Try Quests to earn NEARNEAR Tournament Round 3: The Financial District
Introduction
The NEAR network hosts the application that handles Ref Finance. The platform has an emphasis on decentralization and censorship resistance by eliminating the need for trusted intermediates and operating on a completely permissionless model. By contributing an amount equal to the value of each underlying token in exchange for pool tokens, anyone can trade and/or become a liquidity provider (LP) for a pool (LP tokens). These tokens represent LPs' pro rata portion of the overall reserves and can be exchanged at any time for the underlying assets. Ref Finance's (v2.ref-inance.near) smart contract manages automated market maker functions such as swapping and providing liquidity, and unlike Uniswap, it contains all pairs or liquidity pools, each of which is composed of reserves of two or three NEP-141 tokens (ERC-20 equivalent on NEAR). Link
Method
Swap To/From Stablecoins: ==Vis 1 => 44
> In the first part I tried to calculate the amount volume of NEAR exchanged to or from stablecoins, and for that I used near.core.fact_receipts table by filtering of receiver_id = 'v2.ref-finance.near' and method_name in Swap to find all transactions that executed by Ref-finance to swapping tokens.
I chosen 4 stablecoin such as USDC, USDT, DAI and USN as native stablecoin of Near ecosystem.
> I also separated the following metrics on this section by months of year and shown the share of each metrics per month.
Tokens TVL on Ref-finance. Vis 45 => 46
> This part is completely credited to CryptoIcicle#4958, I found this Query’s Link On flipsidecrypto discover.
Success/Fail Transactions on Ref-finance Vis 47 => 50
> For this part of research I excluded Success and Failed transactions by status_value column on near.core.fact_receipts table and calculated Success transactions per minute over the last year and Failure rate over same time, and shown these on a DOT graphs for a hourly time frame on days of weeks.
Staking On Ref-Finance Vis 51 => 57
> Finally, I decided to take a glance on Staking on Ref-Finance. We knew that xREF is the main staking contract (xtoken.ref-finance.near) on the platform. When you stake your REF, you effectively exchange your REF for xREF. Over time, you will always earn more REF by holding xREF tokens. So I excluded all transactions on near.core.fact_receipts table by receiver_id = 'xtoken.ref-finance.near' and calculated the amount of REF volume as Staked token and xREF volume as received token.
> # So come join us on this journey.
Swap ==TO== Stablecoin on ref-finance
- The first high point in the volume of transactions occurred on October 5, 2021. However, beginning in early November 2021 and continuing until early March 2022, daily transaction volume fell to below 500. The most purchases were made with each stablecoin on May 12th. Initially, we aimed to exchange for USDT with a transaction count of at least 3 thousand.
- The majority of unique swappers converted their NEAR to stablecoins, mostly more USDT, on October 4th, 2021.
- That date also saw the highest volume of volume swaps.
Conclusion
Swap To Stablecoins: ==Vis 1 => 22
> On October 5, 2021, transaction volume peaked. After that, daily transactions dropped to under 500 until March 2022. May 12 saw the highest stablecoin purchases. We had targeted for 3,000 USDT transactions. > > On October 4, 2021, most unique swappers switched NEAR to stablecoins, notably USDT. > > On that date, volume swaps peaked. > > The overall number of transactions and swaps grew consistently until late April, when they grew much quicker. The USDC overtook the DAI to become the second most commonly traded currency, behind only the USDT. > > Unique swappers and USDT and USDC volume. > > Swapped transactions and volume peaked in May. > > USDC followed USDT in volume and currency swaps. > > Most swappers use stablecoins in October. Swaps targeted USDT and DAI assets. > > On Oct. 5, 2021, swaps increased. From November 2021 to March 2022, daily transaction volume decreased below 500. On May 9, stablecoin transactions increased sharply. The first trading coin had around 2,000 USDT in transactions. > > On October 5, 2021, Stablecoins were converted to NEAR, more USDT.
Swap From Stablecoins: ==Vis 23 => 44
> Since late April 2022, more stablecoins have been exchanged for NEAR, with the most on June 13. On these dates, Ref-Finance converted over $1.3 million USDT to NEAR. > > The number of transactions and trading volume continuously increased until late April, when they suddenly surged and the USDC overtook the DAI to become the second most commonly traded currency, behind the USDT. > > 172,000 unique swappers shifted more than 250 million stablecoins to NEAR, putting USDC in second position for unique users and total swaps. > > May witnessed the largest volume and share of stablecoin Swapped transactions. > > USDC followed USDT in volume and currency swaps. > > Most swappers use stablecoins in October. USDT and DAI were traded for additional DAI.
Tokens TVL on Ref-finance. ==Vis 45 => 46
> The Stablecoins on Ref-Finance have attracted the largest share of the Total Locked Value. > > So, whereas USDT accounted for over 38% of Total Value Locked (TVL) on Ref-Finance, USN, the native Stablecoin of the Near ecosystem, ranked second with 36% TVL. > > With 10% of the TVL, wNEAR takes third place.
Success/Fail Transactions on Ref-finance ==Vis 47 => 50
> Since September 1, 2021, transaction failure rates have risen from 2% to 67%. > > Increasing failure rates reduce successful transactions from 33 to 4 per minute. > > According to the next chart, daily Success transactions fell and Failed transactions increased. More than 7% of daily transactions failed on October 10, 2021, and more than 90% on July 14, 2022. > > Ref-Finance on NEAR Protocol has 10.5 successful transactions per minute and a 20.9% fail rate. > Wednesday evening has the biggest positive signal (high sTPM and low TFR), whereas Friday morning has the opposite.
