What is On Chain Analysis and Why Should Crypto Traders Use It?

September 14, 2023



Research Team

Table of contents

    On-Chain Analysis 101


    On chain analysis refers to the examination & use of blockchain data, for purposes ranging from trading, to research, to media investigations & reporting. Because the blockchain is a public & unchangeable ledger, it hosts data like wallet addresses, transaction amounts, contract addresses, timestamps, and metadata. On chain analysis transforms this raw blockchain data into useful insights, for traders & researchers to understand different topics e.g. the amounts of cryptocurrency held by specific persons, the sources & destinations of fund movements, as well as data on an entire blockchain ecosystem’s activity. Simply put, it can help traders make decisions with deeper insights, through providing them with a powerful source of economic data to inform their decision making.

    In this article, we’ll look at the different ways to do on chain analysis, and show you how Arkham can help make your analysis significantly more efficient than trying to make sense of blockchain data yourself.


    • There are many different ways to do on chain analysis. All are built upon looking at wallet holdings & examining transactions between wallets.
    • More advanced analysis looks at specific token metrics, token flows to exchanges, blockchain ecosystem activity & other aggregated data.
    • Technical analysis uses charts & patterns to predict future trends. On chain analysis is different - and uses actual blockchain data to understand the market. These are 2 completely different data sources.
    • Traders can use this to help inform their decisions, through understanding the actual movement of tokens across blockchains - and using this data to make better decisions.


    There’s no one fixed method of on chain analysis, but rather multiple approaches to looking at different sources of data, which can help a trader decide where & when to make a trade. We’ll look at the most commonly used methods, to help you familiarize yourself with the different types of data stored by blockchains & learn how they’re useful to analysts.


    While data on how much money someone has is private by default for a person’s bank account or physical wallet, the amount of a specific token held by a wallet address is publicly recorded data on a blockchain. Given this, we can actually see a wallet’s current and historical holdings of various tokens. This is one of the building blocks of on chain analysis - seeing who holds what token & how much of it they hold.

    As wallets may be used by people, funds, exchanges, and even governments, the ability to see the current and historical holdings of any wallet means we can actually see how much of a token any of these people or organizations hold and held in the past.

    While blockchain addresses are pseudonymous by default, commonly in the form of addresses like: 0xB63AaE6C343636d66Df13b89Ba4425cfE13d10bA - Arkham deanonymizes the blockchain using artificial intelligence and other proprietary methods, linking wallet addresses to actual people & organizations. This allows you to see who the likely owner of a particular address is and how much of a particular token they presently hold or held in the past.

    With on-chain wallet data at your fingertips, you can fact-check statements and claims made on social media or in public announcements. For instance, is a certain influencer bullish on a project - or just being paid for advertising? Likewise, is a venture capital firm a long-term protocol holder - or just selling off their tokens? Wallet data allows you to perform your own due diligence. Don’t simply trust - verify their actual holdings.

    As an example, you can see the up to date holdings of what is likely Donald Trump’s wallet, first identified by Arkham, in the screenshot below and use the Portfolio Archive feature on Arkham to look at his holdings at a particular date in the past:




    In addition to tokens held by an address, blockchains record the flow of funds between different addresses, meaning they store details on the actual transactions between 2 or more wallets on-chain. Each transaction on a blockchain has a unique ‘hash’, which stores data about that transaction, from the sender, to the recipient, to the timestamp and the amount(s) sent. This is another fundamental building block of on chain analysis - seeing where and when money moves.

    Transaction analysis lets on chain analysts identify patterns of buying or selling. As this data propagates to the blockchain in real time, one can be notified of a transaction taking place the moment it happens. Some uses cases for this might be:

    • Tracking a successful trader’s buys or sells, to copy-trade them
    • Monitoring a wallet linked to a hacker to see if they’re transferring funds to another wallet

    The entire record of past transactions on-chain is also available. Arkham’s entity pages show you lists of that particular entity’s transactions, both as they happen & historically - so you can see every transaction they’re associated with. Let’s look at a different example this time - the VC firm Andreessen Horowitz (a16z).

    a16z are prominent investors in MakerDAO, with large holdings of the token MKR. Here you can see some of their largest recent transactions, which some speculated to be sales of MKR:


    Towards the end of July 2023, a16z moved over $10M of their MKR tokens to Coinbase. This marked a local top in the MKR price, which fell by 12.5% in the following week. On chain analysts who saw this movement from a16z’s wallets early may have been able to profit by taking a short position out against MKR.


    Now that we’ve looked at the fundamental building blocks of on-chain analysis - namely portfolio holdings & transaction analysis, let’s build upon our analysis to look at the ways in which the combined knowledge of someone’s portfolio & transaction activity might be useful. This combination of examining holdings & transactions serves as the bedrock upon which all on chain analysis is built.


