Introducing cohort-based on-chain analysis. Part 1: Realised price
This article is the first in a series of articles that will be applying cohort-based analysis to on-chain metrics such as SOPR, MPL and On-chain volume.
In this short piece, an improved version of the Realised price metric will be introduced. It allows splitting Realised price (an average price that the circulating supply of Bitcoin was obtained by wallets on the blockchain) depending on how large the wallet is (large players, whales, retail, etc).
This way one can find out what is the average price whale or retail wallets have obtained their Bitcoin for.
Before we begin, it is important to give credit to Coinmetrics that have introduced the concept of Realised Capitalisation that this new metric is built upon. For more details about the evolution of on-chain metrics, please refer to this article by Adamant Capital.
Structure of this article is as follows: we begin by explaining the concept of realised capitalisation as this is what ultimately lies at the foundation of realised price and many other metrics. After that, we will dive deep into cohort-based analysis and see how it can be used to partition realised cap by wallet-size cohorts. Naive Realised price and realised price split by address cohorts is presented at the end of the article.
What is realised capitalisation?
Realised capitalisation is the total dollar value of the current circulating supply of bitcoin.
How is realised capitalisation different to market capitalisation? Market cap is calculated by multiplying the total number of available stocks a company has by their last traded price. Market cap can also be said to be the total dollar value of the company’s stock. However, Market cap is only an approximation to the total dollar value whereas realised capitalisation is as close as you can get to it. Here is an example,
If you know that
— investor A paid $100 for 1 stock
— investor B paid $200 for 1 stock
— investor C paid $300 for that 1 same stock
the total dollar value of a company will be 1*$100 + 1*$200 + 1*$300 = $600. (as a heads up — realised capitalisation is calculated in a similar fashion)
Unfortunately, if you lose information about the original buying price, which is usually the case in legacy markets, the only way for you to measure the total dollar value of a company will be its market cap. For example, if the last traded price of the company’s stock is $400,
the Market cap will be (1+1+1)*$400 = $1200. This value is significantly different from the value we obtained using the first calculation method.
However, information about the original buying price is not lost in Bitcoin!
In bitcoin, you can refer to the blockchain and find out exactly where each bitcoin was obtained by any given wallet!
Hence, there are two ways to calculate the total dollar value of the circulating supply of bitcoin:
1. Market capitalisation = circulating supply*last traded price
2. Realised capitalisation = ∑ (amount of bitcoin*price at the time that bitcoin was obtained by a wallet)
What follows from this, is that since we now have the information about the original acquisition price of every Bitcoin, we can also find out if market participants are making a profit or a loss.
Are Bitcoin market participants at a profit or at a loss?
After we got the concepts of market and realised caps out of the way, we can start going deeper and try to distil insight from what we have got so far.
By comparing Market cap to Realised cap first, we get the following result.
From this, one can see that Market cap and Realised cap have different values, and that most of the time, Market cap is above Realised Cap.
When Market cap is higher than realised cap it means that the current market price of Bitcoin is higher than the average price that market participants have paid for their BTC. This in turn means that market participants are on average in profit!!!
The opposite goes for when Market cap is lower than Realised cap, i.e. it means that on average, market participants are at a loss.
This type of insight is unique to cryptocurrencies!
But what if we want to know if only whales are in profit? What about retail traders? Are they in profit or at a loss?
One can get the answer by using cohort-based on-chain analysis
Cohort-based analysis of Realised price
Cohort-based analysis of Realised capitalisation and ultimately Realised price (which is introduced shortly) is what is needed to find out if different types of market participants (whales/retail) are at a profit or at a loss.
Getting straight into it, since Realised cap is the total dollar value that wallets participants have obtained their BTC for, we can start dividing market participants by cohort and finding out their respective Realised caps.
However, since we want to know the average price that market participants have acquired their Bitcoin for we need Realised price:
Realised price = Realised Cap / Circulating supply of Bitcoin
i.e. Realised price is the average price that the circulating supply of Bitcoin was obtained by wallets on the blockchain.
Finalising the analysis and plotting realised price partitioned by wallet-size cohort, we get the following:
This type of analysis is what cohort-based analysis ultimately is. You can apply it to other on-chain metrics such as MPL and see what portion of moving profits belongs to whales or apply it to on-chain volumes and find out the relative activity of different wallet-size cohorts.
Zooming in one can notice that some cohorts provide support and resistance to Bitcoin price
We can see that 10–100 BTC cohort is the ultimate, most important cohort that has been providing support for BTC’s price action so far. It is super interesting why this is the way it is.
Looking at price action in the period of 2017–2020 we can also notice that Realised price split by wallet cohorts provide accurate support levels for Bitcoin price action.
One reason why this metric works so well is due to psychology. Since Realised price is the average price that the circulating supply of Bitcoin was obtained by wallets on the blockchain, whenever price is above a certain band, wallets in that band will be reluctant to sell at prices lower than their average acquisition price. Hence, when Bitcoin price is above a given band, that band will act as support.
As soon as Bitcoin price gets below a band, market participants will be looking to sell to break even at their average buying price. Hence, when bitcoin price is below a given band, it will serve as resistance.
This concludes our first exploration of applying cohort-based analytics to common on-chain metrics.