This study is designed to aid in the determination of whether an exchange, index provider, investment manager, or any market participant should support a new fork or credit holders of the parent chain with units of the forked asset. It was conducted with particular focus on the several months immediately after the fork event. 


Deciding on which forks to support is an independent decision that each market participant must make. Although there are over 100 known forks of Bitcoin, only a small number have achieved meaningful market valuations. For the purposes of this study, three forks are examined: Bitcoin Cash (BCH), Bitcoin SV (BSV), and Bitcoin Gold (BTG). Coin Metrics’ coverage of network data and market data is complete for these three assets. 

Comparing forks that may occur in the future with the baseline performance established by these three forks allows an objective method for determining whether to support the fork. Although Bitcoin SV forked from the Bitcoin Cash parent chain, it is still in competition with Bitcoin for mindshare and status among the community. Thus, Bitcoin SV data is still compared to Bitcoin’s data in the analysis below.

The following analysis examines the legitimacy of forked assets along two dimensions: market data metrics and network data metrics. Market data metrics are defined as metrics derived from off-chain transactions in the form of trades that occur on major exchanges. Network data metrics are defined as metrics derived from on-chain transactions that can be observed by running a full node. 

Since forked assets have the incentive to give the impression of elevated activity, particularly in the moments immediately after the fork event, focus was given to metrics that are resistant to manipulation. Focus was also given to the state of the forked asset up to the 50th day after the fork event ‘ a short enough time window for an operator to make a timely decision but also long enough for some limited market and network data to accumulate.

Measuring Legitimacy Through Market Data

Fork legitimacy is examined along three market data metrics: exchange support, price, and volume.

Exchange Support

The degree of exchange support is an important determinant in a fork’s success. At the time of the fork event, each exchange must independently evaluate the legitimacy of a fork and decide whether to add new markets where the forked asset can be traded and whether to credit holders of the parent chain with the forked asset. Although few exchanges have publicly disclosed their criteria for deciding whether to support a fork (see Further Reading section), their collective actions can be examined as a measure of overall support among market participants. The decision of large exchanges can be particularly impactful. The direction of causality can be circular in that an asset’s degree of acceptance among market participants partially determines whether an exchange will support the asset, and the action of exchanges also determines an asset’s degree of acceptance among market participants.

At the moment immediately after the fork event, there are few exchanges that list the forked asset, but a handful of exchanges can telegraph their support of an upcoming fork by listing pre-fork futures markets. For the three forks in this study, in each case fewer than five exchanges supported the asset at the point of network inception. Bitcoin Cash and Bitcoin SV swiftly and consistently achieved greater support from exchanges over the subsequent months. Bitcoin Gold is an example of a fork where support among exchanges has stagnated. Historical data indicates that if a fork manages to achieve support from at least 8 major exchanges by the 50th day post-fork, it is likely to continue to achieve greater acceptance from additional exchanges.

Coin Metrics’ market data consists of data from 25 exchanges which in our determination are the major exchanges that most trading activity takes place on. For most exchanges, Coin Metrics has every trade since inception of the exchange, but a handful of exchanges do not allow users to query historical trade data. For these exchanges, the market data begins at the time that Coin Metrics began collecting it. Therefore, the numbers below should be seen as a conservative lower bound.


Cryptocurrency market microstructure is still in the process of maturing. Price anomalies, order book quote stuffing, price manipulation, large spreads between markets, and flash crashes can still regularly be observed. Despite these incidents of disorderly markets, the price and market capitalization of an asset are still an important indicator of fork acceptance by market participants (under the assumption that markets are still semi-efficient).

Since forks can happen during various market regimes and the size of cryptocurrency assets continue to grow, the price of forks as a percent of Bitcoin’s price is examined. Price is calculated using Coin Metrics’ Reference Rates which calculates an independent and accurate price using a robust methodology that is resistant to manipulation. The Reference Rates use a market whitelisting approach in which markets are scored using a systematic framework and only the highest scoring markets are selected to serve as sources of input data. This is particularly important in the early stages of a new asset where large spreads between exchanges can be observed.

