Coin Metrics' State of the Network: Issue 33

Tuesday, January 14, 2020

Weekly Feature

Is Bitcoin Becoming a Safe Haven Asset?

By Kevin Lu and the Coin Metrics Team

Discussion regarding Bitcoin’s status as a safe haven asset during times of elevated geopolitical risk and macroeconomic uncertainty has existed almost since Bitcoin’s inception. Despite anecdotal evidence that Bitcoin has reacted positively to certain historical events and a compelling narrative that Bitcoin has the fundamental properties to serve as a safe haven asset, the actual body of empirical evidence (prior to recent events) is inconclusive. 

Recent events have transpired that significantly expand the body of empirical evidence -- the intensification of military tensions between the United States and Iran. In this issue of State of the Network, we examine events related to the conflict to further our understanding of Bitcoin’s reaction function to geopolitical events. Additionally, we use high time-resolution price data to study the degree of market efficiency and speed of information diffusion.

Major Events in the United States-Iran Conflict 

We conduct event studies on three major events related to the intensification and subsequent de-escalation of military tensions between the United States and Iran in January 2020. A description of the three major events is found below: 

  1. On January 3, 2020 at 01:00 UTC, major news sources began to report on a drone strike executed by the United States which killed Iranian Major General Qasem Soleimani. The actual drone strike occurred roughly three hours earlier to first publication and initial reports in the immediate aftermath were short on details.

  2. On January 7, 2020 at 22:43 UTC, Iran launched a missile attack against United States military bases located in Iraq as retaliation to the assassination of Major General Qsem Soleimani. This event marked a dramatic escalation in the military tensions between the United States and Iran. 

  1. On January 8, 2020 at 16:27 UTC, President Trump addressed the nation regarding the Iranian missile attack, stating that “no Americans were harmed” and that “Iran appears to be standing down”. President Trump concluded his ten-minute speech by stating, “the United States is ready to embrace peace with all who seek it”. These comments were interpreted as a cessation of hostilities and a deescalation of tensions. 

During this time period, oil futures and gold futures both experienced immediate positive reactions to events that marked an escalation of tensions and negative reactions to the de-escalation. This shows their high degree of market efficiency and the speed and effectiveness of information diffusion during a volatile situation. Market participants were able to quickly and accurately adjust prices due to changes in the probability of disruption of oil supplies in the Middle East. 

We examine Bitcoin’s response to these events using Coin Metrics’ Real-Time Reference Rates, which represent a global price quoted in U.S. dollars for a set of cryptocurrencies, updated once per second. Real-Time Reference Rates are calculated using a robust and resilient methodology that adheres to international best practices for financial benchmarks, including the International Organization of Securities Commissions’ (IOSCO) Principles for Financial Benchmarks. Constituent markets used in the calculation of the Real-Time Reference Rates are carefully selected using a framework which evaluates markets and exchanges along numerous dimensions. 

United States Drone Strike 

Major news sources began reporting on the U.S.-led drone strike which killed Iranian Major General Qasem Soleimani on January 3, 2020 at 01:00 UTC. Reports were first circulated on Twitter and examination of timestamps from major publications indicates that the information was widely disseminated by 02:00 UTC. By this time, both oil and gold futures had already made significant moves in response to the attack. 

Although many observers point to Bitcoin’s response as evidence of its safe haven properties, a close examination of the timing suggests that multiple explanations are possible. While Bitcoin did subsequently move upward mirroring the response seen in oil and gold, it did so with roughly a three hour delay. Significant movement in Bitcoin’s price was not observed until 04:00 UTC. 

One possible explanation is that market participants bid up the price of Bitcoin in the face of greater geopolitical uncertainty (a validation of the safe haven theory) but did so with a delay because the market is inefficient. Under this explanation, market participants are slow to learn about or act upon information. 

An alternative explanation points to the timing of Bitcoin’s response and concludes that this event indicates no strong relationship between Bitcoin and geopolitical events. Bitcoin’s price movement did not occur at the same time as other financial markets such as oil and gold futures despite Bitcoin’s market being open 24/7. And for several hours after the event, Bitcoin prices declined or remained stable which is incompatible with an explanation that Bitcoin markets are inefficient due to slow information diffusion. If the slow information diffusion explanation were true, we would expect prices to gradually reflect available information, and not react suddenly and sharply as it eventually did. 

Finally, Bitcoin has historically seen sharp intraday price changes without any apparent news catalyst. Instead, these price changes are driven by forced liquidations on futures products which can have a disproportionate impact on short-term prices and are often the cause of bouts of short-lived volatility. 

When examining this one event in isolation, multiple explanations are possible. Despite loud claims that Bitcoin’s price movement was driven by the U.S.-led drone strike, a spurious relationship cannot be ruled out. 

Iranian Missile Attack 

While the previous event illustrates the potential limitations in market efficiency for Bitcoin and the slow speed of information diffusion during normal conditions, an examination of the Iranian response illustrates how rapidly market efficiency can improve. 

In response to the United States-led drone strike, Iran retaliated by launching several missiles to United States military bases located in Iraq. Initial reports were again short on details, and information first circulated through journalist Twitter accounts before being picked up by mainstream news publications. The earliest known mention of the Iranian missile attack was on January 7, 2020 at 22:43 UTC. 

In contrast to the multiple explanations in the previous event, Bitcoin’s response to the Iranian missile attack suggests a much narrower set of possible explanations. First, Bitcoin moved in concert with oil and gold futures with no noticeable delay. Second, prices moved upward over the subsequent hours with a steep but gradual slope -- not the sharp price movements that are commonly observed during forced liquidations on futures positions. In fact, few forced liquidations on futures positions were observed on BitMEX despite the large change in prices. 

The body of evidence strongly suggests a connection between Bitcoin and the escalation of military tensions between the United States and Iran and serves as a validation of the safe haven theory. 

Deescalation of Military Tensions 

President Trump’s remarks indicating a de-escalation of military tensions is perhaps the strongest evidence in the history of Bitcoin that there is a direct connection between Bitcoin and geopolitical events. While the previous two events in our study measured Bitcoin’s response on the order of hours, its response to this event can be measured on the order of minutes. 

President Trump started his address to the nation on January 8, 2020 at 16:27 UTC. Bitcoin, in concert with traditional financial markets, responded immediately to the news that both the United States and Iran would not seek further military action. This event and the other two events in our study show that under the proper circumstances, Bitcoin’s market efficiency can increase and has the potential to be as efficient as the largest financial markets in the world. Circumstances were ideal for optimal market efficiency because market participants were already attuned to the significance of the unfolding situation and the time of President Trump’s remarks was widely known in advance. This conclusion is consistent with a similar study we performed for TRON in State of the Network Issue 10, where we found that under optimal conditions, even markets for a mid-capitalization asset can become very efficient. 

While many observers have pointed out this connection, we feel the implications of this event are still not widely appreciated. We have witnessed perhaps the strongest validation of the Bitcoin safe haven theory in its 11 year history, and this watershed moment marks an important milestone in Bitcoin’s maturation as a legitimate asset class. 

Why has this event in particular invoked such a strong reaction from Bitcoin? We feel that there are both first order and second order effects at play. 

First, the escalation in military tensions increased policy uncertainty. This heightened uncertainty increases the attractiveness of safe haven assets such as gold. 

Second, these events caused a short-lived but significant decline in real yields (nominal interest rates adjusted for inflation) which increases the attractiveness of holding Bitcoin. Nominal interest rates declined slightly in part because U.S. sovereign bonds were bid due to safe haven capital flows. But inflation expectations also rose because market participants were pricing in the possibility of a disruption in oil supplies -- products derived from crude oil (most notably gasoline but also many consumer products) are a key determinant in headline inflation rates. Declines in real yields can be driven by declines in nominal interest rates which reduce the opportunity cost of holding a non-yield producing asset like Bitcoin. Declines in real yields can also be driven by increases in inflation expectations which drive an increased need for store-of-value assets like Bitcoin. 