Staking On Ref-Finance ==Vis 51 => 57
> The first day of staking, January 12, 2022, saw the biggest volume staked and the most transactions. > > Most Staking trades and Volume happened in April and May. > > August had 4.8m Staked volume, followed by May. > > On April 7, Staking Volume rocketpulled.
About:
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Author: HaM☰d
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Discord: 0xHaM☰d#8391
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Twitter: @arjmandi_hamed
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Email: h_arjmandi2012@yahoo.com
Provide and explore key health metrics, as well as detailed data on at least 1 key project.
(TOURNAMENT ENTRANTS ONLY)
In your analysis, provide visualizations of USN, USDC and USDT breakdowns (i.e. which dapps and addresses hold the majority of USDC and USDT, and what cumulative flows to & from exchanges look like over time)
Partitions on this dashboard:
- Swapping Stablecoins From/To Near on Ref-Finance.
- Tokens TVL on Ref-finance.
- Success/Fail Transactions on Ref-finance
- Staking On Ref-Finance
Swap ==FROM== Stablecoin on ref-finance
- The number of swaps reached its highest point on October 5th, 2021, marking the peak of the trading activity. But after that, the number of transactions per day fell below 500, beginning in November and continuing until early March of 2022. On May 9th, there was a rise in the total number of transactions that took place across all stablecoins. The first token to be used as a switching source was USDT, which had a transaction count of more over 2,000.
- On October 5, 2021, the vast majority of one-of-a-kind swappers traded their Stablecoins for NEAR, which is equivalent to more USDT.
- Since the end of April, 2022, there has been an increase in the amount of stablecoins being traded for NEAR. As a result, the volume of stablecoins being swapped for NEAR reached its maximum point on June 13th. Therefore, on this date, more over 1.3 million USDT was converted into NEAR via the Ref-Finance platform.
Findings:
- Cumulative transaction count and exchanged volume were increasing steadily up until the end of April, but suddenly, on that date, they began to increase at a much faster rate, and USDC overtook DAI to take the second place spot, after USDT.
- The most unique swappers and the highest volume of switched goals have been achieved with USDT and USDC.
Findings:
- Cumulative transaction count and swapped volume were increasing steadily up until the end of April, but suddenly, on that date, they began to increase at a much faster rate, and USDC overtook DAI to take second place, after USDT, as the previous part stated.
- More than 172 thousand unique swappers moved more than 250 million stablecoins to NEAR, and USDC came in second position both in terms of the number of unique users and the volume of stablecoins switched.
Findings:
The line chart on the below shows the daily success transaction per minute (Purple line) and transaction fail rates (Red line)
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Since September 1, 2021, the rate at which transactions fail has climbed from approximately 2% to a value that varies between 67% and 100%.
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Because of the growing number of unsuccessful transactions, the number of successful transactions that occur each minute has decreased from 33 to 4.
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According to the following graphic, it is possible to see that the daily count of successful transactions has fallen while the number of unsuccessful transactions has climbed over time. Therefore, by October 10th, 2021, more than 7% of transactions failed per day, and by July 14th, 2022, that number had increased to above 90%.
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In the past year, the transaction success rate per minute for Ref-Finance using NEAR Protocol was 10.5, while the transaction failure rate per minute was 20.9%.
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The core Idea of this part credited to this Dashboard
Findings:
- The color assigned to each individual dot on the graphs The values of the related measurements are shown in the table below, with the hours of the day and days of the week indicated by their positions along the x- and y-axes, respectively.
- The transactions have the highest positive signal (high sTPM and low TFR) on Wednesday evening of each week, according to both graphs, however the signal is the opposite on Friday morning.
Findings:
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As of the time of writing this section, it has been determined that on the first day of the introduction of staking, the biggest volume staked and the most transactions counted took place on January 12th, 2022. This date was chosen as the launch date.
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Between the middle of April and the first ten days of May, the majority of transactions involving staking and volume took place.
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August was the month that had the most total Staked volume and transactions count other than, with 4.8 million total Staked volume; May was the month that came in second.
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On April 7th, there was a significant spike and rocketpull in the growth of Staking Volume.
Staking On Ref-Finance
Staking is the process of converting REF to xREF, with a percentage of trading fees used to buy back REF and send it to the xREF contract (xtoken.ref-finance.near). Over time, your xREF will give you more REF. Visit the xREF tab to have more details relating the rewards.link
Findings:
- May was the month that had the highest number of Swapped transactions as well as volume overall.
- The number of transactions, as well as the volume of swaps to and from USDT, placed it in first place, followed by USDC.
- In the month of October, the majority of unique swappers moved their transactions to stablecoins. and a greater number of trades were made to assets denominated in USDT and DAI, respectively.
Findings:
As expected the Stablecoins have had most Total Value Locked on Ref-Finance.
So that USDT with about 38%, USN as native Stablecoin of Near ecosystem was the second place with 36% of Total Value Locked (TVL) on Ref-Finance.
The third place are belongs to wNEAR with 10% of TVL.
> This part is completely credited to CryptoIcicle#4958 by this query
Findings:
- As was said in the previous section, the month of May had the highest number of Swapped transactions originating from stablecoins as well as volume overall.
- The number of transactions, as well as the volume of swaps to and from USDT, placed it in first place, followed by USDC.
- In the month of October, the majority of unique swappers moved their transactions to stablecoins. a greater number of assets denominated in USDT and DAI correspondingly were traded.
Hey there 👋!
Firstly, I appreciate you sticking with it until the conclusion.
I’m Hamed, Ph.D. In Civil Engineering and interested in data science.
I've made many similar dashboards and visualizations since I started at Flipside in January.
Please have a look at my various contact information and let me know what you think.