Original author: NFTGo, CoinMarketCap
core point of view
NFT transaction volume rose sharply in the first quarter of 2023, but then declined. Blurs incentive and airdrop mechanism is the main driving force. On April 19, the number of NFT holders fell to a 12-month low of 11,187 traders.
OpenSea still dominates the NFT royalty market, but Blurs royalty share surpassed OpenSea in mid-February and was on par with OpenSea in March. Blurs optional royalty and zero-fee strategy has attracted price-conscious users. In addition, the number of wash trades on Blur is gradually decreasing, which shows that the real traders in this market are settling down.
Affected by the bear market at the end of 2022, the profitability of blue-chip NFT projects dropped significantly in the first quarter, but some projects still performed well. BAYC has the strongest profitability in the sellers market, and Azukis whale count has increased by 100%, making it one of the most resilient blue-chip NFT projects this year. The profit fluctuations in the NFT market are still affected by the trading status of blue-chip giant whales, and at the same time, there is a significant gap in the assets of traders between different projects in the market.
There are several ways to generate income through NFTs, and profitable NFT traders can be divided into three categories. Including buying high-quality NFTs at low prices at the right time and holding them for a long time, casting NFTs in batches from niche projects and selling them at high prices, or anchoring more promising NFT categories for short-term high-frequency trading profits.
In the past four months, the trading volume of the Bitcoin Ordinals market has shown an upward trend, but it still only accounts for 0.02% of the ETH market. Due to the slow transaction speed, high cost and limited application range of Ordinals NFT, Ethereum NFT still has advantages in terms of application range and speed.
The NFTFi loan market recovers in the first quarter of 2023, with approximately $25 million in NFTFi loans from January to March. Among them, ParaSpace occupies the largest market share in the lending market this quarter, while NFTfi leads in the number of NFT lending users.
Chapter 1 Market Overview
Ups and downs of the NFT market
image description
NFT market value and trading volume in 2023, data source: NFTGo
image description
Trends of NFT holders and traders in 2023, data source: NFTGo
image description
Trends of NFT Holders and Traders 2021-2023, data source: NFTGo
image description
BAYC floor price, data source: NFTGo
The NFT market is not in decline, but is in the early stage of the second major cycle, and has a certain lag compared to the overall encryption market. In the NFT Annual Report 2023, we calculated that the average correlation coefficient between the Ethereum market and the NFT market is 0.76. The NFT market reaction is not as sensitive as the traditional cryptocurrency market. When the market is volatile, the NFT market usually does not react immediately. For example, when the price of ETH fell, the U-standard price of many blue-chip NFTs fell relatively small.
image description
Comparison of NFT market value and ETH market value trend, data source: NFTGo
When we extend the NFT time to two years, the number of NFT holders increased by 10 times. However, the volume of the NFT market is still small, and the market value of the NFT market on Ethereum is about 1/10 of the market value of the entire Ethereum.
secondary title
Ethereum dominates NFT transactions
image description
NFT sales volume by public chain(USD, 2023.03.27 ~ 04.26). Data source: Dune Analytics
From the perspective of the number of transactions, Ethereum Q1 still ranked first with the number of transactions accounting for about 50%, and the monthly transaction frequency remained within 1 to 2 million. Polygon is no longer in the situation where the transaction frequency accounted for half of the country in the second half of last year. At the beginning of this year, the proportion of Polygon transactions dropped significantly, and the number of transactions per month was less than 100,000.
Solanas multiple accidents, such as the inability to generate blocks normally led to the failure of transactions, the bankruptcy of FTX, etc., caused Solanas performance to continue to sluggish in early 2023. Intense competition from Ethereum and polygon and other new platforms also made Solanas quarter worse, and transaction activity continued to slowly decline.
NFT trading market and wash trading
Blur becomes the new darling of the trading market
image description
Comparison chart of trading volume in the NFT trading market (after cleaning transaction data is removed), data source: NFTGo
image description
Ranking of NFT trading platform trading volume in 2023, data source: NFTGo
Unexpected wash trade
image description
image description
The proportion of Blurs real transactions, data source: NFTGo
image description
Ranking of real trading ratios in each trading market this year, data source: NFTGo
Blur Royalties Share Surpasses OpenSea
image description
Royalty Transaction Change. Source: Dune Analytics
Royalties surge for blue chips as OpenSea and Blur battle royale
image description
Royalty fees for blue-chip deals. Source: Dune Analytics
NFT market fee competition
image description
NFT market fees. Source: Dune Analytics
Chapter 2 Micro Trends and Liquidity
Micro Trends of NFT Project Issuance
NFT floor price vs. illiquidity analysis
image description
Dead NFT collection number
Among these illiquid NFT projects, the floor price of about 69% of the projects returned to zero within 6 months, 48% within 3 months, and 18% within 7 days. It can be seen that more than half of the projects in the long run Lack of liquidity NFT will be left out of the priceless and marketless state.
