On-Chain Analytics - Part 1: Introduction and Timeline
One of Bitcoin’s most unique attributes (as is the case with all public blockchains) is that all digital asset transfers that occur ‘on-chain’ are publicly visible. By unlocking the power of blockchain data, it is possible to gain valuable insights into the decentralized economy and better inform one’s investment research and analysis. With the right knowledge and tools, anyone can become an on-chain analytics expert. All the tools are open, accessible, and permissionless. And insofar as market participants are able to tell how much of a native blockchain’s assets are held by any particular address, all their operations can be mined for crucial ‘consumer behaviour’ information: i.e. market intelligence. This beginner’s guide will provide an overview of what on-chain analytics is, the benefits of using it, and how to get started.
Blockchain tech has revolutionized the way we interact with currencies, securities brokers, markets, exchanges, trading platforms, and fin-tech applications. As a result, the need for understanding on-chain analytics is greater than ever.
Unsurprisingly, in the world of public blockchains, this study is called On-Chain Analytics. On-chain analytics is the process of extracting, analyzing, and visualizing data from public blockchains. This is an introduction to that study, as well as an overview of its most commonly used ‘metrics’ and what information can be gleaned from their analysis.
What Are On-Chain Analytics?
To improve investment and trading decisions, on-chain analysts examine the fundamental factors of cryptocurrencies–but on-chain.
In particular, it involves reviewing public blockchain transactions and wallet balances, which can be helpful information to have on hand when doing investment research. (For example, investing in a token that has little or no on-chain activity and is largely concentrated in the hands of a few large holders–known as whales–may not be the result of a career-best risk/reward analysis).
These ideas can be developed and applied by traders who want to utilize public blockchain information to enhance their trading strategies and position management.
The study of price action, or technical analysis, is perhaps the most prevalent form of analysis in cryptocurrency trading. Nevertheless, public blockchains like Bitcoin and Ethereum provide a wealth of information that complements other analyses and offer a unique perspective.
A Brief Timeline of On-Chain Analytics
On-chain metrics started with coin days destroyed (CDD–which we’ll define here later). In 2011, Bitcoin Talk user ByteCoin created it as a way of analyzing the age of bitcoins transferred on a particular day in order to measure market health (by determining how long the average bitcoins were being held in wallets).
Gbianchi, another user on the bitcoin talk forum, posted a thread in 2014 titled "Network Value" based on Metcalfe's Law... A later iteration of HODL waves was posted by Jon Ratcliff in the same year.
In 2017, Willy Woo, one of the most prolific on-chain analysts, developed the network value to transactions ratio (NVT) metric. Several on-chain analysis companies were founded in 2017, including Glassnode, Coin Metrics, and others - as well as Messari, Dune Analytics, and more.
Dmitry Kalichkin introduced a new metric called Network Value to Metcalfe Ratio (NVM) in early 2018. Dhruv Bansal from Unchained Capital then released an update to HODL waves.
Coin Metrics' Nic Carter and Antoine Le Calvex revealed realized capitalization towards the end of the year, which displayed the total value of bitcoins last moved. Based on Market Value to Realized Value (MVRV) by David Puell and Murad Mahmudov, Tamás Blummer proposed liveliness to measure bitcoin hodling behavior.
On-chain analysis has seen a huge increase since those rapid developments in 2018. As a result of this growth, there have been numerous new data providers, analysts, and metrics developed (over 75 on glassnode alone). Traders can also discuss network growth rates via tic-tac-toe, a big change from the message board style forums of a decade ago.
It has proven extremely useful to have an arsenal of valuation tools and fundamental-based metrics to analyze the health of blockchains. Although most were developed specifically for bitcoin (and remain so), they may be applied to other large blockchains (such as Ethereum).
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