It is worth noting, however, that releases of pure macroeconomic data (without an increase in geopolitical risk) which have resulted in large changes in real yields have failed to spark a reaction in Bitcoin’s price thus far. Such events include important meetings of the Federal Open Market Committee and releases of key macroeconomic indicators like the U.S.’s employment report and important survey-based indicators like manufacturing PMI. 

Taken together, this confluence of events caused a perfect storm that led to Bitcoin having an extremely strong reaction. On the first order, it appears that Bitcoin is a source of safe haven capital flows during times of uncertainty, at least for now. On the second order, Bitcoin may begin to exhibit some sensitivity to changes in real yields and the macroeconomic events that lead to changes in real yields. In addition, while the initial reaction in Bitcoin to the United States-led drone strike may have been spurious, it renewed discussion about Bitcoin as a safe haven asset and introduced the idea that other traders are considering it for safe haven capital flows. Ultimately, assets attain a safe haven status by a combination of their fundamental properties and due to game theory-driven consensus among investors. 

Finally, these events serve as a contemporary study of market efficiency with serious implications surrounding the debate on whether the upcoming block reward halving is priced in. The speed of response indicates that under normal circumstances, there are still limitations  to Bitcoin’s market efficiency, but under special circumstances in which market participants become attuned to the significance of upcoming events, market efficiency can increase to levels comparable to the largest financial markets. 

Network Data Insights

Summary Metrics

The major cryptoassets rallied over the past week after a rocky start to 2020. Usage was up for BTC, ETH, XRP, and BCH, while LTC saw a slight decrease. XRP, notably, had a 117% increase in active addresses and close to a 50% increase in transaction count.

Both BTC and BCH adjusted transfer value grew by over 33% week-over-week with ETH not too far behind at nearly 18%. But BTC still has a huge lead in terms of average daily transfer value. BTC had a daily average of $1.7B adjusted transfer value over the last week, while ETH and BCH had $195M and $130M, respectively.

Network Highlights

ETH annual issuance percentage (i.e. the monetary inflation) fell to an all-time low of 3.45% at the end of December, 2019 as the Ethereum ice age approached. The Ethereum ice age was a planned difficulty increase which made it more difficult to mine blocks, and therefore increased the time between new blocks. Lower block count led to lower total daily block rewards, and therefore led to decreased issuance. 

The ice age was originally designed to grind the Ethereum network to a halt in order to encourage users to shift over from Ethereum 1.0 to Ethereum 2.0. However, Ethereum 2.0 did not launch by the end of 2019 as once expected. Ethereum therefore hard forked on January 2nd, 2020 in order to increase difficulty and delay the ice age. After the fork, ETH annual issuance is now back up to 4.56% as of January 12th.  

Ethereum ERC-721 transactions have cooled off at the beginning of 2020 after a strong close to 2019. The following chart shows transaction count growth over the past year (1/13/2019 - 1/13/2020)  for ETH, ERC-20’s, and ERC-721’s, smoothed using a seven day rolling average.

Market Data Insights

Tensions between the United States and Iran this past week are largely responsible for a widespread rally in cryptoassets. Bitcoin is up 11%, outpacing gains seen in some smaller cryptoassets. Historically, altcoins have had a high beta to Bitcoin returns and having exposure to altcoins during upswings has been used as a method to increase overall portfolio return.. 

Still, we do see some isolated examples of extreme price movements that cannot be easily explained. Bitcoin Cash SV (+49%) is the strongest performer among major cryptoassets perhaps due to speculation about positive developments  surrounding the legal developments of Craig Wright, a vocal proponent of Bitcoin Cash SV. Bitcoin Cash (+20%), EOS (+19%), and Litecoin (+18%) are all strong performers this week on no clear news catalysts. 

Mid-cap cryptoassets are also mixed with some assets outperforming Bitcoin and others underperforming. Dash (+30%) and ChainLink (+25%) are notable movers. Ethereum Classic (+14%) and ZCash (+16%) continue with a strong performance over the past several weeks. Cosmos, one of the strongest performers over the past three months, is only up 1% this week. 

Volatility for most cryptoassets continues to steadily decline. Many cryptoassets are at or approaching all-time lows when measured on a three month rolling basis -- only Bitcoin’s volatility appears to be stable or trending upwards. This reflects the proliferation of leveraged products and how investor interest has become increasingly concentrated in Bitcoin. Volatility for nearly all cryptoassets are now inline with Bitcoin’s.

The relationship between Bitcoin and gold deserves continued observation. Observers have pointed to Bitcoin’s performance during the summer of 2019 in which both Bitcoin and gold saw large gains in response to a sudden shift in monetary policy from the world’s major central banks. This shift involved unexpected interest rate cuts, causing many developed world countries’ sovereign bonds to trade with negative yields, and renewing concerns about the sustainability of the current path of monetary policy and the long-term consequences of such actions. More recently, both Bitcoin and gold jumped simultaneously in response to military tensions between the United States and Iran. 

While the recent conflict presents quite convincing evidence in support for theory that Bitcoin has benefited from safe haven capital flows, the correlation between Bitcoin and gold has always been low and inconsistent when measured over longer time frames. 

Here we show the correlation of Bitcoin daily returns and gold daily returns over a 90 day rolling window. While correlation was weakly positive for the majority of 2019, it has since recently flipped to be negative, although the sharp decline has reversed over the past several days due to the situation between the United States States and Iran. 

In order to see higher correlations between Bitcoin and Gold, Bitcoin would need to begin to react instantaneously to releases of surprising macroeconomic information that reflect changes to growth, inflation, and real yields. Thus far, there has been no evidence that Bitcoin consistently exhibits such behavior. 

CM Bletchley Indexes (CMBI) Insights

All indexes started the year in a stellar fashion off the back of very strong market performance across most cryptoassets this week. The Bletchley 10 (large cap) and Bletchley 20 (mid cap) performed best, each returning ~12% for the week with the Bletchley 40 (small cap) lagging the higher cap indexes, returning only 6%.The relative uniformity of the market movement this week can be seen through the low return profile of indexes when denominated in Bitcoin terms.

The Bletchley 10 Even was the strongest performer of the week, outperforming all indexes, demonstrating for the second week running that there is merit in considering index calculation designs other than market cap weighting for cryptoasset managers.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 6 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at info@coinmetrics.io.

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you'd like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics' State of the Network: Issue 32

Tuesday, January 7th, 2020

Weekly Feature

Investigating the Failed Stellar Inflation Experiment

By Antoine Le Calvez and the Coin Metrics Team

Each blockchain has a unique process for issuing new supply. For some, like Bitcoin, the full issuance schedule and final supply are encoded into the protocol (and is unlikely to change, due to social consensus). 

Bitcoin issues new supply through block rewards issued to the miner of each block. Bitcoin block rewards halve on a predetermined schedule -- the next halving is expected to take place on May 11th, 2020. Other blockchains have issuance schedules that are not as resolutely encoded, and are subject to change. Ethereum issuance has been adjusted several times since 2017, most recently reducing the reward from 3 ETH per block to 2.

Whenever new supply is issued, monetary supply is inflated (we will therefore refer to this process as monetary inflation). This (at least theoretically) dilutes the value of the rest of the supply, unless an equal amount of existing supply is burned. 

In the case of Bitcoin and Ethereum, the new supply is used to reward the protocol’s miners. But the new supply can also go to other destinations. Some blockchains, such as Stellar, reserve some of their newly issued supply for use by an official protocol-focused foundation. The Stellar Development Foundation (SDF), for example, is a non-profit organization that has a mandate to support the development and growth of the Stellar network.

From its genesis in 2014 until the activation of the version 12 of its protocol, the Stellar network featured a monetary inflation process that issued new units at a rate set to 1% per annum.

