Sushiswap is a decentralized exchange (DEX) built on the Ethereum blockchain that allows users to trade cryptocurrencies and other digital assets without the need for a centralized intermediary.

Stablecoins are a type of cryptocurrency that is designed to maintain a stable value by pegging their value to a traditional currency or other asset. This makes them a useful tool for traders and investors looking to mitigate the volatility typically associated with other cryptocurrencies.

Inflow/outflow refers to the movement of funds into and out of a particular asset or market. In the context of Sushiswap, it refers to the volume of stablecoins that are being bought and sold on the platform.

Dominance refers to the degree of control or influence that a particular cryptocurrency or blockchain network has in a given market or industry. In the context of stablecoins, dominance could refer to the market share held by a particular stablecoin relative to others in terms of trading volume, adoption, and overall usage.

We have created a dashboard to analyze the most actively traded stables on Sushi across multiple chains, including Ethereum, Optimism, Arbitrum, and others. Our aim was to chart the monthly volume and inflow/outflow of stablecoins through Sushi on these various chains.

Additionally, we aimed to identify which chain has seen the most stablecoin activity pick up in the last 3 months.

To accomplish this, we used data from Flipsidecrypto's 'sushi.ez_swaps' tables on multiple networks, such as Ethereum mainnet, Polygon, Binance Smart Chain (BSC), Arbitrum, Optimism, Avalanche, and Gnosis. We accessed the tables of all Sushi-powered blockchains via sushi.ez_swap in the specific blockchain network.

To categorize trading transactions, we divided them into "outflows" and "inflows" based on whether stablecoins were being bought or sold on Sushi. We considered trading operations involving stablecoins such as USDC, USDT, BUSD, DAI, TUSD, FRAX, and sUSD. Once we gathered data from all the blockchain tables, we combined and arranged them in accordance with our graphical concept.

It is important to note that information on BUSD trading from Polygon charts was filtered out due to volume because it didn't make sense. It is crucial to ensure that any data we use for analysis is accurate and reliable. Filtering out this information will help prevent any inaccuracies or bias in our analysis of stablecoin activity on sushi across various chains.

🌡️ Analysis 🔎 🔥 ⏳

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Hey there 👋!

Firstly, I appreciate you sticking with it until the conclusion.

I'm Hamed, a civil engineering Ph.D.

student interested in data analysis.

I've made many similar dashboards and visualizations since I started at Flipside in January.

Please take a look at my various contact details and let me know what you think.

About:

• Author: HaM☰d

• Discord: 0xHaM☰d#8391

• Twitter: @arjmandi_hamed

• Email: h_arjmandi2012@yahoo.com