GNS Token Liquidity 💸

1. Introduction 🏁

The Gains Network is a decentralized finance (DeFi) ecosystem built on the Polygon and Arbitrum blockchains. Its main offering is gTrade, a decentralized leverage trading platform that allows users to trade a variety of assets, including cryptocurrencies, stocks, commodities, and forex

The GNS token plays a key role within the Gains Network ecosystem. It is designed to incentivize user engagement and participation. Users can stake GNS tokens to earn passive income.

2. Objective 🎯

The primary objective of this project is to propose a strategy for purchasing $5M worth of GNS through DEX while causing minimal market impact. This will be achieved through a data-driven approach, examining historical liquidity and slippage trends. I would like to use this project to showcase my skills in on-chain data, programming, and DeFI.

The following dashboards were developed to help us:

• Dune Dashboard: https://dune.com/dolfo_lima/gns-liquidity
• Flipside Dashboard: https://flipsidecrypto.xyz/Rodolfo-Lima/slippage-in-gns-pools-DGxFD4

3. Methodology 🧪

Multiple data sources and tools were utilized in this project. Below is a brief explanation about each one and the reasons for using them.

3.1 Data Sources & Tools 💻

• We used Dune to get an overview of the volume in GNS pools. Given that Dune provides a swap table for multi-chain, it's convenient to use it. We used the table dex.trades for GNS pools in Polygon and Arbitrum
• Flipside was used to concentrate on the slippage in relevant pools. Since the dex.trades table does not provide decoded information about the USD amount in and out of the pool, the table polygon.core.ez_dex_swaps was used for calculating slippage on Polygon. Flipside does not offer a decoded table for swaps on Arbitrum, but I saw a great opportunity to demonstrate how to handle logs and raw data to accomplish more complex tasks (I remember Jan asking me in the interview if I knew how to use logs 😆). The table arbitrum.core.fact_decoded_event_logs was used to calculate swaps on Arbitrum and their USD value, thus making it possible to compute the slippage for trades on Arbitrum as well.
• In addition to SQL-based data providers, the Coingeko API (**https://www.coingecko.com/en/api/documentation**) was used to obtain current crypto prices, and Arkham Intelligence (**https://www.arkhamintelligence.com/**) was used to acquire the GNS balance for CEXs like Binance and Coinbase. Additional Resources Like Etherescan and Uniswap Inf were explored as well.
• The programming languages utilized were SQL and Python, particularly the Dash Plotly framework for creating a Slippage Simulator. You can find the SQL code in the Dashboards and Python code in the GitHub repository (https://github.com/LimaRods/GNS-Liquidity/tree/main)

4. Data Analyses 📊