Here’s how it worked: each Stellar account could designate an “inflation destination” account that would get as many votes as lumens (XLM) the designating account held. Votes were tallied weekly and each inflation destination account that got voted by at least 0.05% of the supply would receive a share of the inflation pool proportional to the total balance of all its designating accounts, with any unallocated amount to be distributed during the next week. Any account could be designated as an inflation destination but only those that got voted by at least 0.05% of the supply would qualify to receive the new issuance. 

In addition to newly minted units, transaction fees were also redistributed this way. However, they only account for a tiny amount of value compared to the inflation.

On September 30th, 2019 following a year of discussion within the community, the SDF announced that the monetary inflation process would be phased out. This protocol change was completed on October 28th 2019.

In this feature, we’ll look at the on-chain data to get to an understanding of the process, look at the reasons why it was phased out and finally, evaluate the impact it had on Stellar’s on-chain metrics.

Goals vs reality

In an email to the stellar-dev mailing list, Jeb McCaleb (co-founder of Stellar) listed 2 main reasons behind the existence of the inflation process:

  1. A way to “address some criticisms of cryptocurrencies being deflationary”

  2. To “give people incentive to collaborate and decide how network rewards are allocated”

Jed also elaborated that “any early inequities or problems with the initial distribution would get less important as time went on.”

Reality however proved different. 

In a blog post announcing the deprecation of the inflation process, the SDF explained that the new supply, which should have helped “support the development and growth of the ecosystem,” was instead being claimed by individuals who were not actively working on development projects. This primarily happened through the creation of inflation pools, which allowed individuals to pool their resources together to pass the 0.05% supply threshold to qualify for receiving an inflation payout. 

Inflation payouts overview

Over the roughly 4 years the inflation process was running (from October 2015 to October 2019), it was run 280 times and only 23 unique recipients got to share 5.482B XLM as the designated inflation destination accounts. 

Astute observers will have noticed that the number of times the inflation process was run (280) is greater than the number of weeks that the process was running for (roughly 212 weeks). 

From the Stellar protocol’s point-of-view, the inflation process didn’t start at the time the current public network was launched (Sept 30th 2015) but earlier, when the first public Stellar network was launched on July 1st 2014.

Participants

From the list of inflation recipients, we can identify several types of addresses using public sources:

  • Stellar Development Foundation (SDF) addresses

  • Exchange addresses

  • Inflation pool addresses

  • Unknown addresses (unknown large balance holders, etc..)

Inflation pools are a way for users to benefit from the inflation process if they own less than the qualifying amount to participate themselves (0.05% of the outstanding supply, roughly 50M XLM or $2.5M at current prices). Inflation pools users would designate the pool address as their inflation destination and get paid their due share weekly.

Exchanges started partaking in the inflation process too, with Binance and Poloniex even distributing the proceeds to their XLM balance holders.

In total, 1,087,306 accounts designated an inflation destination. This means that only 18.3% of the accounts ever created before the end of the inflation process participated in it. While this represents only a fraction of the accounts, it likely represented a large proportion of the supply since many of the largest accounts participated. Only a small minority (6.6%) of the accounts that designated an inflation destination voted for one that never passed the 0.05% threshold.

Looking at the payout recipients of the 2 largest inflation pools’ (Lumenaut and XLM Pool), we can see how many accounts participated in inflation pooling (and received payouts) as well as several key milestones: the end of the inflation process (late October 2019) and a change in policy from Lumenaut (in April 2019) which made it so they would only payout accounts holding at least 100 XLM.

This means that despite there being millions of Stellar accounts, only a few tens of thousands got to regularly enjoy the benefits of the inflation process (perhaps not surprising given that only 18.3% of accounts ever designated an inflation destination account).

Payouts flows

Putting it all together, we can paint a picture of how this newly minted money flowed:

As we can see, the great majority (98%) of the inflation payouts accrued to the SDF. This can be explained by two factors:

  • The SDF controls 80% of the supply and likely designated itself as an inflation destination

  • It has always participated in the inflation process

Given that Stellar became very popular in 2017, the SDF had a 2 year head start where it was nearly the only participant benefiting from the inflation process.

Furthermore, only a paltry amount of supply (834K XLM, $41K at current prices) went directly to community projects the way the inflation process intended it (it is unclear how the unknown destinations used their funds). Furthermore, since 98% of the newly created money went to the SDF despite it controlling 80% of the total supply, the inflation process arguably worsened inequities. For its part, the SDF has spent roughly 340M XLM (or $16.7M at current prices) from a total mandate of nearly 30B XLM since November of 2019 on development and growth.

Impact on network metrics

Looking at activity around Stellar’s native token (XLM), we can see the impact of the end of the inflation process:

The weekly spikes in addresses receiving XLM is now gone. These were caused by the inflation pools paying out their users. The Stellar inflation is therefore a good example as to why network data metrics have to be contextualized to take into account each network’s idiosyncrasies. Rather than measuring on a daily basis, Stellar active receiving addresses (the number of unique addresses that received XLM at least once in the observed week) could be measured instead on a weekly basis to smooth out the effect of this irregular issuance.

Doing so, we can see that it is now reaching lows unseen for months:

Aftermath

The SDF blog post announcing the end of the inflation process ended by mentioning that they would soon shed more clarity about their plans for handling their XLM, including the 5.4B XLM they received via the inflation process.

Indeed, a few days after the deactivation of the inflation process, the SDF burned 5B XLM from its operating fund and 50B XLM from its funds earmarked for giveaway, bringing the circulating supply to exactly 50B XLM, 20B of which is now outside the SDF control.

What we are left with is a few tens of millions of XLM having been doled out to exchanges and XLM owners over 5 years, with very little of it going to its intended use: helping community projects.

The Stellar inflation process was an interesting economics experiment. Analyzing it draws parallels with current hot topics like the Cantillon effect. It also helps in showing that each network has idiosyncrasies that have to be taken into account in order to better understand its activity and usage.

Network Data Insights

Summary Metrics

Ethereum (ETH) usage suffered a down week after completing its second hard fork in less than 30 days. ETH active addresses fell 16% week-over-week, and transfer count fell over 10%. Comparatively, BTC was marginally up in both active addresses and transfers, increasing 0.6% and 2.7%, respectively. 

XRP, LTC, and BCH adjusted transfer value all increased by at least 50% from the previous week. BTC adjusted transfer value, however, went in the opposite direction, decreasing by 6.2%. 

Network Highlights

The major stablecoins are off to a hot start in 2020. The following chart shows the weekly growth in the number of addresses with a balance of at least $10 for 18 large cryptoassets. The Ethereum version of Tether (USDT-ETH), Paxos (PAX), and USD Coin (USDC) all grew by at least 2.2% over the past week, while BTC and ETH grew 0.52% and 0.94%, respectively.

The number of addresses with a balance of at least $10 can be used as an approximate measure of the number of total “retail” holders of an asset. However, it’s important to note that one address does not necessarily mean one user (users often have multiple addresses), so it should be thought of as a maximum number of potential holders. 

The number of stablecoin addresses with a balance of at least $1M has also been increasing over the past year. The following chart shows the annual growth for the same 18 cryptoassets. USDT-ETH, USDT Omni (USDT), and USDC all outpaced Bitcoin over the course of 2019.

Read more on this plus similar charts for 18 other metrics in our State of the Network 2019 Year in Review.

Market Data Insights

Despite the increase in prices over the weekend, most major cryptoassets are flat or down over the week with a few important exceptions. Both Bitcoin Cash (+5%) and Bitcoin Cash SV (+9%) saw outsized gains relative to the overall market. 

Coins with privacy features including Monero (+15%), Dash (+14%), and ZCash (+5%) have performed well over the past week. Monero briefly entered the top 10 coins ranked by market capitalization at the tail end of the previous week. Ethereum Classic (+4%) continues its outperformance over the past month. 

Bitcoin and the broader cryptoasset reaction function to macroeconomic and geopolitical events is still not understood. Over the past weekend, an event transpired which provides additional data to help us understand Bitcoin’s reaction function -- the United States led a drone strike that killed Iranian Major General Qasem Soleimani. Over the subsequent days, tensions between the United States and Iran have escalated as both countries consider their response. 

