Introduction

Borrowing and lending are one of the cornerstones of the DeFi ecosystem that has been consolidating in the Ethereum blockchain in recent years. It is a financial practice analogous to traditional loans between individuals, involving two types of actors with opposing but interchangeable interests:

• On one side are the borrowers who have the opportunity to use their cryptocurrency funds as collateral to obtain a loan - which can be in the form of fiat, stablecoin or any other cryptocurrency.

• On the other hand, lenders, are who put their idle cryptocurrency funds to work, lending them to the former in exchange for a fixed or variable interest rate.

Through this dashboard, we will identify if the Sushi borrowing and lending activity have been affected from the recent price slump of SUSHI token.

Methodology

The analysis consist of extract as maximum information as possible about the amounts of lending and borrowing deposited. In this case, only the deposits have been computed in order to be compared with the SUSHI price over time, to see if the downtrend of the token affects to the deposits in lending and borrowing features.

To be able to extract the information about amount lended and borrowed, I have taken into account the amounts in udm_events transactions on Ethereum tables filtering by symbol 'km' which corresponds to the Bentobox borrows and lends. For the lendings, I have filtered the events bby from_address 0x0000000000000000000000000000000000000000 and function signature 0x656f3d64, because it represents that it is a deposit. And for borrowings, I have changed the function signature to 0xe2bbb158 and in this case, I have choosen to_address 0xc2edad668740f1aa35e4d8f227fb8e17dca888cd corresponding to the borrow deposits. Finally, I get the price of SUHSI to be compared with it.

Results

The first charts shows the evolution of number of users borrowing and lending over time, as well as the cumulative number over time as well. As we can see, the first chart indicates that the number of users have decreased considerably in both cases, starting from a total of 98 lenders and 77 borrowers and being right now 2 lenders and 4 borrowers. It will be compared later to the SUSHI price in order to see if there is a reason or not for that dumping.

In case of the cumulative numbers, the same occurred, the ascending line was more exponential during the first days, but then, the line became more smoothie over time. The total number of lender and borrowers are around 6k. 3.7k lenders and 2.6k borrowers.

The above charts represents the amount USD lended and borrowed over time in a daily basis. We have seen taht even the number of users have decreased over time, the amount of deposits didn't do it or didn't do it in a similar manner. From September to December 2021, the amount lended increased and the amount borrowed have a huge jump on November 1st. That day was the best day registered with more than 178k USD deposited and almost 100k USD lended. In the second chart, the cumualtive deposited growth can be seen. Since now, a total of 47M USD have been borrowed and 83M of USD lended.

Finally, the last 2 charts shows teh number of users borrowing and lending against SUSHI price, as well as the amount borrowed and lended against SUSHI as well. I made a scatter plot to see some correlation between the metrics.

Looking at the first chart, there is a clear relationship between number of borrowers and lenders and the price of SUSHI. In this case, the correlation is positive but not stronger at all because of while the SUSHI price increase, the amount of lenders and borrowers do the same but in a lower dynamic. However, the correlation are there.

Observing the second chart, it can be seen a little relationship but not signficant at all to determine something clear. It has seen that when SUSHI price goes up, the number of deposits amount in lending and borrownig increase as well, but there are some disperse points that make the assumption a little bit unclear.

Conclusion

In this dashboard we have analyzed the borrowings and lendings in Sushiswap and have been compared with the fluctuation of SUSHI price. The analysis have concluded that the lenders and borrowers have postivie correlated to SUSHI price and thus, during the last period of time the amount of users depositing on it has been decreased as the same trend as SUSHI price. In terms of deposits, the dynamic is similar. Even there is a small correlation between SUSHI price and the amount deposited on lending and borrowing, the results are not clear at all. However, we can determine that the dynamics in SUSHI price affect users to lend and borrow on Sushiswap.