    Given the ability to see the contents of every wallet’s portfolio, on chain analysis enables us to see who the largest holders of a specific token are. While manually searching through wallets to find this information might be challenging & time consuming, Arkham & other block explorers automatically query blockchain data on users’ behalf - and sort the output in an easily readable manner, for users to see the top holders of any specific token in a list.

    Here’s an example of the top holding wallets for a specific token - in this case, we’ve used Bitcoin:


    Additionally, Arkham links wallets owned by the same person or organization & groups them into entities. We can list the top holders of a specific token by entity, to see the largest holders of Bitcoin organized by person/institution, rather than by largest individual wallet:


    Monitoring large token holders may be useful for traders to track. Large holders of tokens are more susceptible to affecting token price movements than smaller holders of a token. Their large buy/sell transactions can put more pressure on a token’s price in either direction relative to smaller holders, & their actions may affect trading volume or sentiment around a token among other traders.

    Additionally, knowledge of token holdings & the distribution of a particular token can signal to investors whether a token is too concentrated among insider wallets. And if a large number of the top holders of a specific token are competing funds, this might be a signal to traders that their competitor sentiment around this token is positive, or ‘bullish’.


    Exchange flows refer to the movement of funds between wallets owned by non-exchange users and wallets belonging to exchanges. On chain analysis lets us observe the net amounts of funds flowing to a particular exchange - analysts typically use this data to examine exchange flows on larger timescales or for specific tokens.

    Typically, an inflow of tokens to exchanges is considered to be a negative or ‘bearish’ event, as it often indicates tokens being deposited to exchange wallets for the purpose of selling. Meanwhile, an outflow of tokens from exchanges to wallets is characterized as a positive or ‘bullish’ event as it indicates an intent to hold the tokens for a longer period, as a user is removing them from the place where tokens are typically bought or sold.

    On Arkham, you can see exchange flows for any token - here are the flows for USD Coin (USDC) from the past year. Red refers to deposits to an exchange - green represents withdrawals:


    Over 2022 and 2023, large quantities of USDC were transferred to exchanges. This was because many companies and people redeemed funds for real-world USD, taking their capital out of the crypto ecosystem. Tracking exchange flows like this can show traders when this bearish trend halts or reverses, and may even indicate when money begins to move back into the ecosystem.

    You can also see a specific user’s exchange usage through their entity or wallet page - here’s an example for the quantitative trading firm Jane Street:



    Whales are large holders of a particular cryptocurrency - or more generally, any user with a large account size. There’s no set number denoting how much money a wallet, person or organization needs to have to be denoted as a whale. A holder of a large USD amount of Token A might be considered a whale in the context of Token A - and may also hold a large amount of Token B, but not be considered a whale in reference to Token B as there may be many, many more larger holders of Token B than them.

    This Token A whale might also have a large amount of Token A, but not a large overall portfolio size, meaning that they might not be considered a whale in regards to their entire account. In either case, on chain analysis lets us see their entire portfolio holdings, to make this judgment for ourselves.

    The on-chain movements of whales are notable, as they can move markets or shift sentiments, as indicated above in the ‘Top Holders’ section. Retail traders frequently track and copy whale wallets, with the presumption that whales possess superior or insider knowledge of market dynamics, which a retail trader can potentially benefit from copying directly. 

    In this section however, we deal specifically with setting alerts for whale transactions. This is a popular method used by on-chain traders to be notified when whales make certain transactions. 

    Arkham Alerts, for example, allow the user to be notified by email, Telegram or through Webhooks to a service of their choice, when any transaction type the user wishes to monitor, takes place. EtherDrops is another example & sends custom alerts to users over Telegram.



    Users of blockchains are no longer limited to using only Bitcoin or Ethereum - with the existence of a range of Ethereum Virtual Machine (EVM) compatible blockchains, Layer 2 scaling solutions & alternative Layer-1 blockchains, market participants have the option to use and transfer value across an assortment of blockchains. Bridges allow users to move tokens across blockchains - Stargate Finance is among the most popular of these, & both transaction frequency & volume on Stargate have grown considerably since March 2023, as seen in the graphs below - showing the level of enthusiasm with which blockchain users have embraced cross-chain activity:



    By monitoring movements of tokens within & between these different blockchains, on-chain analysts can build a complete picture of a specific user’s blockchain activity - and in the process of doing so, not only learn about the user’s preferences for different blockchains, but learn about emerging projects, like bridges facilitating the transfer of value across chain - or DeFi protocols which seek to provide enhanced yield to early adopters of an emerging blockchain ecosystem.