The drone strike occurred at approximately 22:00 UTC time on January 2, 2020. News of the strike started to be published approximately three hours later at 01:00 UTC time on January 3, 2020. It was during this time that oil and gold futures had a sharp reaction -- oil likely due to market participants pricing in a higher probability of disruption in oil supplies in the Middle East and gold likely due to a standard flight-to-safety response in the face of geopolitical conflict. 

Bitcoin did not immediately respond to the publication of the drone strike. A sharp increase did occur about three hours after the initial reports started coming in, suggesting either a delayed reaction or a spurious connection. Oil, gold, and Bitcoin are all markedly higher since the incident, adding some support that Bitcoin responds positively to such events. However, the difference in timing suggests that a spurious connection between Bitcoin and the event or limitations on the speed of information diffusal are still possible explanations. We previously examined the speed of information diffusal of cryptoasset markets using TRON in State of the Network Issue 10

As the weekend progressed and the situation continued to escalate, oil and gold continued to rise with a large increase on the night of January 5, 2020. Again, Bitcoin saw a positive movement delayed approximately three hours. 

CM Bletchley Indexes (CMBI) Insights

2019 was a story of two halves. After the bear market of 2018, the first half of 2019 saw much promise as cryptoassets, led by Bitcoin, all performed strongly. Large-cap assets were the best performers with the Bletchley 10 returning close to 200% leading up to July. However, after this rapid marketwide recovery, cryptoassets struggled to maintain these growth levels, and saw declines through the second half of the year. Many cryptoassets, including ETH, even returned to the levels where they started 2019. 

Large-cap assets still finished the year relatively strong, but low-cap assets struggled particularly through Q3. This is evidenced by the Bletchley indexes with the Bletchley 10 returning 49%, the Bletchley 20 returning 17% and the Bletchley 40 returning -45%.

Cryptoassets started 2020 with a relatively quiet week as the Bletchley Indexes saw mixed returns. The Bletchley 20 performed best, returning 1.7%, with the Bletchley 10, Bletchley 40 and Bletchley Total all finishing the week relatively flat. It is interesting to observe that most of the even indexes outperformed the market cap weighted indexes this week, indicating that the larger-cap assets in each index underperformed the lower-cap assets in each index where this outperformance occurred.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • In case you missed it, check out our State of the Network 2019 Year in Review, over 30  pages of charts and analysis about the major cryptoassets’ performance in 2019.

  • Coin Metrics is hiring! We recently opened up 6 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at info@coinmetrics.io.

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you'd like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

State of the Network 2019 Year in Review

Wednesday, January 1st , 2020

By Nate Maddrey and the Coin Metrics Team

In this special edition of State of the Network (SOTN) we take a look back at how the major cryptoassets performed over 2019 across four categories:

  1. Valuation

  2. Usage and Adoption

  3. Economics

  4. Security and Health 

We selected several metrics for each section and analyzed how 18 of the largest cryptoassets performed across those metrics. Each section includes charts which show the yearly change for a metric for each asset as well as a summary table with yearly averages from 01/01/2019 to 12/30/2019 (the valuation table shows end-of-day values for 12/30/2019 while all other tables show yearly averages).

Note: If you received this piece through email it might be truncated due to length. View on the website (https://coinmetrics.substack.com/) for the full piece.

Valuation

Table values are end-of-day values for 12/30/2019

Price, USD

Despite the downturn at the end of the year, most of the major cryptoassets actually finished significantly up on the year in terms of price. 

Bitcoin (BTC) finished the year up 90% while Ether (ETH) finished down 6%. After Tezos (XTZ) was added to Coinbase and XTZ staking was released on Coinbase Pro and Binance, XTZ had a late surge to finish the year up a stunning 182%. 

A few mid-cap assets also had a strong year, including Chainlink (LINK), up 513%, and Basic Attention Token (BAT), up 45%. XRP, Stellar (XLM), and Zcash (ZEC) on the other hand all finished in the red, down 47%, 60%, and 52% respectively. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) of the USD daily midnight UTC closing price (CM Reference Rates)

Market Capitalization

Market capitalization (market cap) is calculated by multiplying the current total supply by the current market price. For example, if BTC’s price today was $10,000, every coin would be valued equally at $10,000. This would result in a total market cap of $178,981,250,000 (17,898,125 total BTC multiplied by $10,000). 

For the most part, yearly market cap changes align closely to price changes with one big exception: stablecoins.

It was a big year for Tether on Ethereum (USDT_ETH). As we covered in SOTN Issue 17, USDT_ETH rapidly overtook Tether on Omni (USDT) in market cap in 2019. USDT_ETH’s market cap grew by almost 3700% over the past year to a total of nearly $2.3B, while USDT Omni’s market cap fell by nearly 39% to a total of about $1.6B. Two other stablecoins, PAX and USDC, grew by 65% and 100%, respectively. 

Note that we use total (or current) supply for our market cap calculations. This is supply inclusive of all funds held in treasury (or otherwise restricted) and visible on the ledger. This is in contrast to market cap calculations which use circulating supply which removes coins restricted from trading. Using total supply will yield larger market caps for assets such as XRP or XLM that have large tranches of restricted supply in treasuries. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 1 day (1d) basis

Realized Cap

Unlike market cap, realized cap values each coin at the time it last moved (i.e., transferred between two distinct addresses) on-chain. So if a coin last moved in 2017 when the price of the asset was $2,500, that particular coin would be priced at $2,500 instead of the current market price. The sum of the prices of all coins priced this way gives the realized cap. 

Realized cap can be thought of as a measure of the average cost basis of all holders of an asset. Read more about realized cap in SOTN Issue 14 and Issue 28.

Note that for assets for which founders hold large portions of supply in treasury, such as XRP, realized cap should be interpreted with caution. If founders move large portions of supply between treasury wallets at a time when prices differ significantly from the current price, it could result in large and unnatural moves in realized cap. Coin Metrics currently does not calculate realized cap for all assets covered in this issue; however, these will soon be available in the new year.  

BTC’s realized cap increased by nearly 28% over the course of 2019. ETH’s realized cap, however, fell by 19%. The differences in market cap vs realized cap can be interpreted as a difference between market expectations and investor behavior. In BTC’s case where its market cap grew by 97% while its realized cap only grew by 28%, price increased more than the average cost basis, which signifies that most investors held onto their coins rather than realize their profits.

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 1d basis

Market Value to Realized Value (MVRV)

Market value to realized value (MVRV) is calculated by dividing the market cap by realized cap. A low MVRV is a potential signal that market participants are minimally in profit or not in profit (if MVRV is negative), while a high MVRV ratio may signal that asset holders are well in profit.  

BTC MVRV increased over 2019 finishing at 1.33 indicating that BTC holders were increasingly in profit since the start of 2019 and remained in profit by the end of the year. ETH MVRV on the other hand grew modestly, signifying ETH holders were also increasingly in profit, but finished at 0.61 indicating that holders were collectively underwater at the end of the year. Bitcoin SV (BSV) MVRV dropped considerably over 2019 indicating that BSV holders were increasingly underwater, but still finished the year at 1.70, well into profit. 

Note that a high MVRV doesn’t necessarily signify future expected price increases. In fact, the opposite may hold. When holders are increasingly highly in profit, they are increasingly more likely to sell, and this has held true historically (for example, an MVRV of more than 4 has coincided with all the major post-bull run price declines in Bitcoin history). Whether this will hold true going forward remains to be seen. 

Chart values are daily (end-of-day) values (1/1/2019 - 12/30/2019) 

Volatility, Daily Returns, 30d

The 30-day (30d) volatility is measured as the 30d standard deviation of log daily returns. Read more about our analysis of volatility in the Market Data Insights sections in SOTN Issue 22 and Issue 29.

