Getting Started with NFT OnChained (Part 1)
This article aims to help you get started with our NFT machine learning platform called NFT OnChained. It will walk you through the main features of the site and give some suggestions on how you can get the most out of the data presented.
The Price of NFTs
Most NFTs are unique. They possess a combination of traits that no other item has. This means that each NFT has its own price history. The rarer a combination of traits the more valuable an item tends to be compared to others in the same collection. We use machine learning to estimate the current value of each individual item within a collection.
Our machine learning model estimates the current fair value for each individual NFT within a collection
The screener is one of the main features of our platform. It displays the most mispriced items across all the collections we track. At the time of writing we are tracking 91 collections but we are steadily adding more.
The screener can be used to spot opportunities but it is recommended that you also consider other factors in your decision making process.
Screener page on nft.onchained.com
The more beneficial factors you combine, the higher your chance of success. Below is an example of the factors you might want to consider before entering a trade, assuming you are planning to sell the purchased NFT as soon as possible for a profit:
Example of factors to stack in order to increase the probability for a successful trade
Asset Card in Screener explained
The Screener page consists of asset cards which contain a lot information to guide you in your decision process:
Explanations of metrics displayed in asset card
Designing your own NFT trading strategy
Everybody has his/her own trading or investing style. Here we just want to mention some factors that you might want to consider when designing your own NFT trading strategy.
Factors to consider when designing an NFT trading strategy
Any NFT trading strategy has two big components. A set of rules which dictate when to enter a trade and a set of rules that dictate when to exit it. Exiting an NFT trade is trickier compared to cryptocurrencies listed on an exchange or on uniswap since you need to find a buyer. Liquidity can evaporate quickly — especially for smaller market cap collections.
Let’s discuss the points mentioned in the infochart above.
Entering a trade
You can use the screener page to identify mispriced items. The “Estimated Gain” metric shows the degree to which the item is currently mispriced according to our machine learning model. We often consider only items with an estimated gain of more than 50–100% to correct for estimate error and other unknown factors.
The term Floor Curve was coined by NFT OnChained. It shows the price of the 50 cheapest listings. It can also be viewed for specific traits (e.g. Cyberkongz VX with trait aquatic fur), or even for combinations of several traits. It can be useful to have a glance at how “steep” or “thin” the floor curve is. If it does not take a lot of sales to move the floor up significantly, it can increase the probability for a successful trade.
Example of a floor curve that is not particularly steep
Example of a floor curve having a steep slope
There are several collection-level metrics worth considering. We designed a traffic light system to indicate when a metric is bullish (green), neutral (yellow) or bearish (red). The level of liquidity can e.g. be assessed by looking at Volume 24h, Volume 7d, Sales 24h and Sales 7d. Fear and greed is a metric we derived from the percent of listings that are set to sell at a loss (below purchase price).
The trend is your friend. Choosing a collection that is in an uptrend is not a guarantee for success but it can increase the probability for a successful trade. The price charts can be viewed in the collection page.
Example of a collection that is currently in an uptrend
Another factor that people use in their trading strategy is “Whale buys” or “Whale watching”. If a big wallet (a whale) starts buying NFTs of a collection it can draw attention to it and the small fish start swimming in the whale’s wake. We have not yet implemented a “whale watching” feature yet but it is high on our priority list since we have the data to easily implement it.
Every trade has the chance to go bad so you have to think probabilistically and not risk everything on a single trade.
Exiting a trade
This point is very important. If liquidity — in other words the number of sales per day — is low, you will have trouble selling your NFT. The longer you hold an NFT the more you are subject to price risk. The quicker you manage to sell an NFT the quicker you have access to capital to invest in other opportunities. On the other hand, the biggest gains are often made by holding an NFT for a longer time period. Fundamental research of the project and team are required to determine whether holding for a longer time might make sense.
You can choose the listing price and thus influence the time it will take to find a buyer. The more attractive the price, the quicker it will sell. One strategy we employ is to lower the listing price gradually every 12 hours or every day. This has the benefit of making your listing visible for people who monitor the recently listed page on OpenSea. But what price should you choose? We often choose the price the model predicted before we bought the item and then — as mentioned — gradually decrease it until we find a buyer.
Another factor to consider is rarity. While common items are typically priced close to the floor, rarer items tend to be mispriced more often since they are more difficult to value. This is where machine learning price estimates can give you an edge. But you have to be aware of the fact that rare items are more difficult to sell than items close to the floor.
This is a wide topic which is outside the scope of this article. But in general it can be said that knowing certain fundamental factors such as
Quality of the team
Engagement and culture of the community
Upcoming events in the roadmap
can be great predictors of future success of a collection.
The fees that are incurred when selling an NFT can vary a lot depending on the collection. It can be viewed in the collection page.
The creator fee can vary significantly from collection to collection. OpenSea charges 2.5% on top.
The screener page on NFT OnChained can be a useful tool to spot mispriced items. It can be beneficial however to incorporate additional factors into your decision process. Some important factors are: Liquidity, collection metrics, price trend, collection fees.