NFTGo Column | Where Does Value Come From: Are Blue-Chip NFT Rarity and Price Related?

This article is written by NFTGo

In many cases, people are willing to pay a premium for rare items or unique experiences. As the saying goes, rarity adds value. But in the world of NFTs, how do we quantify the rarity of this digital asset and its equivalent value?

From a purely business perspective, many assets originally do not require any form of supply restriction, but the value of rarity will affect the total demand from consumers and the market. Artificially designing rarity and quantity will have different effects. The economic notion of rarity value is rooted in the concept that resources are limited, demand is infinite, and price serves as a signal of resource scarcity.

The rarity value of blue-chip NFTs can be measured from the following four points. One is the scarcity of the NFT project itself—each Collection issues a specific number, mostly around 10,000.

The second is the rarity value compared to other NFTs in the total collection. Rarity is closely related to the concept of conspicuous consumption—"exclusive feeling" and the similarity and aesthetic appeal of NFTs and their owners represent a certain attitude and emotional value, as in the case of Jay Chou's ownership of Azuki and its inherent characteristics.

The third is the utility value brought by the scarcity effect of NFTs, or the premium, including the joy of buying and selling NFTs, and the various applications and extensions in the new fields of GameFi and the metaverse.

The fourth is the difficulty of acquisition or time value. Rarity value also reflects the cost of community maintenance. For example, the increase in operation and maintenance costs of some community PASS will be reflected in the price, forming a closed-loop flywheel.

So, is rarity the dominant factor in pricing? Since January, although the overall trading volume of NFTs in the market has declined, blue-chip projects under the early market consensus continue to rise in price due to their scarcity, reflecting consumers' positive expectations for top-tier assets.

We can quantify the intrinsic correlation between NFT prices and rarity through data to explore possible rules and patterns. We selected six distinctive blue-chip projects to evaluate the impact of NFT rarity on their prices.

TL; DR

• Holders of rare NFTs have pricing power more than 10 times that of ordinary NFT holders.
• Contrary to the common belief that "rare NFTs are more expensive," the impact of rarity on price is not entirely positively correlated.
• The influence of rarity sometimes gives way to aesthetic value, community consensus, and other factors that are more implicit than rarity.
• Although medium NFTs have a higher rarity ranking in the market than bottom NFTs, the tiered effect on market prices between the two is not significant. The value of top NFTs far exceeds that of medium NFTs.
• Among the six projects listed, the correlation between rarity and price is strongest for Doodles, while BAYC evidently has other variables affecting its price.

Note: Based on different levels of rarity, we divided NFTs into four groups, with x representing the degree of rarity:

90 ≤ x ≤ 100: Legendary

70 ≤ x < 90: Rare

40 ≤ x < 70: Classic

0 ≤ x < 40: Normal

Is the Highest-Priced NFT also the Rarest?

The price of different NFTs is influenced by rarity in varying degrees. The chart below shows the rarity and total circulation time on the secondary market of the top ten highest-priced NFTs in various collections.

In many cases, people often use various tools to determine rarity. However, besides collectible value, other values of NFTs can significantly dilute the impact of rarity on prices. Rarity sometimes gives way to more subtle factors like aesthetic value and community consensus.

CryptoPunks, positioned more towards OG NFT projects, naturally hold collectible value as the first NFT project, making rarity crucial in the collecting experience. On the other hand, projects like BAYC, although a classic and early blue-chip NFT, derive value from the community and business ecosystem behind them, which diversifies the impact of rarity on their prices. The proportion of legendary rarity among the top ten highest-priced NFTs has significantly decreased compared to CryptoPunks.

Therefore, from the perspective of different project positioning, the highest-priced NFT may not necessarily be the rarest.

Does Rarity Affect Price Tiers?

By contrasting data on two types of NFTs with different rarities - the most common "Normal" and the most rare "Legendary" (comprising the bottom 40% and top 10% respectively), we can see that rarity affects prices differently in various collections. For PFP projects, generally, higher rarity corresponds to higher prices, with NFTs possessing 1/1 top traits often commanding higher prices. As shown in the chart below, the significant rarity differences in projects like Cryptopunks and Doodles lead to a surge in average NFT prices. However, for BAYC, rarity does not create clear price tiers, indicating that rarity does not necessarily reflect the core value of the NFT.

Head and Tail Effects

After comparing the price gap between the highest and lowest rarity tiers, another question commonly encountered by users is how to choose NFTs within the lower 90% of rarity if they cannot afford the high-priced NFTs within the top 10% rarity tier. By analyzing NFTs with rarity rankings between 2000 and 4000 as a dataset (termed Medium NFTs) and comparing them with NFTs ranked beyond 4000 (termed Bottom NFTs), we can assess if Medium NFTs, presumed to contain rarer NFTs than Bottom NFTs, indeed command higher prices. The chart below displays the average sale prices of these two categories of NFTs.

