What is On-Chain Analysis and what are its applications? The Crypto Investor's Guide To On-Chain Data Analysis

On-chain analysis is an advanced and specialized method for analyzing cryptocurrencies, which leverages the data available on the blockchain to gain a deeper understanding of network behavior, transaction trends, and to predict price movements. This type of analysis is based on the transparent and decentralized information recorded on the blockchain, allowing analysts to make more accurate inferences about the status and future of cryptocurrencies by examining various parameters.

Key Components of On-Chain Analysis

On-chain analysis involves examining several key variables, each of which can provide important insights into market conditions and user behavior. Below are some of these key variables:

Transaction Volume: One of the most important indicators in on-chain analysis is transaction volume. This indicator reflects the level of activity within a blockchain network and can help determine price trends. Sudden increases or decreases in transaction volume may signal significant changes in the market.

Miner Rewards and Transaction Fees: The rewards given to miners and the fees paid by users for transactions can provide information about the security and activity of the network. These data also help analysts assess whether the network is attracting new users.

Price Correlation of Cryptocurrencies: By analyzing on-chain data, it is possible to assess the correlation between the price of a cryptocurrency and other currencies or market indices. This correlation can help predict future price behavior. 

Inflow and Outflow of Assets in Various Markets: The amount of cryptocurrencies moving in and out of exchanges is a key indicator for on-chain analysts. This metric can indicate whether users are inclined to buy or sell their assets.

How On-Chain Analysis Works

On-chain data includes all information related to transactions and activities conducted within a blockchain network. This data comprises details such as transaction fees, miner rewards, the amount of circulating cryptocurrencies, and many other specifics. Analysts use this information to calculate and examine various metrics to predict future market behaviors.

Three Main On-Chain Analysis Indicators

1. Market Capitalization: As one of the most important on-chain indicators, market capitalization reflects the total circulating value of a cryptocurrency in the market. This indicator helps analysts compare the real value and market value of a cryptocurrency to identify investment opportunities.

2. Hold Behavior: This indicator reflects users' behavior in holding or selling their cryptocurrency. Analyzing this indicator can help analysts identify behavioral patterns and provide accurate price trend predictions.

3. Cryptocurrency Outlook: Combining insights from on-chain analysis with other methods such as technical and fundamental analysis helps create a comprehensive outlook on a cryptocurrency’s future. This outlook can include predictions on price trends and the optimal times to enter or exit the market.

Combining On-Chain Analysis with Other Tools

One important application of on-chain analysis is its combination with other methods like technical analysis. This combination assists investors and traders in determining appropriate entry and exit points for their digital assets. While technical analysis focuses more on price patterns and market trends, on-chain analysis examines real data and network activities. This combination can lead to more accurate predictions and reduce investment risks.

History of On-Chain Analysis Metrics

On-chain analysis, which involves examining and analyzing on-chain data from blockchain networks, has rapidly evolved over the past few years, becoming one of the key tools for cryptocurrency analysts. However, the roots of this type of analysis date back more than a decade.

The Beginning: 2011 and the Introduction of the CDD Metric

The first on-chain analysis metric was introduced in 2011. A user with the pseudonym ByteCoin on the Bitcoin Talk platform took the first step in this field. He introduced the Coin Days Destroyed (CDD) metric with the aim of measuring the health and level of participation in the Bitcoin market. This metric, which assesses the age of Bitcoins moved on a particular day, indicated the activity and level of engagement in the network. This concept is recognized as the first significant step towards creating on-chain analysis tools.

2014: The Creation of the Network Value Metric

In 2014, the second major on-chain analysis metric was introduced by a user named Gbianchi on the same platform. He introduced the Network Value metric, which was based on active addresses within the network, allowing analysts to evaluate the network's value from a different perspective. Later that year, Jon Ratcliff expanded on this concept by introducing the HODL Wave metric, which analyzed holder behavior and the duration of holding assets within the network.

2017: The Introduction of the NVT Model

The year 2017 marked a major breakthrough in on-chain analysis. Chris Burniske and Jack Tatar introduced the NVT (Network Value to Transactions) model. This model examined the ratio of network value to the transactions conducted within the network, enabling analysts to assess the functional value and utility of a cryptocurrency.

2018: Rapid Developments and Advancements

The year 2018 can be considered a period of major developments in on-chain analysis. Early in the year, Dmitry Kalichkin introduced a new model called NVM (Network Value to Metcalfe), which was calculated based on Metcalfe's law and contributed to more precise network analysis. Additionally, in this year, a new version of the HODL Wave was introduced by Dhruv Bansal, which offered a more detailed examination of holder behavior.