The historical data shows that the three forks in the study can debut at varying prices and that a volatile period of price discovery follows.     Significant movements can occur after the 50th day post-fork. Moreover, Bitcoin Gold, an asset that has achieved less long-term acceptance than Bitcoin SV, nevertheless outperformed Bitcoin SV early in its history. Liquidity is sparse early on in a forked asset’s existence. Since price discovery for forked assets can take a long period of time, a fork’s price performance should be examined with caution. Price should instead be examined in the broader context of the other metrics presented in this study.


Among the six metrics presented in this study, volume is the most susceptible to manipulation. Recent research from Bitwise and others have presented strong empirical evidence that widespread wash trading exists. Therefore, extreme caution should be used in using volume to evaluate fork legitimacy. In addition to the systematic presence of wash trading on certain exchanges, supporters of a new fork are especially incentivized to artificially generate market activity early on in a fork’s existence.

An examination of Bitcoin Cash’s volume immediately after the fork event illustrates the danger of using aggregate volume figures. On an aggregate basis, Bitcoin Cash experienced extremely high trading activity early in its existence but trading was highly concentrated on Bithumb, a large Korean exchange where certain market participants made a concerted effort to increase prices. At its peak, 2.4 million Bitcoin Cash was traded on Bithumb during a single day. Volume analysis is more helpful when analyzing the distribution of volume across exchanges and examining whether reputable exchanges have economically meaningful volume figures. 

Despite the questionable activity on Bithumb, Bitcoin Cash managed to secure the support of Poloniex and Kraken by the 50th day post-fork ‘ two exchanges with markets that score highly on Coin Metrics’ Market Selection Framework, a systematic quality scoring framework. This momentum was enough to compel Bitstamp and Coinbase to list the asset several months later.

Bitcoin SV presents a more healthy distribution of volume split across major exchanges roughly in proportion to each exchange’s global market share. Bitcoin SV was able to secure the support of major reputable exchanges very early, including Binance, Poloniex, and Kraken. However, most recently, some major exchanges such as Binance and Kraken have begun delisting Bitcoin SV.

Bitcoin Gold has also experienced highly concentrated trading on Bithumb. At the 50th day post-fork and up to the present, Bitcoin Gold has not been able to secure the support of any major exchange based in the United States or Europe. However, Binance decided to support the asset and volume on Binance steadily grew during the asset’s first 200 days of existence.

Measuring Legitimacy Through Network Data

Similar to volume figures on exchanges, certain network data metrics are susceptible to manipulation. Due to the nature of previous Bitcoin forks where block space is not scarce, many metrics related to active addresses, transaction count, and transaction value can be gamed. Therefore, particular care was given to choosing network data metrics that are economically meaningful, measure genuine use or acceptance among network participants, while remaining resistant to the actions of a small group of committed actors that may be incentivized to artificially generate network activity.

In this section, fork legitimacy is examined along two network data metrics: fork uptake and hash rate market share.

Fork Uptake

In this section, we introduce a new metric that measures ‘fork uptake’. This is a metric that begins at zero at the start of the fork event and is uniquely resistant to manipulation. It then measures the running total of the number of native units that have been activated, where activated is defined as being sent to an address post a fork event. The intuition here is an attempt to measure how many native units of the forked asset are claimed by owners. 

Over time, as Bitcoin mining rewards are distributed widely to different miners and existing long-term holders slowly sell their holdings, Bitcoin has decisively trended towards reducing the concentration of ownership. The top 100 Bitcoin addresses by size consist of only 20 percent of current supply, a figure that is significantly lower than other assets. An alternative measure of the degree of concentration of ownership is to examine the number of addresses that own at least some minimum amount of native units.

As an illustration, the number of Bitcoin addresses with a balance greater than 0.01 native units is examined. The 0.01 native unit threshold, while arbitrary, represents a value that is large enough to exclude accounts with miniscule dust balances while also small enough for the value to be economically meaningful for most people in the world. Such a threshold represents approximately $10 U.S. Dollars at current prices. The latest day indicates that there are 7.5 million such balances and growing steadily. This is one estimate of the number of economically meaningful owners of Bitcoin, although the true number of owners is unknown because the address-to-person relationship can be many-to-one or one-to-many.