The market conditions of non-trading NFTs cannot be seen from the short-term period of one week, but if the time is extended to 3 months or even 6 months, about 30% of NFTs have not returned to zero, and it can be clearly seen that about one-third of non-trading NFT has a price but no market situation.
image description
Project market value distribution map, data source: NFTGo
After screening and sorting the projects included in NFTGo, more than half of the projects have a market value of 100 to 1000 ETH (approximately $0.21 M to $2.1 M), followed by 0 to 100 ETH, a total of 1550; and 100 k ETH and above There are 125 items.
1% of projects account for more than half of the NFT market capitalization
image description
image description
Top 10 projects and market value, data source: NFTGo
A transaction volume of 1 k ETH is the threshold for NFT projects
image description
Trading volume distribution interval ratio chart, data source: NFTGo
image description
Project transaction volume distribution map, data source: NFTGo
image description
Projects with transaction volume greater than 100 K ETH, data source: NFTGo
NFT price range distribution
image description
The number of NFT projects in different price ranges, data source: NFTGo
The distribution status of NFT items in each price range is mainly due to two factors. From the comparison of data, one is related to the initial issue price of the project. The issue price of most projects is between 0 and 0.15 ETH. Since many NFT projects do not have physical assets, different projects imitate each others pricing, making the bottom of the NFT market Data homogenization of the project. The second is that there are resistance values in each price range, such as 0.1 ETH, 1 ETH, 10 ETH and other integer prices. The prices of some NFT projects will encounter resistance when they touch these values, hovering at the edge of the price range or quickly falling to the next resistance value.
Analysis of NFT liquidity and characteristics
How Market Activity Affects Buying and Selling Efficiency
image description
Liquidity trend chart, data source: NFTGo
Liquidity comparison of different projects
The liquidity of different projects is also very different. The overall feature is that the top-ranked NFT projects maintain a certain degree of liquidity for a long time, and the volatility of liquidity is low. On the other hand, the liquidity of the lower-ranked NFT projects gradually tends to zero after issuance and is greatly fluctuated by the market.
image description
Comparison chart of projects with better liquidity, data source: NFTGo
Chapter III Main Items and Events
NFT project trend analysis
Blue chip NFT reshuffle?
image description
Blue-chip NFT PNL changes from 2022 to 2023, data source: NFTGo
image description
Blue-chip NFT PNL changes in 2023, data source: NFTGo
image description
Blue-chip NFT related data in 2023, data source: NFTGo
image description
Blue chip NFT holders and whale related data in 2023, data source: NFTGo
image description
Top 10 holders of Azuki giant whales, data source: NFTGo
These data all show us that the blue-chip NFTs in the market completed a relatively large change of hands from January to April this year, which is manifested in:
1. The rebound in the Q1 market made some blue chip holders profit and choose to sell.
2. The distribution of blue chip holders has become more concentrated, and the proportion of giant whales among holders is increasing.
3. The price of blue chips generally fell by as much as 50%, but Azuki bucked the trend.
New NFT lacks continuous market
image description
New NFT project data in 2023, data source: NFTGo
image description
Weekly NFT trading volume in 2023, data source: NFTGo
image description
Degods floor price trend, data source: NFTGo
List of Most Expensive NFTs in 2023
What are the events to watch in 2023?
The BTC Ordinals market still has room to improve
BTC NFT is a non-homogeneous token on the Bitcoin public chain. However, the transaction speed of BTC NFT is slow, the cost is high, and the usage scenarios are relatively limited. ETH NFT is a non-homogeneous token based on the Ethereum blockchain technology, supports smart contracts, has fast transaction speed, low cost, and a wider range of usage scenarios. Creating an NFT on Bitcoin is much more complicated than on an NFT-enabled blockchain such as Ethereum, because Bitcoin was not designed for creating NFTs. But it is possible to use Layer 2 protocols (Layer 2 protocols) to create NFTs on Bitcoin, including the Lightning Network (Lightning Network) and RSK (Rootstock).
The auction of the Bitcoin NFT series TwelveFold launched by Yuga Labs on March 6 pushed the Bitcoin NFT to a new climax: there are a total of 300 NFTs in this series, the lowest winning bid price is 2.25 BTC, and the highest winning bid price is 7.11 BTC. The popular NFT blue-chip project Boring Ape has a floor price of 61.59 ETH, worth 3.95 BTC.
image description
Number of Ordinals NFT minted, data source: NFTGo
However, its transaction volume is only 0.02% of the ETH market, and there is a large gap. The main reason for this gap is that the Ethereum network has stronger smart contract functions and higher transaction speeds, and ETH NFT is more attractive. At the same time, ETH NFT also has a wider range of application scenarios, such as games, artwork, real estate and other fields. These factors have contributed to the ETH NFT market becoming mainstream.