In the second half of 2018, Nic Carter and Antoine Le Calvez from Coin Metrics introduced a model called Realized Cap, which calculated the actual value of Bitcoins based on their last transfer time. Following this, David Puell and Murad Mahmudov introduced the MVRV metric, which measures the ratio of market value to realized value.

From 2018 to the Present: Growth and Increasing Complexity

Since 2018, on-chain analysis has rapidly developed, with numerous new metrics being introduced in this field. These metrics have enabled analysts and investors to make more accurate market predictions and better decisions.

On-Chain vs. Off-Chain Transactions

On-chain analysis is directly related to on-chain transactions. On-chain transactions are those that are recorded and confirmed on the blockchain, with all their details visible on the blockchain. These transactions are highly valued for their transparency and security.

Off-Chain Transactions, on the other hand, refer to transactions that occur outside the blockchain network and are not recorded on it. These transactions are faster and less costly, but due to their lack of registration on the blockchain, they offer less transparency and security, making them difficult to verify in the event of a dispute.

Tools Compatible with On-Chain Analysis

On-chain analysis involves examining blockchain data using various tools and platforms that help analysts extract valuable information from the activities and transactions within blockchain networks. Below are some of these tools:

Etherscan: A tool used for the Ethereum network, allowing users to view transaction details, smart contracts, and wallet addresses.

SnowTrace: A blockchain explorer for the Avalanche network that enables users to examine data within this network.

Specialized Analytical Platforms

These platforms collect, analyze, and present on-chain data in the form of reports and graphical dashboards for users.

Glassnode: One of the most well-known platforms for analyzing Bitcoin blockchain data and other cryptocurrencies. It provides diverse information such as whale movements, interest in futures markets, mining difficulty, and the realized market value.

IntoTheBlock: This platform uses machine learning algorithms to analyze on-chain data, including wallet inflows and outflows, network adoption, and transaction volume.

Nansen: An advanced tool for tracking "Smart Money." This platform tags over 100 million digital wallets, helping users track the inflows and outflows of large capital.

Dune Analytics: A platform for building and sharing analytical dashboards based on blockchain data. This tool allows for deeper data analysis through SQL coding.

Messari: A platform that provides comprehensive data on the cryptocurrency market and offers advanced tools for on-chain data analysis and comparing different networks.

Strategies Design Using On-Chain Analysis

On-chain analysis is a powerful tool for gathering and analyzing blockchain data, but the key point is that these analyses alone cannot tell you what investment decisions to make. Instead, you must design and execute an appropriate strategy based on this information. Here are some strategies for using on-chain analysis data:

Bitcoin Price Movements

Bitcoin (BTC), as the largest and most valuable cryptocurrency, plays a very important role in the cryptocurrency market. Bitcoin's price changes typically have a direct impact on other cryptocurrencies and can be used as an indicator to predict market movements.

Using tools like Glassnode, you can access a wealth of information, including whale movements (large investors), interest in futures markets, mining difficulty, and the realized market value. By analyzing this data, you can identify potential signs of a rise or fall in Bitcoin's price and use them in your investment decision-making.

Number of Active Wallet Addresses

Monitoring the number of active digital wallet addresses can provide insights into market activity and the overall health of the network. An increase in active addresses may indicate growing interest and participation, which could influence your investment strategy.

Monitoring Active Wallet Addresses

This indicator can show you how active a network is and how much it's being used. The number of active addresses reflects the usage level of a cryptocurrency, but it’s important to note that a single user can have multiple wallets.

Identifying Usage Trends: If the number of active addresses is continuously increasing, it may indicate network growth and rising demand for the associated cryptocurrency. This information can help you adjust your long-term strategies based on user growth and network activity.

Smart Contracts and Smart Money

"Smart Money" refers to large, intelligent capital movements by whales or investment funds within blockchain networks. Tracking these flows can provide valuable insights into the behavior of major investors.

Using the Nansen Tool: This tool allows you to track the inflows and outflows of Smart Money. By analyzing this data, you can gain a better understanding of market movements and the decisions of large investors, helping you to adjust your strategy accordingly.

Analyzing Non-Fungible Tokens (NFTs)

The NFT market requires its own specialized analysis due to its unique characteristics and focus on rarity. The price of an NFT is usually determined by its rarity.

Using Tools like Rarity.Tools and BlockProbe: These tools help you identify valuable and rare NFTs and determine the best times to buy or sell them. The information gathered from these tools can help you find the best investment opportunities in the NFT market.