Since any Bitcoin fork must adopt the UTXO set of the parent chain, the diluted nature of Bitcoin ownership is inherited by all current Bitcoin forks and all subsequent forks. Importantly, this property cannot be changed by a small group of committed actors.

For many forks that fade into obscurity, fork uptake remains near zero because no owners have claimed the fork asset. For example, if an individual holds Bitcoin in a wallet that the individual controls during a fork event, then subsequently transfers the forked asset to an exchange to sell, those native units are included in this figure.

Due to the diluted nature of Bitcoin ownership, this metric represents a gold standard for measuring adoption and use by the community, and is relatively resistant to manipulation. A small group of committed actors cannot force owners to claim their forked asset. On the 50th day after the fork event, nearly 4.5 million native units of Bitcoin Cash and Bitcoin SV had been claimed. Bitcoin Gold lagged behind with only 2.5 million native units claimed. In contrast to some of the noisy metrics introduced in this study like price and volume, this fork uptake metric is quite smooth and predictable. After only 50 days or perhaps even sooner, an operator should have a good idea of the future success or failure of a fork.

A related measure is the number of addresses with a balance after a fork event. Similar to address count metric introduced in the beginning of this section, this measure is an estimate of the number of owners of the forked asset, subject to the same caveats discussed earlier. On the 50th day after the fork event, both Bitcoin Cash and Bitcoin SV had roughly 200,000 addresses. This almost certainly undercounts the number of owners, however, because many owners tend to consolidate their holdings of the forked asset or send their assets to omnibus exchange wallets to sell. Nevertheless, the shape of the curve and establishing a baseline that future forks can be compared to  can be useful.

Hash Rate

Hash rate also represents a metric that is relatively resistant to manipulation because mining equipment is a scarce asset that incurs high variable costs in the form of electricity. Like ownership, miner market share is widely distributed, although perhaps less so than because most miners assemble into a small number of large pools. Bitmain has an outsized impact as the primary manufacturer of most Bitcoin mining equipment and have shown willingness to use their influence to support Bitcoin Cash in the past. Regardless, an examination of mining market share is also an important metric to examine because it reflects the consensus of miners, an important stakeholder in the ecosystem and a powerful arbiter in a forked asset’s fate.

The hash rate of the forked asset as a percentage of Bitcoin’s hash rate is shown below. For this metric, only Bitcoin Cash and Bitcoin SV are able to be examined because all three share the SHA-256 hash algorithm. Bitcoin Gold hard forked to use the Equihash hash algorithm, an algorithm designed to be resistant to ASICs, so the hash rate cannot be directly compared to Bitcoin’s.

The amount of mining directed to a particular chain is, among other things, a function of profitability. Since prices were so volatile early on in the forked assets’ lives (especially Bitcoin Cash), the hash rate is similarly volatile. Interestingly, at the 50th day after the fork event, Bitcoin Cash had a hash rate market share of roughly 15 percent while Bitcoin SV had less than 3 percent.


When faced with a fork event, operators must make a timely decision whether to support the asset or not in the face of incomplete information. In this study, Bitcoin Cash, Bitcoin SV, and Bitcoin Gold were examined, giving particular focus to the 50th day after the fork event to simulate the situation in which an operator must make a timely decision. If an operator is faced with a fork event in the future, the performance of the forked asset immediately after the fork event can be compared to the baseline performance established by these three significant forks.

Five metrics were presented to evaluate fork legitimacy:

  1. Exchange support, defined as the number of exchanges that have listed the asset, a powerful determinant of future fork success

  2. Price, representing the collective degree of acceptance among market participants under the theory of semi-efficient markets

  3. Exchange volume, a potentially manipulatable metric, but still useful in seeing how volume is distributed and which exchanges have significant volume

  4. Fork uptake, a network metric that is resistant to manipulation and is the gold standard for measuring fork adoption among owners of the parent asset

  5. Hash rate, representing the collective degree of acceptance among miners, an important stakeholder in the ecosystem

Further Reading

Coin Metrics has extensively examined Bitcoin and its forks using additional network data metrics. For a more complete study of Bitcoin forks, please reference Evaluating Bitcoin forks with network data and A Comparative Analysis of Bitcoin Forks.