Volatility decreased across the board in 2019, finishing the year at 2.6% for BTC and 3.3% for ETH. Although there are some positives to price stability, lowered volatility can reduce profits for traders and may incentivize traders towards increasing leverage. 

Chart values are daily (end-of-day) values (1/1/2019 - 12/30/2019) 

Usage and Adoption

Table values are annual averages of daily values (1/1/2019 - 12/30/2019) 

Active Addresses

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 active in the network that day, either as a recipient or originator of a ledger change (“ledger changes” include anything that changes a blockchain’s on-chain ledger, including transactions and other operations).

Active addresses can serve as a proxy for daily active users of the underlying blockchains. However, one active address does not necessarily equate to one active user. Individual users can create and operate as many addresses as they want. Therefore active addresses represent a maximum number of potential blockchain users, while the actual number of daily users is lower. 

Active addresses increased for most of the major cryptoassets over 2019, a positive sign for overall crypto adoption. USDT_ETH, LINK, and XTZ  saw the largest growth in 2019 while XRP, XLM, and ZEC saw decreasing activity over the course of the year with XLM decreasing by a whopping 66%. The XTZ active addresses line appears thicker than other assets because XTZ has staking payouts on a regular basis, which leads to high variance in activity day-to-day. 

Note: ZEC active address metric and other usage metrics do not take into account shielded transactions.

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Number of Addresses with Balance of At Least $10

The number of addresses with a balance of at least $10 can be used as an approximate measure of the number of total “retail” holders of an asset. $10 is a somewhat arbitrary number but is a small enough balance to be considered an average, non-institutional investor, and large enough to not be dust (amounts smaller than the fee required to move them).

However, the same caveat as with active addresses also applies here: one address does not necessarily mean one user, so it should be thought of as a maximum number of holders. Contract addresses or various exchange deposit addresses (of which there are many) would be included in these figures. 

Similar to active addresses, the number of addresses with a balance of at least $10 also increased for most of the major cryptoassets over 2019, another positive sign for overall crypto adoption. All of the stablecoins in our sample increased considerably. Of the non-stablecoins, XTZ and LINK saw over 100% gains on the year. Only BSV, XRP, and ZEC saw decreases. BSV is particularly odd since it saw a large increase in active addresses of over 600%. 

BTC and ETH both have significantly more addresses with a balance of at least $10 than all other major cryptoassets. ETH has nearly 2x as many as any other asset (besides BTC) and BTC has almost 4x as many as ETH.

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Number of Addresses with Balance of At Least $1M

The number of addresses with a balance of at least $1M can be used as an approximate measure of the number of total “institutional” investors (or institutions), including exchanges, custodians, foundations, and others. 

BTC has a large lead over every other asset in institutions or institutional investors (keep in mind it also has the largest market cap by a large margin). On average, BTC finished the year with over 11,000 addresses with a balance of at least $1M, while ETH finished with over 1,800. No other asset finished with more than 700. In terms of growth however, LINK and USDT_ETH led the way posting 538% and 5817% growth respectively. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Active Supply Percentage, 30 Days

Active supply percentage, 30 days measures the percent of total supply (visible on ledger) that was transacted at least once in the trailing 30 days. Coins transacted more than once are only counted once. 

A decrease in active supply percentage may signal that an asset is being increasingly used as a store of value, while an increase could be a sign that an asset is being used more as a medium of exchange. However, these are just proxies. A decrease in active supply can also occur if an asset’s usage is generally declining. There are also other factors that could affect active supply, such as exchanges or foundation treasuries shuffling large amounts of supply between cold wallets that can result in large changes in activity.

Of the large cap assets, BTC decreased in percentage of supply active in the last 30 days from 14% to 9% while ETH decreased from 32% to 24%. In contrast, stablecoins showed large percentages of active supply ranging from 50-75% suggesting they are being used as intended, as mediums of exchange. 

Chart values are daily (end-of-day) values on a 7d moving average basis

Block Size, Bytes

Block size, bytes measures the total sum (in bytes) of all blocks added to a blockchain that day. This metric is only possible to measure for the public blockchains and therefore does not apply to ERC-20 tokens or other tokens built on top of public blockchains.

Increasing block sizes could indicate that a blockchain is seeing more usage overall (as transaction counts increase, demand for block space increases) or is seeing increasing usage in “costlier” transactions (such as complex contract transactions that take up more block space). However, increased block size could also be caused by a small number of users spamming the chain (particularly on low-fee blockchains) so it is important to look at block size increases on a case-by-case basis and consider other contextual clues. It’s also worth noting that if blocks are already mostly full as they are for some blockchains such as Bitcoin and Ethereum, there may be little space for additional increase unless block size limits are increased. 

Block size increased for most blockchains in our sample, meaning blockchains are becoming increasingly fuller as demand for block space increases. Notably, BSV block size increased by a huge amount: nearly 14,000%. This is likely because BSV is being used heavily for data storage, as opposed to monetary transactions (such as transfers of BSV coins), as we covered in SOTN Issue 8. BTC, ZEC, and Cardano (ADA) all saw decreases with ZEC seeing the largest at nearly 45%. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Economics

Table values are annual averages of daily values (1/1/2019 - 12/30/2019) 

Transaction Count

Transaction counts increased for most major assets over 2019. After USDT_ETH, which saw an incredible 59,303% increase, BSV saw the next largest increase in transaction counts (20,688%) with the majority (74%) being non-economic OP_RETURN transactions used to store data on-chain. Of the major assets, XRP, saw an average of nearly 1M transactions, largely due to a late surge towards the end of the year, as noted in SOTN Issue 28.

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Transfer Count

Transfers are transactions that include an exchange of the native blockchain cryptoasset. In other words, a transfer is any transaction where a cryptoasset is moved from one address to another. For protocols like Ethereum, only transfers of ETH are counted, not ERC-20 or other tokens. 

BTC and ETH led all assets in terms of annual average daily transfer count. BSV and USDT_ETH however saw the largest increases at 19,254% and 60,647%, respectively. 

Note that the XTZ active addresses line appears thicker than other assets because XTZ has staking payouts on a regular basis, which leads to regular variance in activity day-to-day. 

Note: ZEC payment and adjusted transfer value metrics do not take into account shielded transactions.

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Adjusted Transfer Value, USD

Transfer value is the sum value in USD of all native blockchain cryptoassets transferred over the course of a day. For protocols like Ethereum, only transfers of ETH are counted, not ERC-20 or other tokens. Raw transfer value can be relatively noisy. Some value transferred might be the result of change being sent back to the sender (on UTXO-based blockchains such as Bitcoin) or the result of exchanges shuffling single deposits between many addresses. We therefore created an “adjusted transfer value” metric which removes such noisy “non-economic” behavior.

BTC and ETH saw the largest annual average daily transfer value at $1.8B and $364M per day, respectively. USDT_ETH however had the largest growth posting a huge increase of over 60,000%. Many other assets saw declines in daily transfer value over 2019. Despite these declines, transfer value is highly variable day-to-day and few assets saw visible trend towards decline over the year with most remaining either flat or increasing. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Annual Issuance Percentage

Public blockchains have different methods for issuing and releasing new supply. For example, Bitcoin and Ethereum (and many others) issue new supply through block rewards. Each block, new supply is released and existing supply gets slightly diluted. Annual issuance percentage is calculated by taking the amount of new units of supply issued daily, extrapolated to one year (i.e., multiplied by 365), and divided by the current supply. Increasing issuance percentage signifies that supply dilution is increasing, while a decreasing issuance percentage means that dilution is decreasing. We measure issuance only for public blockchain native cryptoassets at the moment so ERC-20 or other assets are not included in our sample. 

2019 marked some notable declines in issuance with Litecoin (LTC) seeing a protocol-mandated halving of its issuance (as covered in SOTN Issue 30), ZEC seeing a decline from 47% to 32%, and ETH seeing a drop from 6.6% to 3.5%. BTC will see its issuance halve in 2020. Notably, no asset in this sample saw an increase in issuance. 