Analyzing Buy and Sell Ranges with On-Chain Indicators

On-chain analysis is highly effective in assessing the short-term and mid-term performance of the cryptocurrency market. This method helps you examine the behavior of investors, miners, and exchanges, and use this information to make informed buying and selling decisions. Below are some key indicators and on-chain analysis models for evaluating buy and sell ranges:

Coin Days Destroyed (CDD) Indicator

The CDD indicator is one of the most important tools for assessing the length of time a cryptocurrency has been held in a wallet. This indicator reflects the behavior of long-term holders and can help you determine the right time to enter or exit the market.

Application in Analysis: An increase in the CDD indicator suggests that long-term holders are deciding to sell their assets, which can increase selling pressure in the market. If CDD is high, it indicates that the market may be in an overbought range and could signal a good time to sell.

Supply in Profit and Loss

This indicator shows the number of tokens that are in profit or loss. Analyzing this indicator can provide insights into market sentiment and the potential for price growth or decline.

Application in Analysis: If a high percentage of tokens are in profit, selling pressure may increase as holders decide to cash in their gains. Conversely, if most tokens are in loss, selling pressure may decrease as investors are less inclined to sell at a loss.

Realized Cap (Realized Value) Indicator

Realized Cap is a metric that calculates the total value of assets in circulation based on their last purchase price and compares it with the market value (Market Cap).

Application in Analysis: If Realized Cap is higher than the market value, this indicates overall market profitability. In such a situation, investors may be inclined to sell, as the market approaches its price ceiling.

Thermo Cap Model

Thermo Cap is a metric for evaluating the cumulative value of rewards paid to miners. This model can provide insights into the fundamental valuation of Bitcoin and miners' incentives to continue mining.

Application in Analysis: If Thermo Cap significantly increases, this indicates heavy investments by miners and could be considered a sign of potential price growth.

Analysis Based on UTXO and Account Models

UTXO-Based Analysis

UTXO (Unspent Transaction Output) is one of the most important concepts in the Bitcoin network, tracking unspent transactions. UTXO analysis helps you examine the spending and holding patterns of Bitcoin.

 

Application in Analysis: By analyzing UTXO patterns, you can identify the behavior of long-term and short-term Bitcoin holders. If older UTXOs start being spent, it could signal widespread selling in the market.

Account-Based Analysis

This method is more applicable to networks like Ethereum that use the account model. Account analysis includes examining transaction counts, account balances, and wallet inflows and outflows.

Application in Analysis: Analyzing account balances and wallet inflows and outflows can help you understand the behavior of traders and large investors and identify the right times for buying or selling

Limitations and Drawbacks of On-Chain Analysis

On-chain analysis is a powerful tool for understanding the behavior and health of blockchain networks, but like any analytical method, it has its limitations and drawbacks. Below are some of the most significant ones:

Short Lifespan of the Cryptocurrency Market

Cryptocurrencies have existed for just over a decade, and this short timeframe makes historical analyses less reliable. Many of the patterns and behaviors observed in on-chain data may change or disappear entirely in the future. Therefore, relying on past data in on-chain analysis can lead to incorrect conclusions.

Limited Usefulness for Short-Term Timeframes

On-chain analysis is more suited for examining long-term trends and analyzing the overall market structure. This type of analysis is generally less applicable for traders who operate in short-term timeframes, such as day trading. On-chain data, due to its nature, is updated with a delay and is not suitable for predicting short-term market fluctuations.

Complexity and Need for Specialized Knowledge

On-chain analysis requires technical knowledge and familiarity with blockchain and cryptocurrency concepts. Traders and analysts who lack sufficient understanding of these concepts may struggle to interpret on-chain data. Additionally, the tools and platforms used for this type of analysis are often complex and require advanced analytical skills.

Limitations in Access to Accurate Data

Some networks and protocols do not provide users with complete and transparent data. Additionally, off-chain transactions or those conducted through second-layer solutions are not directly visible in on-chain data. These limitations can reduce the accuracy of on-chain analyses.

Impact of External Events

External events, such as changes in government regulations, major news, and widespread adoption or rejection by users, can have significant impacts on the market that may not be clearly reflected in on-chain data. This type of analysis alone cannot cover all aspects of the market and may fail to predict sudden changes.

Conclusion

The history of on-chain analysis indicators shows that this field is rapidly growing and evolving. From the introduction of the first indicators in 2011 to the development of more complex models in recent years, on-chain analysis has become one of the essential tools for cryptocurrency analysts and investors. Given recent developments and the continuous creation of new indicators, these tools are helping to provide more accurate analysis and better decision-making in cryptocurrency markets.

On-chain analysis allows analysts to better understand user behavior and market trends. However, like any other analytical method, it requires knowledge and experience and cannot be used alone to predict prices. Combining this method with other forms of analysis can help achieve more accurate predictions.