CoinSpot
● Intermediate
Crypto Basics
Guide to On-Chain Metrics & Analysis
5 minutes
2 days ago
5 minutes
2 days ago
Because blockchains like Bitcoin and Ethereum are public and openly accessible, anyone can verify the information recorded on them by using certain software tools. This information is referred to as on-chain data.
Examples of on-chain data include any information related to transactions (e.g. senders, recipients, fees, timestamps) and blockchain addresses (e.g. token balances, number of transactions).
On-chain data is generally not very useful on its own. It is raw and unprocessed. In order to glean insights from this data, on-chain metrics are required. These are specific and quantifiable measurements that have all sorts of applications.
On-chain analysis is simply the process of examining and interpreting on-chain data and the metrics derived from it. It can offer unique insights into market behaviour, network activity, and more.
| Term | Definition | Examples |
|---|---|---|
| On-chain data | Raw information directly recorded on a blockchain network. | Transaction fees and token balances. |
| On-chain metrics | Specific and quantifiable measurements derived from on-chain data. | Miner outflows and market value to realised value (MVRV). |
| On-chain analysis | The process of examining and interpreting on-chain data to gain insights. | Assessing the behaviour of the top holders of a particular token over the past 90 days. |
On-chain metrics can reveal important trends about the behaviour of long-term coin or token holders and network activity. These insights may provide a unique layer of understanding that complements other forms of analysis.
For research purposes, it’s important to understand that on-chain analysis will be greatly impacted by the technique used by a given blockchain to track the balances of its native coin or token. For example, the Bitcoin blockchain uses the unspent transaction output (UTXO) model, whereas blockchains like Ethereum and Solana use an account-based model.
Miner outflows represent the total amount of coins transferred from miner addresses. An increase in this metric can indicate likely sell pressure since miners often need to sell coins to cover expenses (e.g. electricity, labour, mining equipment). Note that this metric is only relevant for blockchains like Bitcoin that use proof of work (PoW).
Bitcoin miner outflow over the seven years ending October 8, 2024 (Source: CryptoQuant)
MVRV is a ratio of a cryptocurrency’s market cap to its realised cap (i.e. the cumulative sum of every coin if it were valued at the price when it last moved).
When MVRV equals 1.0 means that the market is at a break-even point. Put differently, on average, holders are neither in profit nor loss, as the current market value is the same as the price they paid.
In general, an MVRV that is well above 1.0 suggests that prices have diverged from cost basis by a very large margin, meaning there are substantial amounts of unrealised profits within the market. The opposite is true for an MVRV that is significantly less than 1.0.
During bull markets, MVRV tends to spike as prices soar. Tracking MVRV across multiple assets can provide clues on which cryptocurrencies are becoming overvalued, helping investors avoid buying into inflated prices. Conversely, a low MVRV across many assets could indicate a buying opportunity during a market downturn.
By definition, Bitcoin’s MVRV ratio climbs well above 1.0 during bull markets (Source: Glassnode)
Dormancy is a ratio that describes the average number of days each coin transacted remained dormant or unmoved. It is calculated by dividing the total number of coin days destroyed by the total on-chain transfer volume.
In general, a relatively high dormancy indicates that long-held coins are returning to the market, which can suggest profit-taking or rising sell-side pressure. Low dormancy signals that coins moving are relatively fresh, which can point towards accumulation or active trading. However, dormancy metrics don't always indicate market sentiment, as old coins may move for various reasons (e.g. security upgrades).
Bitcoin’s average coin dormancy over the seven years ending October 8, 2024 (Source: Glassnode)
On-chain analysis has limitations, which is why it is often used in combination with other types of analysis (e.g. fundamental, sentiment, technical) to inform decision-making.
One limitation is that it can be difficult to draw accurate conclusions in certain scenarios due to off-chain activity. For example, centralised exchanges facilitate the buying and selling of cryptocurrencies, but these transactions are not recorded on blockchains.
Another limitation is the reliance on third-party platforms to accurately decode on-chain data. While blockchain data is public and transparent, sophisticated software is often required to read, label and present this data for people to use for their analysis. If these platforms incorrectly label or process on-chain data, it can lead to incorrect conclusions and misguided decisions.
On-chain analysis can assist with understanding the crypto market and network activity much more deeply. While it has its limitations, like any form of analysis, on-chain analysis can unearth unique insights that can make for a more well-rounded and nuanced decision-making process.
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