Chart values are daily (end-of-day) values on a 7d moving average basis

Median Fees, USD

Median fees are calculated by taking the median transaction fee (USD) over a day. Fees are only calculated for native blockchain cryptoassets and thus are not available for ERC-20 tokens or some other assets in our sample for which determining transaction fees is challenging. 

BTC and ETH are the only assets that had daily median transaction fees of over $.06 on average over the year. Most other assets saw fees below one penny on average over the year suggesting that the demand to transact for these networks is still so low (in relation to their capacity) that there is little need to pay more. 

Chart values are daily (end-of-day) values on a 7d moving average basis

Security and Health

Table values are annual averages of daily values (1/1/2019 - 12/30/2019) 

Hash Rate

Without connecting to all mining pools and miners directly it is impossible to determine the exact hash rate of the network. Thus, many data providers, including Coin Metrics, estimate the hash rate by looking at the mining difficulty on any given day and the number of blocks produced in that 24 hour period. 

Hash rate is the speed at which computations are being completed across all miners in the network. The unit of measurement varies depending on the protocol. It serves as an estimation of the amount of computing power devoted to securing the network. Since hash rate is only relevant for base blockchains, it cannot be computed for ERC-20 tokens or blockchains that do not use proof-of-work mining. 

Hash rate cannot be directly compared between protocols that use different hashing algorithms, like BTC and ETH. However it can be compared across protocols that use the same algorithm, like BTC, BCH, and BSV.

Read more about how we calculate hash rate in Weekly Feature #2 of SOTN Issue 19.

BTC is still the clear leader in terms of hash rate growth, growing by over 130% over 2019. BTC hash rate is orders of magnitude higher than BCH and BSV, as covered in our research piece “A Comparative Analysis of Bitcoin Forks.” LTC had a large increase in hash rate leading up to its halving; however, hash rate plummeted after, as covered in SOTN Issue 31. ETH also saw a decline in hash rate over the year perhaps due to upcoming plans to launch its proof-of-stake blockchain in 2020. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Total Fees, USD

Unlike median fees, total fees measure the sum USD value of all fees across all transactions over a day. Fees do not include new issuance (i.e., block rewards) and are therefore only a portion of the revenue that goes to miners.

BTC and ETH both have an enormous lead over all other assets in terms of total daily fees, with an annual average of $427K and $95K, respectively. No other asset in our sample had more than $1,200 in daily total fees on average over the year.

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Miner Revenue, USD

Miner revenue measures the sum USD value of all transaction fees plus newly issued supply (i.e., block rewards), both of which are paid to miners or other validators (such as staking validators). Miner revenue represents the incentives pool for miners of a blockchain. The more total revenue there is, the more money miners can potentially earn. Therefore total miner revenue is an important indicator for the long term health and security of a protocol and the industry that surrounds it. Miner revenue is only calculated for native public blockchain cryptoassets that utilize miners or staking validators and thus is not available for ERC-20 tokens or other blockchains that do not utilize mining or staking. 

As with total fees, BTC and ETH have a large lead over most other assets in terms of miner revenue. In 2019, BTC generated an average of $14.2M in revenue per day for miners while ETH generated an average of $2.6M. No other asset generated more than $900K per day on average. 

Chart values are annual percent change (1/1/2019 - 12/30/2019) on a 7d moving average basis

Fee to Revenue Percentage

The fee to revenue percentage is the percentage of miner revenue derived from fees, or in other words, fees divided by the miner revenue. In the long run, many blockchains’ block rewards will gradually decrease towards zero due to regularly scheduled block reward halvings or other decreasing issuance schedules. As block rewards decrease, fees begin to become a larger percentage of overall mining revenue and therefore become a more and more critical part of a chain’s long term sustainability and health (read more in SOTN Issue 24).

As noted above, BTC and ETH are the only two assets that currently have a meaningful amount of fees, and therefore have a large lead in terms of security and health going forward. ETH however comes far ahead in terms of the proportion of miner revenue earned by fees, finishing the year at 3.2% vs. 0.8% for BTC. 

Chart values are daily (end-of-day) values on a 7d moving average basis

Conclusion

2019 saw a rise in prices, decreases in volatility, and general increases in usage for the majority of major crypto assets. All of these are positive signals heading into 2020. We look forward to continuing to cover crypto in 2020, and providing more insights and analysis throughout the new year.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • SOTN will be back to its regular, non-holiday schedule starting next week

  • Coin Metrics is hiring! We recently opened up 6 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at info@coinmetrics.io.

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you'd like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics' State of the Network: Issue 31

Tuesday, December 24th, 2019

Weekly Feature

Revisiting the Block Reward Halving Theory 

by Kevin Lu and the Coin Metrics Team

The upcoming block reward halving for Bitcoin, anticipated in May 2020, has already given rise to intense discussion about its potential impact. Several theories have been advanced to study supply-side dynamics surrounding halvings and its eventual impact (or lack thereof) on cryptoasset prices. But up to this point, the short history and infrequent nature of block reward halvings have prevented us from drawing strong conclusions. 

In this article, we evaluate commonly proposed theories surrounding block reward halvings through the lens of the most recent instance: Litecoin’s halving that occurred in August 2019. 

History of Block Reward Halvings 

As a byproduct of mining, proof-of-work networks distribute new coins into circulation through block rewards. Block reward halvings are a common characteristic built into the protocol of Bitcoin-derivative proof-of-work coins as a means to gradually reduce the supply issuance. Other proof-of-work coins adjust issuance every block and/or do not have halving-induced supply shocks. 

Bitcoin has experienced two block reward halvings and Ethereum has similarly experienced two block reward reductions. While Bitcoin halvings are mandated by the protocol, Ethereum has a less transparent issuance model. There has, however, been broad consensus for the Ethereum block reward to trend downward over time and for eventual issuance to be maintained at a low level as the network shifts to a proof-of-stake model. 

The few historical instances of block reward reductions have been associated with increases in price in Bitcoin and Ethereum within the first 1.5 years of the halving. For this reason, an upcoming block reward reduction is often cited as a reason to be bullish about an asset’s future price appreciation. 

Litecoin was initially launched in October 2011 as a fork of Bitcoin. The Litecoin issuance model is similar to Bitcoin's except that blocks are produced every 2.5 minutes, and the total supply of Litecoin will eventually be capped at 84 million. Block rewards are halved every four years, assuming that blocks are produced on average every 2.5 minutes. 

Litecoin experienced its first block reward halving in August 2015 when the block reward halved from 50 LTC to 25 LTC. The second halving occurred in August 2019 when the block reward halved from 25 LTC to 12.5 LTC. 

Theory: Block Reward Halvings are Priced In 

There is intense discussion regarding whether block reward halvings are priced in. In one camp, proponents of the efficient market hypothesis (EMH) state that block reward halvings are mandated in the protocol and are well-known to all market participants far in advance. Since all information regarding halvings is already known, any impact that halvings have on supply-side dynamics or price should be fully reflected in the cryptoasset’s price. Furthermore, demand should not change since the issuance rate schedule and final supply are already known. Indeed, for Litecoin, the approximate dates of each of the halvings that have occurred (and all future halvings) were known when the protocol was launched in October 2011. 

Detractors of this theory state that not all market participants are aware of the existence or significance of halvings and will still act on this phenomenon when discussion increases as the halving date nears. While this may be true, this is not incompatible with the theory that halvings are priced in. The EMH does not require all market participants or even a majority of market participants to be aware of information for prices to fully reflect that information. In fact, all that is required is the existence of a small fraction of market participants who control enough capital and act upon this information to force prices to react. 

Detractors of this theory also point to empirical evidence which shows that historical halvings have been associated with positive returns, arguing that the historical halvings were not priced in, and the trend is likely to continue. This argument deserves further consideration. Here, we propose an alternative theory which attempts to reconcile the arguments made by both sides. 

