Borrowing activity on Aave

    In this dashboard, the borrowing activity of three tokens (SNX, UNI and MKR) on Aave has been determined. Precise investigation on the behavior of borrowers and also the application of borrowed assets calculated, too.

    Overview of analysis:

    Create a dashboard that covers and answers the questions below:

    • How many unique borrowers of SNX, UNI, & MKR are there on Aave V2?
    • What is the total cumulative borrow for each asset on Aave V2?
    • Can you visualize the borrowing of each asset over time?

    Additional aspects of analysis:

    • Behavior of borrowers
    • Application of borrowed assets on the Ethereum blockchain

    The Aave protocol is tied to the concept of lending and borrowing; That is, like traditional banks, Aave provides facilities in the form of loans. Borrowing in centralized financial markets is not easy, But blockchain technology and the world of digital currencies have put a new solution in front of people. Aave is a decentralized and non-custodial liquidity protocol that users can use to participate in depositing and borrowing activities. This protocol is considered a reliable name in decentralized finance (DeFi) and has managed to gain a special place for itself. The Aave protocol is an open-source protocol that allows users to create their own decentralized financial markets on the Ethereum blockchain. Depositors are people who provide the liquidity of this protocol by depositing base cryptocurrencies in lending pools. Their goal is to earn money by getting rewards. On the opposite side, Borrowers are people who can borrow the property they want from the protocol, with or without collateral, which we will explain below.

    Reference

    Methodology:
    About Aave:

    Methodology

    To handle this analysis, the data from Flipsidecrypto has been utilized. The following steps have been used in this analysis:

    Step 1: The borrowing stats on Aave V2

    • Borrow type-> Regular or Flashloan
    • Assets-> SNX, UNI, and MKR
    • Metrics-> Totoal and average volume in USD, Total borrow count, Borrowers and average borrower per day, Overtime analysis handled on a monthly basis

    Step 2: Determine the behavior of borrowers

    • Metrics-> Distribution of borrowers based on the count of borrow and volume in USD, Balance of borrowers in USD, Time difference between first and second borrow, Crossover with other assets

    Step 3: Application of borrowed assets on the Ethereum

    • Metrics-> Most popular sectors and programs for each asset.
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