A handful of operators have publicly disclosed their policy for handling forks. These include Ethfinex, Bittrex, ErisX, and Bitwise

An Analysis of Kin’s On-Chain Activity an-analysis-of-kins-on-chain-activity 2019-06-24 15:06:06

In the following post, we investigate Kin’s on-chain activity compared to other blockchains.

The SEC has officially filed a lawsuit against Kik, the parent company of the Kin token, accusing them of selling unregistered securities. Kik has vowed to fight the suit, and recently launched a crowdfunding campaign to fund the effort.

As part of their response to the SEC, Kik made several claims about the usage of their blockchain, two of which are of particular note:

Claim 1: Activity

Consistent with Kik’s stated vision, Kin has been adopted, integrated, and used within over 30 digital applications. Excluding secondary market transactions, as of today, Kin exceeds Ether and Bitcoin in daily blockchain activity, demonstrating Kin’s wide acceptance and adoption. (See Indeed, of the over 2,000 tokens in circulation, Kin is ranked as having the fifth highest daily blockchain activity.

    – Kik’s Response to the SEC Wells Notice

Claim 2: Users

Despite the fact that last month over 300,000 people earned and spent Kin as a currency, the SEC is still saying that it might be a security.

Kik Responds To the SEC Complaint

Although the case is primarily about whether or not Kin’s Token Distribution Event should be considered an unregistered sale of a security, Kik’s response brings up another important question: how do we measure real blockchain activity and usage? And can Kin’s ledger, the ultimate source of truth for any blockchain, verify the claims Kik has made about Kin’s blockchain activity?


In the following post, we investigate both of Kik’s claims about activity and usage by auditing the Kin Blockchain.

Kin has gone through several infrastructure changes over the past few years. Kin was first launched as an ERC20 token built on the Ethereum blockchain (Kin 1). It then moved to a two-chain hybrid solution built on a fork of Stellar, that still supported the Ethereum blockchain (Kin 2). Kin 2 is a centralized version of the Kin blockchain that was designed to be a temporary solution before moving to a self-described decentralized blockchain, Kin 3. Kin is now in the process of migrating to Kin 3, which is also forked from the Stellar protocol.  

In order to analyze Kik’s claims about on-chain operations, we assessed on-chain data from both the Kin 2 and Kin 3 version of the ledger. Kin 1 (ERC20) is basically disused at this point (it currently has less than 500 daily transactions) as most tokens have been migrated over to Kin 2 or Kin 3, so we omitted it from our analysis.

Claim #1: Assessing Blockchain Activity

Consistent with Kik’s stated vision, Kin has been adopted, integrated, and used within over 30 digital applications. Excluding secondary market transactions, as of today, Kin exceeds Ether and Bitcoin in daily blockchain activity, demonstrating Kin’s wide acceptance and adoption. (See Indeed, of the over 2,000 tokens in circulation, Kin is ranked as having the fifth highest daily blockchain activity.

    – Kik’s Response to the SEC Wells Notice

As it stands today, there are well-defined and accepted metrics for estimating usage and activity of traditional applications. Daily active users (DAU), for example, is a widely used and agreed-upon metric. But given their relative infancy, blockchains do not share this level of standardization. Even seemingly simple questions like ‘what counts as a blockchain user?’ and ‘what counts as activity?’ are still up for debate.

In the following section, we investigate Claim #1 according to two different criteria:

Operations Count: Firstly, we examine if Kin is a leader in blockchain activity as measured by operations count, which is the metric that Kik used as evidence for their claim.

Transfer Value: Next we investigate how Kin compares in a different measure of activity: transfer value. We define transfer value as the USD value of all native units transferred (i.e., the aggregate size in USD of all transfers) during that day.

