Borrowing On Folks Finance

Q69. Let’s look at borrows on Folks.Finance a borrowing and lending protocol built on Algorand. We want to get an understanding of how what assets users most want to borrow, how often borrows are happening, and the average collateral ratio between the collateral offered and the asset that is borrows. Ultimately, we want to get a better understanding of what people are borrowing, and what the collateral ration looks like.

• Chart number of borrow actions by day. Additionally chart the number of borrow actions by day for each asset.
• Chart the volume that is borrowed for each asset by day(USDC, USDt, goBTC, goETH, ALGO), are there any notable borrowing days? What might have caused this?
• Note the average collateral debt position of ALGO(fALGO) to the borrowed asset for each asset. Then create a scatter plot for each asset plotting the collateral ratio for each borrow(x-axis is date) and highlight which ones were above the average collateral ratio and which ones were below. If you have a better way to visualize showing the borrows each day that were above and below the average collateral ratio for the asset show us!

Tips:

• Try borrowing on Folks Finance here: https://app.folks.finance/borrow
• The borrow process is as follows: a wallet will first commit an escrow transaction converting ALGO to fALGO. Then the wallet will place the fAlgo up as collateral and borrow the asset in a separate tx group. We are only concerned with the borrowing action
• Borrow Examples: https://algoexplorer.io/tx/group/AKAaPlaaXqX3A%2FXJjvRPb5rUJ6u%2FXqIQEuGRvXhNTwQ%3D https://algoexplorer.io/tx/group/9rtUuXDx0CMwB6LWsAGONovmhG3PDHRzmYoCb4fOPCU%3D
• Borrow Documentation: https://docs.folks.finance/protocol-architecture/borrow
• The borrowing app_id’s will be the assets poolAppId https://docs.folks.finance/developer/contracts
• To decode and filter borrow application call transactions: TRY_BASE64_DECODE_STRING(tx_message :txn :apaa [0] :: STRING) = ‘b’