with five TEA NFTs, specializing in crypto protocol design and optimization. Since 2022, she has been engaged in Token Engineering, fostering education and collaboration in the field.

About HoloBit

HoloBit is a no-code, visual modeling and simulation platform for protocol design and optimization. It is user-friendly, transparent, and shareable, making it perfect for community education, governance, and outreach with the GHO initial model. HoloBit features a Turing-complete Agent-Based modeling and simulation engine, which is essential for creating a high-fidelity GHO simulation model.

Research Achievements

Our team has used HoloBit to quickly build a model of the Terra/Luna protocol. Through simulation experiments, we successfully replicated the internal mechanisms of the Terra/Luna collapse. This demonstrates our research and modeling expertise. It also shows HoloBit's capability to replicate real-world protocols.

Here is the link to the Terra/Luna model (requires a computer to view):

• Scenario 1, Bull market: https://app.holobit.world/embed/9ec46684798598c1c92b13a94231f9d429c0c4c8d9f2579069fb78b41e86c37b

• Scenario 2, Bear market: https://app.holobit.world/embed/9e9dbc531214e37ba84e254470326ff3b50314a91bd0cea6e50957924be628c7

• Scenario 3, Bull market & Attack: https://app.holobit.world/embed/7b9020e2fd1da643a2d4f424d8c72f579da30975e62430810e8261f5d1f90aa0

HoloBit has initiated grant programs for research groups focused on protocol ecosystem optimization. We are fortunate to have received sponsorship for a premium account, which will enable us to transparently document the construction and validation of the GHO initial model using this advanced modeling and simulation platform.

3. Research Plan

3.1 Technical Approach and Deliverables

The technical approach of this research is outlined as follows:

3.2 Current Progress

Given AAVE's significant role in the DeFi ecosystem and the strategic importance of launching $GHO, we have proactively started part of the 'GHO Mechanism Research' as the first step to the technical route:

Based on the preliminary research, our model will cover at least the following key areas:

Based on our preliminary research, the draft of our model interaction process is as follows:

It's important to note that the critical components and process interactions outlined above are preliminary results from an initial quick survey. They aren't the final model and may contain inaccuracies. As our research deepens, we'll offer a more comprehensive and accurate description of these components and process interactions.

4. Conclusion

Our aspiration in introducing the initial model of off-chain GHO into the AAVE ecosystem is to not only enhance economic security of AAVE and GHO ecosystems in coordination with the existing risk management framework. More importantly, we envision this model to serve as a transparent and flexible experimental platform that encourages broader community participation and innovation. The research grant requested in this proposal will be allocated not only to ensure high-fidelity model development and optimization but also to fund community education and outreach to maximize the impact of this project within the Aave ecosystem.

We firmly believe that the implementation of this project will significantly enhance public awareness, trust, and acceptance of the AAVE and GHO systems. Simultaneously, it will considerably strengthen the community's governance and innovative capabilities. We look forward to collaborating with Aave to usher in a new chapter of DeFi covering the next billion users, enabling everyone to participate safely, transparently, and efficiently in this exciting new era.

Thank you for considering this proposal and special thanks to HoloBit for their support. We look forward to contributing value to AAVE and the broader community as we embark on this innovative and transformative journey together.