On one hand, empirical evidence supports a narrow interpretation of the efficient market hypothesis -- at the instant that a halving occurs, there is no immediate reaction in the price, either up or down, as no new information has been revealed. On the other hand, halvings can still impact prices over a period of several months to years, not because new information is revealed, but because market participants understand the impact of a reduction in miner-led selling (discussed more fully below) and anticipate actions by other traders in a reflexive, game theory-like manner. 

Litecoin’s price performance this year supports the theory that market participants anticipate halvings and act on halvings by bidding prices up in advance. Among major cryptoassets, Litecoin experienced one of the strongest price appreciations this year, increasing in price by 350% between January 2019 and July 2019. Over the same time period, this performance was second only to Binance Coin and far outpaced the gains seen in Bitcoin, Ethereum, XRP, and Bitcoin Cash. 

While all information regarding halvings is widely known, the evidence suggests that market participants still act upon halvings in part because of a strong narrative that halvings are positive for prices. Even if no logical cause-and-effect relationship exists between halvings and prices, the narrative (or belief that others will act on this narrative) can cause a self-fulfilling increase in prices as market participants attempt to enter positions in advance of other market participants doing the same thing. 

In Litecoin’s case, this game theory-like “anticipation trade” caused prices to run up and sell-off in advance of the halving as market participants attempted to time their entries and exits while anticipating the actions of others. Poor performance of Litecoin’s price after the halving could be explained by a continuation of traders unwinding their positions, although Litecoin’s year-to-date performance is still among the strongest of the major cryptoassets. 

Theory: Reduction in Miner-Led Selling Pressure 

The protocols of major proof-of-work coins adjust the difficulty of the proof-of-work calculation regularly to ensure that blocks are produced at regular intervals. Mining represents a near perfectly competitive industry that constantly seeks a steady state where miner revenue is only slightly above miner costs. When the state is far from this equilibrium, miners will either enter or exit the industry until the equilibrium is achieved. 

Miners earn revenue in the form of native units of the cryptoasset they are mining, while their variable costs (primarily in the form of electricity) must be paid in fiat currency. This, combined with the fact that miners must, in the long-run, operate at a profitability level that is only slightly above breakeven, means that they represent the single largest cohort of natural, consistent sellers. According to this theory, miner-led selling pressure is likely significant, small perturbations in the amount they sell can have an impact on prices, and a halving of this selling flow may eventually have a large impact on prices. 

To illustrate, Litecoin’s annualized supply issuance since the halving has been running at around 4%. At current prices, this means that miner revenue denominated in U.S. dollar terms is roughly $100 million per year. Under the theory that miners must sell nearly all of their holdings for fiat, this is equivalent to nearly $300,000 in natural selling pressure every day over the course of an entire year. 

Immediately prior to the halving, these figures were doubled -- issuance was running at 8% and daily selling pressure was $600,000. Such a drastic reduction in compelled selling pressure should be supportive to prices going forward. Importantly, this reduction in selling flow occurs regardless of the degree to which the halving was priced in or anticipated by market participants. 

Detractors of this theory point to the relatively small amount of volume that can be attributed to miners compared to all trading volume that occurs within exchanges or on-chain. Indeed, compared to these much bigger figures, miners appear insignificant. Although data is not readily available on capital inflows and outflows into a cryptoasset, it is likely that the majority of trading that occurs within exchanges and on-chain do not represent a net inflow or outflow of fiat. Under this perspective, miner-led selling pressure may represent a large amount of net capital outflow of a cryptoasset. 

The Current State of Litecoin 

Although still one of the strongest performers this year, Litecoin’s performance after the halving has been quite negative, perhaps reflecting an unwinding of the “anticipation trade”. Any positive price pressure as a result of a halving of miner-led selling flow has yet to occur or has been overshadowed by the unwinding of the anticipation trade. 

The halving of the block reward combined with the decline in prices have caused a sharp decline in mining difficulty. Current difficulty is approaching two year lows and have already exceeded the lows during the depths of the market-wide sell-off in December 2018. 

Looking at the one-month change in mining difficulty reveals that after the halving, difficulty declined at the fastest pace ever. Litecoin mining is clearly in a state where a significant number of miners are operating with a loss and/or less cost-efficient miners are exiting the industry. 

Inventory management of miners is not a well-studied topic since access to this information is not available, but it stands to reason that each miner makes their own decision on how much of their block rewards to sell for fiat and when to sell it. Since miner variable costs are relatively constant in fiat terms, during periods of rising crypto prices, miners are required to sell less of their block rewards to cover their expenses. On the other hand, when crypto prices are falling, they are required to sell more. Under this theory, miners have a procyclical effect on the market, in that they further exacerbates price increases during periods of increase and vice versa. 

During periods of capitulation, miner-led selling flow is likely to be high. Miners may play games of chicken in which miners that are barely profitable are attempting to hold on, perhaps even willing to temporarily operate at a loss, until less cost-efficient miners exit the industry. Miners may even be willing to sell block rewards earned in prior periods that they kept on their balance sheet to be used in an attempt to outlast other miners. 

Although this has not yet occurred, Litecoin difficulty will likely eventually stabilize as all unprofitable miners exit the network. The culling of inefficient miners combined with the halving of the block reward should eventually result in a significant reduction in miner-led selling flow and could be supportive of prices going forward. 

Coin Metrics is actively researching miner flows by tracking the movement of block rewards from miners to other entities in the ecosystem. We hope to publish more information on this topic as our understanding grows. 

Current market value to realized value (MVRV), calculated as market capitalization divided by realized capitalization, is significantly below 1 and is approaching levels close to all-time lows. At current prices, most Litecoin holders are now underwater with values below their cost basis. Historically, low levels of MVRV for Bitcoin have marked good entry points and have accurately identified periods of undervaluation. 

Conclusion

Several theories have been advanced to explain the impact or lack of impact of block reward halvings and active debate continues over whether block reward halvings are priced in and whether reductions in miner-led selling are impactful to prices. The few historical instances of block reward halvings, including Litecoin’s recent halving this year, deserve continued study. Over the course of 2020, a number of major cryptoassets are scheduled to experience a block reward halving, including Bitcoin, Bitcoin Cash, Bitcoin Cash SV, and ZCash, all of which will provide additional opportunities to test the current set of halving-related theories. 

Network Data Insights

Summary Metrics

BTC showed some early signs of recovery this past week, after a mostly negative December. Although BTC market cap was still down week-over-week, BTC estimated hash rate grew by over 10%. ETH, LTC, and BCH hash rate, however, all dropped by at least 2.9%, with ETH experiencing the largest drop of 8.3%. This is a potential signal that BTC may be gaining even more ground on the major cryptoassets in the wake of the latest downturn. 

ETH, on the other hand, continues to slide, losing over 10% of market cap week-over-week. Despite the drop in market cap, ETH active addresses, transaction, and fees all increased week-over-week, which could be a sign that ETH usage is somewhat independent of market cap. 

Network Highlights

Bitfinex’s BTC supply has increased sharply over the last month, despite the decrease in BTC price. Bitfinex held 204,150 BTC on December 22nd, up from 154,996 BTC on November 22nd. 

BitMEX’s BTC supply has also been increasing over the last month, despite an email leak that exposed client email addresses. On November 1st, it was reported that BitMEX suffered a security breach that caused over 23,000 email addresses to be leaked. Since then, BitMEX’s BTC supply has increased from 246,937 to 255,741 back to near all-time highs.

Market Data Insights

This week, the market has staged a recovery off the lows experienced on December 18, although many assets are still down over the past week. Bitcoin (+5%) has been one of the few assets that increased in price in addition to TRON (+7%). Tezos (-13%) has continued to decline despite the market staging a recovery in the past few days. 

Ethereum Classic (+10%) is the strongest performing asset among this set. Huobi Token (+5%), Maker (+2%), and UNUS SED LEO (+1%) also sustained small gains for the week. 