Gem v2 brand upgrade to OpenSeaPro, airdrop Gemesis NFT
image description
Price and sales volume of Gemesis, data source: NFTGo
image description
Gemesis minting volume and holders, data source: NFTGo
From the perspective of Holder Trends, the total number of traders of giant whales and blue-chip holders is less than 7%, and the total number of Gemesis NFT holdings is less than 12%. The large proportion of assets owned by ordinary holders is also one of the reasons for the relatively stable floor price .
Chapter 4 Analysis of Traders and Giant Whales
What is the distribution of assets per capita?
After eliminating invalid items, we calculated the per capita assets of a single item. The average per capita assets was $3,893, the median was $1,459, and the average was 63% higher than the median, which means wealthy The assets of the project have greatly increased the overall per capita assets, which has widened the gap between the rich and the poor among users of different projects.
image description
Ranking of top projects per capita assets, data source: NFTGo
The stratification of per capita assets also allows NFT players to form groups with different consumption capabilities, allowing NFT and infrastructure project owners to design products and stratify marketing for different user needs.
User single asset distribution
Calculate the interval per capita assets of 748 qualified NFT projects, of which the main distribution area of NFT projects is below $2000, and projects with per capita assets of $500 to $2000 account for 52% of the total, and this part of users is also the majority There are a total of 233 core users owned by NFT projects.
image description
image description
Single asset per capita ratio, data source: NFTGo
Analysis of NFT giant whale assets
Proportion of giant whale assets
image description
The proportion of giant whale assets, data source: NFTGo
image description
This years buying and selling power comparison chart, data source: NFTGo
image description
The top 10 NFTs favored by giant whales and the average purchase price, data source: NFTGo
Trend and Behavior Analysis of Giant Whales
image description
Comparison of trading funds of giant whales, data source: NFTGo
image description
Comparison of the net worth of giant whale funds, data source: NFTGo
Who is making money and how?
image description
Top 10 PnL Trader, data source: NFTGo
Through the analysis of the profit leaderboard, the characteristics of the profiteers are mainly divided into three types.
1. Buy a large number of high-quality NFTs at low prices and hold them for a long time. As shown in the figure below, the user holds 145 CryptoPunks and 171 Meebits through continuous purchases. The rising market brings good returns.
2. Casting niche projects in large quantities and completing high-priced shipments, as shown in the figure below, after the user mint has a large number of NFTs, they will sell them at high project prices to complete the shipments.
3. The type of trading NFT is fixed, and the trading frequency is high. As shown in the figure below, the user chooses Otherdeed as the trading target, and realizes profits through high-frequency trading.
Profitable bargain-hunting logic
For a single NFT, buy in batches (3 batches) according to the range, and buy only when you enter your own valuation range.
Buy according to the decline rather than time, the greater the decline, the more you buy.
Try to buy the bottom by way of Offer bidding, sometimes there will be a good buying cost.
Buy bottoms for big blue chips classified by rarity, and buy bottoms for new blue chips with diversified combinations.
You can try multiple platforms such as Blur, X2Y2, LooksRare, not limited to OpenSea.
Chapter 5 NFTFi and Valuation
NFTFi Development Status
The NFT market is currently facing two major problems. First of all, the value assessment of NFT depends on the liquidity of the market, and the lack of rich and multi-dimensional value assessment methods reduces the value discovery and liquidity of NFT. Secondly, NFT itself has limited practicability and functionality, and cannot be linked with the mainstream cryptocurrency market, and can only be used for small-scale dissemination. This has also created many opportunities for the NFT+ Finance track.
NFTFi Project Comparison
image description
Total amount of NFTfi monthly loans (USD, 2023.01-2023.04), data source: Dune Analytics
image description
NFTs weekly lending market share of various institutions (USD, 2023.01-2023.04), data source: Dune Analytics
image description
The cumulative number of NFT loan users (2023.01.01-2023.04.26), data source: Dune Analytics
image description
Blends lending times per hour, data source: Dune Analytics
NFT Valuation Framework
At present, NFT valuation is generally divided into several methods such as weighted average price, machine learning algorithm pricing, industry evaluation pricing, manual bidding, and game pricing. And each method has corresponding advantages and disadvantages. First of all, TWAP and other forecasts and quantitative models are very affected by the amount of data (the number of market transactions, the number of NFTs in the collection, etc.); and are easily affected by the market, difficult to deal with future emergencies, and subject to human manipulation (eg.wash trading).
Through financial tools and peer reviews are also ways. On the one hand, the market balance can be achieved through the game mechanism, and at the same time, the price can be corrected through the market performance. However, this method is difficult to evaluate NFT on a large scale, and is more suitable for pricing an NFT.
Trait-based machine learning is based on traits that have a greater impact on NFT prices, and it is impossible to predict collections without traits. However, in the collection that is greatly affected by traits, the application of machine learning algorithms works well. Currently, NFTGo provides APIs for machine learning algorithms, covering most mainstream NFTs, with an accuracy rate of over 90%. The key can be obtained by filling out this form.