Using Operations Count To Assess Claim #1

According to Kik’s source for the metric, ‘blockchain activity’ is defined as ‘the number of operations on the blockchain in the last 24 hours.’ Operations are broadly defined as any type of action that could be recorded on chain. But operations are not standardized across blockchains which makes comparing across chains difficult.

Additionally, different blockchains have different use cases. Kin is designed primarily to be used within the Kik messaging app to buy and sell digital content (e.g., stickers) and send payments directly to other users. Other blockchains, however, are designed for radically different purposes, which can make it difficult to compare operations across different platforms.

There are two distinct types of operations that happen on the Kin blockchain: payments and account creations. Payments are simply transfers of value (i.e. movement of Kin tokens) between two distinct addresses. Account creation operations on Kin create a local key pair and record the account creation on the Kin blockchain. On Kin 3, it is also possible to transfer Kin to an account while simultaneously creating it, which is then recorded on-chain. This differs from blockchains like Bitcoin and Ethereum, where keys are created locally but are not recorded on chain.

The below charts show the count of these two different types of operations on both Kin 2 and Kin 3. Over the last three months, 36% of Kin 2 operations and 72% of Kin 3 operations have been account creations:


In theory, Kin account creation could be a good proxy for blockchain activity: more Kin accounts could mean more users. But the Kin blockchain has another modification which adds more noise to this measurement: Kin accounts do not have a minimum required account balance, and therefore can remain empty indefinitely.

Stellar-based ledgers require a ‘base reserve’, which is a minimum amount of native units required for each address. This serves as a spam prevention mechanism to inhibit empty addresses from bloating the blockchain. For Stellar, this base reserve is 0.5 XLM (about $0.06 at current prices). Kin, however, does not have the same required minimum account balance. Kin initially implemented a base reserve value of 1,000 Kin but this was later changed to 0 Kin at ledger #5 (a ‘ledger’ is Kin’s version of a block).

The below chart shows Kin’s (both Kin 2 and Kin 3)  non-empty balances over the last month. The orange area represents the percentage of Kin addresses with balance and the blue area represents the percentage of empty addresses.


Furthermore, Kin transaction fees are basically non-existent. Kin’s ‘create account’ operation has a fee of .001 Kin, which at the time of writing is about $0.000000023 USD. For comparison, Bitcoin’s mean transaction fee is currently $2.28, and Ethereum’s is $0.12.

In fact, there has only been a total of 30,015 Kin paid in transaction fees on the Kin 3 blockchain over the last three months. That amounts to a total of a little more than $1 USD worth of total fees:


The combination of low fees and no base reserve make it possible to add millions of addresses on the ledger at basically no cost. This highlights one of the problems of using operations count as a measurement for blockchain activity. Blockchains like Bitcoin and Ethereum do not track account creations on chain, while Kin does. This inflates Kin’s on chain operation count compared to those chains, which makes it an unreliable metric for comparing different platforms.

Separating out Kin payments from account creations gives a somewhat clearer picture. The below chart shows different average daily transaction counts over the last three months compared to Kin’s (combined Kin 2 and Kin 3) payment count:



Kin is near the top of the pack, trailing only EOS. This highlights Kin’s core use case; Kin was designed to be used within a messaging app, primarily for microtransactions. This naturally leads to low fees and a high transaction count. Similarly, EOS is designed as a Dapp platform and has low fees, which also leads to a high transaction count. Bitcoin, on the other hand, is not used as a microtransaction or Dapp platform, so it has a significantly lower transaction count despite being the leader in terms of market cap.

Using Transfer Value To Assess Claim #1

Transfer value gives a different picture of on-chain activity. We define transfer value as the sum USD value of all native units transferred (i.e., the aggregate size in USD of all transfers) during that day.

Theoretically, high daily transfer value should signify high activity. But transfer value is often quite noisy, especially on low fee blockchains where there are minimal costs to sending transactions. Some transfers might simply be users moving money around between addresses they own, for example.