    Technical analysis involves using price charts, patterns, and indicators to predict future price movements. It relies on historical price data, trading volume, and various technical indicators to identify patterns and trends in market behavior. Many technical analysts will share charts of their analysis on platforms like Twitter, with their commentary on whether they think the market will go up or down. Technical analysts spend a large amount of time analyzing charts like this:


    A more accurate term for technical analysis might be price chart analysis. Unlike on chain analysis, technical analysis does not employ actual blockchain data.

    An additional type of analysis that is commonly used to understand both cryptocurrency markets, as well as traditional markets, is fundamental analysis. Fundamental analysis can be categorized as either quantitative or qualitative. Quantitative factors often refer to company-related data, like cash flow, revenue, and net income while qualitative refers to factors like the management’s background, brand-name recognition, and competitive advantage.


    In the previous sections, we looked at specific metrics & perspectives which on chain analysis makes use of, to inform trading, research & other activities. Continuing from these fundamental ‘building blocks’ of on chain data, let’s look at how analysts might use this to examine ecosystem level, or macroeconomic data using on-chain indicators.

    Macro on chain data provides a larger overview of the collective behavior of market participants over longer time frames. This usually involves analyzing the usage and adoption of blockchains or DeFi protocols and assessing their growth and user engagement.

    Some of the metrics which macro on-chain analysis focuses on are listed below, with a brief explanation of each one:

    • Number of Active Addresses: The number of wallet addresses that have been involved in transactions within a certain timeframe - indicative of network adoption and usage trends.
    • Daily Transactions: This refers to the total number of transfers or operations conducted on a blockchain network each day - this can allow traders to spot breakout trends in the popularity of a chain & could help them determine whether they’re ahead of the curve in finding opportunities.
    • Total Transaction Volume: The cumulative value of all transactions processed within a specific time period, typically measured in a USD equivalent value. Like ‘Daily Transactions’, but for a custom timeframe/all-time. 
    • Total Value Locked (TVL): The total amount of assets locked or staked in decentralized finance (DeFi) protocols - useful for evaluating how popular a protocol is/is becoming over time.
    • Number of Unique Token Holders: The number of unique individuals or addresses holding a particular token.

    All of the above data require knowledge of, or use of platforms that make sense of on chain data & cannot be gleaned from off-chain sources.


    Using everything we’ve learned so far, let’s look at some case studies for on chain analysis - beginning with the Bitcoin blockchain:

    1. Whale Movements

    We’re going to start with the analysis of a Bitcoin whale, to show you some things to look out for when looking at whale activity.

    We’ll look at this address:


    On 24th April 2023, this address moved funds for the first time after being inactive for over 10 years. They sent 400 Bitcoin out of their account, which eventually moved to different exchanges and payment services, such as Binance and Coinspaid.


    The wallet originally had 1,000 Bitcoin, all of which it acquired in May 2011. Bitcoin’s price at this time was approximately $5-10. By the time the Bitcoin was sent out of the wallet, the 400 Bitcoin it sent was worth over $10 million.

    There is often a small lag time between the transfer from an old account and the actual sale of the contents. Traders who are alerted about transactions like this might be able to predict a downward trend in price - as this is typically what happens when a large amount of tokens are sold. Essentially, traders can potentially make a trade using special knowledge of the fact that Bitcoin is about to experience selling pressure, before others become aware of this fact.

    1. Long Term Holders

    Now that we’ve looked at a specific transaction, let’s take a broader view & look at some market level data. One method of discerning market sentiment relies on grouping Bitcoin’s holders into long term or short term holders, & seeing which ones predominate.

    Traders take a date at which Bitcoin held by an address was last moved, and measure those that have or haven’t moved their Bitcoin since this point - corresponding to short term and long term holders respectively. Knowledge of the ratio between the two can guide traders on the current state of market sentiment - and whether people believe Bitcoin is a solid long term hold, or something to be speculated on & sold in a rising tide.

    Additionally, traders who track multiple whale accounts can apply the same long term holder analysis to large Bitcoin accounts only, and learn about what actions the biggest traders are taking. Understanding whether they are biased toward taking profits, or accumulating more Bitcoin, can help traders in their own decision making, as they seek to emulate the actions of successful traders.


    Next, we’ll look at the Ethereum blockchain for 2 further case studies:

    1. Entity Analysis

    Specific wallets sometimes have outsized influence on the opinions of traders. For example, the Ethereum Foundation has garnered a reputation for selling the top of the market.

    They sent ETH to Centralized Exchanges 3 times in total during 2021. 2 of these sales - 35,053 ETH in May, and 20,000 ETH in November - marked a local top in the price of ETH.