It is evident that there is a clear distinction in price between NFTs with higher rarity rankings and those with lower rankings. To study the impact of high rarity, NFTs with Legendary rarity are included by selecting NFTs ranked within the top 2000 (termed Top NFTs). The chart below illustrates the average price of each group of NFTs (in USD).

It is clear that while Medium NFTs hold a higher status in the market than Bottom NFTs, the market price tiering effect between the two categories of NFTs is not significant. On the other hand, although Medium NFTs are relatively rarer in the market, the value of Top NFTs far exceeds that of Medium NFTs. Evidently, a "head effect" influences NFT prices.

There are various trading behaviors in the market, with terms like "floor sweeping" and "collecting top traits," but discussions regarding collecting mid-rarity NFTs are less common. Even in GameFi projects associated with rarity and gold farming, collecting mid-rarity NFTs appears less economically viable due to psychological and economic reasons, indicating a certain "disconnect" in the impact of rarity on prices within the mid-tier.

Which NFT Collection Exhibits the Strongest Correlation?

To further confirm the correlation between rarity and price, z-score standardization and Pearson Correlation Coefficient analysis were utilized to assess the pricing power of NFT collections and reevaluate the impact of rarity on prices. It is essential to note that there are biases and variables in the analysis of prices and rarity due to differences in holding time and purchase times. Additionally, based on dynamic factors such as secondary market circulation time, project activities, and differentiation, an in-depth analysis of the characteristics of different collections was conducted to assist investors in better planning their investment strategies and profit expectations in the NFT market.

Observing the data sets, it is apparent that while some collections like BAYC exhibit a normal distribution, the data distribution of NFT collection prices remains non-normal, indicating a relatively minor impact of rarity on prices. In scenarios where the price data set shows a non-normal distribution, a QQ-plot method was employed to verify if the data conforms to a normal distribution. The red line on the chart represents data that fits a normal distribution, while the points represent actual data.

While some parts of the data set conform to a normal distribution, it is crucial to consider all outliers when selecting an analysis method. Generally, NFT prices tend to exhibit a non-normal distribution, with studies confirming that this trend leads to errors in estimating the Pearson Correlation Coefficient.

Non-normal distributions inflate the correlation coefficient by +0.14. Therefore, a more robust approach, the Spearman Correlation, was utilized to provide a conservative estimate of the correlation between rarity and price. The simplified formula for the Spearman Correlation is shown below.

The result of this formula is a value between -1 and 1, indicating complete positive or negative correlation. A value closer to 0 signifies a non-positive correlation. The Spearman Correlation varies significantly between different collections, with some collections showing minimal correlation between rarity and price, suggesting the presence of other variables, while in others, rarity and price are significantly correlated. The chart below illustrates the difference in analysis results between Pearson and Spearman Correlation.

The research findings indicate that the Spearman algorithm yields smaller errors, whereas when using the Pearson Correlation, the estimates for all collections are either too large or too small due to the presence of non-normal distributions.

Ultimately, the statistical results reveal that among the six projects examined, Doodles exhibit the strongest correlation between rarity and price, while BAYC evidently has other variables influencing prices, perhaps explaining why BAYC has become one of the most successful NFT projects in history, with people valuing more than just a rare monkey but also the additional value it brings.

Is Price Defined by the Community or Rarity?

Similar to Panini NBA trading cards and rare game cards, when the player base of a collectible type is large enough, price tiering occurs. The same applies to NFTs, where price tiering is not solely influenced by rarity but more so by the community. For instance, communities like mfer and StartCatchers, with different Dynamic Traits, define their own hierarchy: 3 dynamic traits > 2 > 1 > all static. The value of mfer projects lies in the cultural consensus behind them, resonating with numerous holders who see themselves reflected in the NFT image. Rarity's influence on price is greatly diluted, replaced by aesthetic resonance and community consensus. Additionally, NFT prices are correlated with the celebrity effect, with Trait NFTs associated with celebrities commanding prices higher than the average. For example, many opt to purchase NFTs with traits identical to those held by celebrities like Jay Chou, driving up the prices of such NFTs.

Therefore, in NFT issuance, projects need to be well-thought-out. Community-driven gameplay makes it easier to promote and increase circulation, with the gameplay hidden in PFP project images being a crucial consideration. Furthermore, for projects aiming to create NFT valuation tools, understanding that NFT value is determined by multiple factors is essential. PFP projects, through collaborations and meme propagation, redefine rarity, subtly boosting NFT prices.

Conclusion

By constructing a data analysis mechanism, we explored the correlation between NFT rarity and price, quantitatively analyzed NFT pricing power, and reevaluated the impact of rarity on prices. It is important to note that biases and variables exist in the analysis of prices and rarity due to differences in holding time and purchase times. Additionally, based on dynamic factors such as secondary market circulation time, project activities, and differentiation, an in-depth analysis of the characteristics of different collections was conducted to assist investors in better planning their investment strategies and profit expectations in the NFT market.