To account for this, Coin Metrics has devised an ‘adjusted transfer value’ metric, which removes noise and certain artifacts like self-sends, or deliberate spammy behavior. While this results in a decreased transfer value, we believe this represents the best assessment of true economic activity on chain, and gives a slightly clearer picture of real transfer volume. The following chart shows the daily adjusted transfer value for Bitcoin, Ethereum, Bitcoin Cash, Litecoin, and Ripple, compared to Kin (Kin 2 and Kin 3 combined):

Despite having a high number of daily operations, Kin’s adjusted transfer value is much lower than the other chains. While the other blockchains mostly have daily adjusted transfer values of over $100,000,000, Kin’s daily transfer value is closer to $1,000,000.

Furthermore, Kin’s average transaction value is also low compared to other blockchains:


While other chains have average transfer values in the thousands, Kin’s average transfer value has been trending towards $1.

This again goes back to how the Kin blockchain is being used. By their nature, microtransaction platforms will have more transactions for smaller amounts. Does this mean that a microtransaction platform like Kin has more activity than a platform like Bitcoin, which is not primarily used for microtransactions? Ultimately, it depends how you define blockchain activity. Kin could be considered one of the most active blockchains if measured by payments count, but could be considered one of the least active if measured by transfer value.

Claim #2: Assessing Blockchain Usage

Despite the fact that last month over 300,000 people earned and spent Kin as a currency, the SEC is still saying that it might be a security.

Kik Responds To the SEC Complaint

Traditional applications typically have user profiles and ask for personal information like email or phone number in order to identify unique users. Blockchains, however, only have addresses (an address is like a unique bank account number except users are not limited by the number of addresses they can create). While this has advantages, it also makes it difficult to determine exactly how many individuals are using a blockchain. Addresses represents the maximum number of users that could be using a blockchain, assuming that each user needs at least one address. However it is important to note that a single user could be operating multiple addresses, which means that the number of actual users may be significantly lower than the number of addresses.

In the following section, we investigate Claim #2 in terms of ‘active addresses.’

Using Active Addresses To Assess Claim #2

One way to measure the number of potential blockchain users is to look at active addresses, which we define as ‘the number of unique addresses that were active in the network (either as a recipient or originator of a ledger change) during that day.’ ‘Ledger changes’ include anything that changes the specific blockchain’s on-chain ledger, including transactions and operations.

Since Claim #2 is specifically about the number of spenders and earners  of Kin, we filtered out Kin’s account creation operations in order to look solely at the active addresses making payments on the Kin blockchain.

The below chart shows the daily count of unique addresses that were active as the originator of a Kin payment over the course of the last three months for both Kin 2 and Kin 3:


Interestingly, Kin 2 has significantly more originating active addresses than Kin 3. Although Kin is in the process of migrating to Kin 3, it appears that Kik is using data from the Kin 2 chain to support their claims about usage. The migration from Kin 2 to Kin 3 is currently in progress, so it remains to be seen if the usage numbers fully transfer over to the new chain.

Additionally, both Kin 2 and Kin 3 have more active addresses that received payments than originated payments. This is possible because a single address can send out many payments to multiple receivers. Overall, Kin has many more earners than spenders. The below chart shows Kin payment receivers, filtering out account creations:

The following chart shows the Kin 2 and Kin 3’s combined active addresses compared to other blockchains. Kin is well below Bitcoin and Ethereum, but compares favorably to several other blockchains (both charts also filter out account creations to focus on payments):


However, a majority of these active addresses hold a small balance of Kin. The following chart shows the amount of Kin addresses with a balance of at least 10,000 Kin over the last month. At the time of writing, 10,000 Kin is equal to $0.23 USD:

The chart shows steady growth over our sample time frame. At most, there have been 34,475 addresses that hold at least $0.23 USD. This is orders of magnitude less than other blockchains in our sample, which each have at least 1,000,000 addresses that hold at least $1 USD (which is an even higher threshold than 10,000 Kin). The following chart shows the daily average number of addresses with a balance of at least $1 USD for the five blockchains in our sample compared to addresses with a balance of at least 10,000 Kin:


Furthermore, a large majority of Kin addresses are either empty, or hold less than 10,000 Kin. Below are the daily averages (calculated over the last month) of Kin total accounts, accounts with balance, and accounts with 10,000 Kin :

Although Kin has a relatively high number of active addresses, it has a relatively low amount of addresses with a significant account balance. This is further evidence that Kin is being used primarily as a microtransactions platform. It only costs fractions of a penny to use the Kin blockchain given the combination of low fees and absence of a minimum account balance. This makes it difficult to compare users across chains, which have different use cases and operating costs.