    Subsequent movements from the Ethereum Foundation’s wallet often precede a speculative sell-off from traders, as happened in May 2023. When the Ethereum Foundation moved $30M of ETH to exchanges on May 7th, the asset fell almost 5% on the day.

    Traders can only learn about moves like this by tracking the Ethereum Foundation’s wallets on-chain.

    1. Exchange Flows

    Analyzing fund movements to and from exchange wallets can help traders to determine whether traders are bullish or bearish on a given day. Large crypto flows out of exchange addresses generally suggest individuals are moving their assets to long term holding addresses (bullish), while large flows towards exchanges may indicate entities moving to sell (bearish).

    However, you need to consider context when analyzing any on-chain fund movements. For example, large amounts of USDC moving to an exchange like Binance or Coinbase in 2021 may have represented a trading firm moving capital to purchase crypto. However, over 2022 or 2023, stablecoins moving to exchanges may have represented an entity or person attempting to swap the stablecoins to the US Dollar - and reduce their overall crypto holdings.


    Above, we’ve covered on-chain analysis as it applies to the examination of other users’ portfolios, activities, as well as broader market dynamics. Traders however, can also use on-chain analysis to track their own portfolio & performance by aggregating their various wallets into one place. 

    This allows them to:

    1. Monitor personal portfolio performance
    2. Track the location of personal funds

    Crypto users frequently report forgetting about or misplacing wallets - tracking all of one’s wallets in one place can help prevent this from happening.


    Visualizing on chain data can help traders draw connections between different entities & understand transaction flows more intuitively, as compared with traditional data tables & logs. This is especially useful for traders who might not have expertise in data analysis or data science methodologies - as well as researchers trying to, for example, follow the movement of stolen money as it hops between different wallets.

    Bubblemaps is a useful tool for understanding the proportional ownership of a specific token, with respect to all of the other token holders. Traders can clearly see how concentrated a token’s ownership might be & whether this presents any future risks to a token’s price action, which might not be immediately obvious from a technical chart alone.

    Additionally, Arkham’s visualizer can help users see connections between different deanonymized entities, so that traders can understand who their competitors’ counterparties are & monitor their activities in real-time. 



    There’s a number of options for a trader looking to start using on chain analysis in their research process. We’ve compiled a list of some useful tools below - we recommend trying all of them, as different tools typically have different strengths, and often complement one another: 

    Arkham: We built Arkham to give traders & researchers a way to understand the people and organizations behind crypto market activity. You can make use of Arkham’s wide feature set to look at entities’ portfolios, visualize their activity, receive real-time alerts on their activity & build custom dashboards to see data which you wish to see. Alongside this, you can use Arkham’s other unique features, like the Intel Exchange - to buy & sell on-chain data on wallet addresses, or the Oracle - an AI assistant for on-chain research

    Etherscan: Etherscan is a widely used legacy block explorer, which provides lists of transactions for users to parse through & make sense of. It’s a popular tool for users to understand transaction level data in granular detail.

    Glassnode: Glassnode is a powerful tool for looking at broader market data, through a range of curated charts, dashboards and ‘workbenches’ - allowing users to understand the calculations behind some of their more cutting edge metrics. It provides helpful data on major assets like Bitcoin & Ethereum - and their platform is popular among institutional clients.

    Icy Tools: Icy Tools is a specialist NFT tracking & analytics tool, which uses on-chain data to help NFT traders understand critical metrics for this asset class, from floor prices, to volume, to sales history. Traders can use this tool to find trending collections, newly launching NFT collections, and customize feeds, charts, watchlists & alerts on their platform. 

    Token Terminal: Token Terminal is a useful tool for users looking for more aggregate metrics & big picture market analysis. Their dashboards collate many of the Market Level Data Metrics we spoke about above, alongside other useful data for traders & researchers e.g. Looking at fees paid on each blockchain - as well as the top projects categorized by type e.g. Gaming, Infrastructure, Lending, & much more.


    Alongside the fundamental analysis & technical analysis typically used by traders, on-chain analysis provides a powerful 3rd way of examining market data, which traders can use to strengthen their research & analysis. Arkham helps traders do exactly this.

    Information provided herein is for general educational purposes only and is not intended to constitute investment or other advice on financial products. Such information is not, and should not be read as, an offer or recommendation to buy or sell or a solicitation of an offer or recommendation to buy or sell any particular digital asset or to use any particular investment strategy. Arkham makes no representations as to the accuracy, completeness, timeliness, suitability, or validity of any information on this website and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. Digital assets, including stablecoins and NFTs, are subject to market volatility, involve a high degree of risk, can lose value, and can even become worthless; additionally, digital assets are not covered by insurance against potential losses and are not subject to FDIC or SIPC protections. Historical returns are not indicative of future returns.