We analyzed Kin’s ultimate source of truth, their blockchain ledgers, in order to assess their claims on activity and usage. The Kin blockchain has a high number of daily operations, which is the metric that Kik uses to measure blockchain activity. However our analysis found that most of these operations were account creations which are creating empty addresses. Filtering out account creations, Kin still has a relatively high number of on chain payments compared to other blockchains. But when measured by transfer value, Kin was well below other major blockchains in our sample. Similarly, Kin falls below the dominant blockchains in terms of daily active addresses; however, growth has been increasing.  Ultimately, what our data show is that Kin’s users are transferring small amounts, and paying low fees. Additionally, a majority of Kin’s active addresses have small account balances. While this makes sense for a network built around micropayments, when viewed across multiple metrics, our data show that Kin is not more widely used than dominant chains such as Bitcoin or Ethereum. It is therefore critical to examine multiple factors, including the type and quality of usage, in order to get a full picture of the activity on Kin or any blockchain.


We are open sourcing the data we used for this report, which you can access here. As always, feel free to reach out to if you have any comments or questions.

An important network value to transaction ratio caveat mtv-caveat 2017-06-28 19:27:11 If you’ve been following coinmetrics closely, you might be convinced of the usefulness of our network It’s awfully difficult to extract decent transaction volumes from blockchains directly, because Bitcoin (and most cryptoassets) does not maintain balances of users, but rather spent and unspent’outputs. If Bob wants to send 9 BTC to Alice but has 10 BTC in his wallet, his’entire 10 BTC (acquired in a prior transaction) is recorded as the input for the transaction and 1 BTC is returned to him as change. If both listed addresses are new, there is no way of knowing which is the change address and which the recipient. In this transaction, for instance, both addresses had not been used and there is only one input.  If you compare our numbers for transaction value for bitcoin to those available at, you’ll see that this transaction mentioned above, guesses that’0.7695 BTC was in fact sent, rather than 3.72 BTC. This estimation difficulty also explains why there is such poor data for other cryptoassets, since there aren’t many wallet services as sophisticated as which are so committed to releasing that sort of data. Estimating change outputs ‘ when possible ‘ is hard, and much of the time it is entirely impossible. Therefore we made the deliberate decision to aim for a different sort of ‘precision ‘ to eliminate the double-counting of change outputs when they were known, and to include them when it was impossible to tell. This means our transaction value number is guaranteed to To clarify: makes an educated guess about which outputs are change, based on probabilities and the extrapolated tendencies of their wallet users. This is a proprietary algorithm. Our estimation is certainly too large, but we can offer some guarantees, which is nice. We know ‘ under a limited set of conditions ‘ exactly which transactions are change, and can rule them out compThe tradeoff here is therefore: a) a plausible estimate based on guesswork and heuristics or b) a precise yet overly-broad estimate based on falsifiability (removing transactions we absolutely know.  Our code is public on our github, so our method can be examined and critiqued by anyone. If a better open-source method of ruling out cAnd since the estimates that use only work for bitcoin, and we’re aiming to find comparable metrics between different cryptoassets, we dispensed with their estimation and scraped various blockchains to find our own numbers. The important thing here is that our transaction values may be elevated, but if they are systematically elevated across different cryptoassets.  Since we seek to arm our readers with reliable data, we’re going to issue this caveat as clearly as possible: our NVT indicator, which is dependent on an estimate of transaction volume, isWe currently can’t say confidently whether this is the case or not, but to the best of our knowledge, we are one of the only projects procuring this sort of data and making it freely available. We are aware of the shortcomings of the collection process, and are working to refine it and provide the best possible estimates for our readership.