CM Bletchley Indexes (CMBI) Insights

Crypto assets had a very volatile week, ending with mixed results across the market. For the first time in months, Bitcoin not only outperformed most of the market, but was one of few assets that returned positive weekly gains. This is reflected in the below charts where only the Bletchley 10 (~70% BTC) and Bletchley Total (~66% BTC) were positive performers. The negative performance of the even indexes, which lower the weight of BTC, are testament to the fact that most of the Bletchley 10’s and Total’s positive performance was due to BTC.

This pattern was a sustained phenomena during early 2019 when BTC rose from $4k to $14k with very few other crypto assets managing to keep up. It will be interesting to monitor this over the coming weeks to see if markets will repeat their early 2019 trend.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 6 new roles, including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at info@coinmetrics.io.

Subscribe and Past Issues

Coin Metrics’ State of the Network, is an unbiased, weekly view of the crypto market informed by our own network (on-chain) and market data.

If you'd like to get State of the Network in your inbox, please subscribe here. You can see previous issues of State of the Network here.

Check out the Coin Metrics Blog for more in depth research and analysis.

Coin Metrics' State of the Network: Issue 30

Tuesday, December 17, 2019

Weekly Feature

Ranking Crypto Assets by Auditability 

by Antoine Le Calvez and the Coin Metrics Team

In Medieval times, landed estates’ accounts were read out loud to a person charged by the local ruler to ensure that their steward had not swindled them. As the primary role of this person was to listen (audire in latin), they became known as auditors.

A parallel can be drawn between the genesis of auditing and crypto asset nodes that do not take part in that asset’s consensus; they primarily serve to listen to the peer-to-peer network and validate that everything is unfolding according to the protocol’s specification: they are auditing the network.

Coin Metrics takes this approach one step further: as well as running nodes for most major crypto assets, we also extract raw blockchain data from them to rebuild the asset’s ledger independently. This allows us to compute many of our metrics (for example, realized capitalization) but also to more deeply analyze each asset.

Our version of auditing a crypto asset is being able to rebuild its ledger (the mapping of who owns what) independently, for any point in time, using data provided by the asset’s protocol implementation and, using this reconstructed ledger, verify that its supply matches what it should be according to the protocol’s specification.

In this feature, we’ll dig into how we audit crypto assets, what difficulties can be encountered during this exercise and what can be learned from it. Finally, we’ll attempt a ranking of assets along two different dimensions of auditability: node operation and ledger reconstruction. Note that those rankings are arbitrary and that they reflect our subjective experience of working with each asset.

Crypto Assets Auditability Dimensions

Node Operation

The first step to audit a crypto asset is to synchronize a node that understands its protocol. The node is software that implements the asset’s protocol, connects to the peer-to-peer network, and downloads and verifies the blockchain. Depending on the asset, hardware and time requirements vary. For some assets, there are different node variants to choose from, either because parallel implementations of the same protocol exist, or there are various configurations possible depending on the user’s needs. 

In the case of an auditor, it’s better to use the configuration that will give access to the most data possible, sometimes referred to as an archive or full history node. Depending on what level of audit is needed (current or historical audit), a configuration that doesn’t store all historical data could suffice, for example, pruning mode in Bitcoin Core.

Synchronization

The first thing a crypto asset node does is synchronize itself with the current state of the network. Depending on the asset and configuration, this could involve downloading a current or recent snapshot (for example, downloading a recent Ethereum’s state trie using fast sync) or downloading the entire history of the block chain and replaying it in its entirety (like what Bitcoin does). While the former is much faster, the latter is better suited for auditing as it makes historical data available.

For some assets and node configuration, completing this process requires a lot of patience (and expensive hardware). As an example, synchronizing a full archive EOS node took more than one month and required a machine with terabytes of NVMe SSDs, some of the fastest storage available.

Finally, a handful of assets, most notably Ripple, require such huge amounts of storage (tens of TBs) that they are impractical to run and synchronize.

Normal Operation

Having a node synchronized with the rest of the network is only the first step of the audit process. The node also needs to stay synchronized in order to be able to audit the network on an ongoing basis. While this sounds easy to achieve, a lot of node software fails to stay synchronized and sometimes experiences catastrophic failures during normal operations.

An example would be that our EOS node needs to be shut down very carefully otherwise it risks corrupting its own database.

Code Audit

A major part of being able to audit an asset is being able to understand how it works. Since the implementation of each protocol lives in code, being able to read it is paramount to getting a deep understanding of the intricacies of each protocol. While some assets have deep, detailed specifications, they might differ ever so slightly from the actual implementation.

In that dimension, of the more than 35 unique nodes that Coin Metrics manages, one is unique: Binance Chain. It’s the only one whose source code is not available: only signed binaries are provided to would-be node maintainers.

Despite there being some documentation on Binance Chain’s protocol, it’s not detailed enough to be able to reconstruct its ledger using the data exported from the node.

Extracting Ledger Data

The last step before being able to reconstruct an asset’s ledger is to be able to extract the necessary data from the node. Few assets’ nodes offer the ability to directly obtain the latest (or historical) ledger; most of the time, it has to be rebuilt by replaying the asset’s history.

In order to do this, we need to be able to extract all the data required from the node. All nodes offer some form of API to access this data, with varying levels of user-friendliness, documentation, and completeness.

A key to easy auditability for an asset is to have as few ways as possible to credit or debit accounts. For example, Bitcoin only has 1 way to credit native units (the mining of an unspent output) and one way to debit native units (spending a previously unspent output). The more distinct things there are to track, the harder it gets. The more ways there are to credit/debit native units, the more likely that data for some is not easily accessible (an example would be some fees charged by the Binance Chain DEX).

Node Operation Ranking

We ranked full nodes in several tiers (A, B, C, and F) depending on their ease of synchronization, update, and maintenance. Here is our ranking for the top 10 assets by market cap (Coin Metrics doesn’t operate Ripple or Stellar nodes, but relies on the APIs provided by both Ripple and the Stellar Foundation).

Since historical ledger auditing for Ethereum requires a node with tracing and they take a long time to synchronize, it gets a B.

Omni gets a B as, even though it’s a modified Bitcoin Core and is therefore easy to run and sync, it has many different ways to credit and debit native units, each accessible through its own API endpoint requiring some effort to understand and put together.

Despite having a very clean accounting model for an asset of its complexity, EOS gets an F due to the complexity of extracting all the necessary data to run a complete audit. An archive node running with an extra plugin is required, documentation for which is scarce. Finally, the amount of data to sift through in order to get credits and debits of EOS is very large which makes it impractical.

Binance Chain gets an F for two linked reasons: it has a very complex fee schedule for its DEX and it’s closed-source which makes reverse engineering this schedule very hard. 

Ledger Reconstruction

Once the node is synchronized, running correctly and its data exported, the task of rebuilding its ledger can begin.

The way this is accomplished depends on the asset’s accounting model: UTXO-based (like Bitcoin and its derivatives) or account-based (Ethereum and many others). The ledger for UTXO based chains’ consists of a set of unspent transaction outputs (UTXO). Therefore, rebuilding the asset’s ledger consists of tracking which transaction outputs are unspent. For account based chains, the ledger is closer to a mapping of accounts to their balance. In order to rebuild it, auditors have to keep track of credits and debits for each account.

UTXO Sets

Tracking unspent outputs is done by replaying the block chain: each block creates new outputs and spends old ones. After having replayed the whole chain, the outputs remaining unspent make up the asset’s ledger. Summing up their value gives the asset’s supply.

As straightforward as it seems, there are still some nuances to keep in mind. We detailed some of Bitcoin’s supply idiosyncracies in a recent installment of this newsletter. For example, some special outputs (OP_RETURN) are not counted towards the supply; Bitcoin’s genesis block’s output doesn’t count either.

Account Ledgers

For account-based chains like Ethereum, we have to track credits and debits for each account on the chain. Given the complexity of some chains driven by the existence of smart contracts, this can get complicated very quickly. 

Another difference between UTXO and account-based protocols is that transactions in the former are more explicit about how they affect the ledger:

  • A UTXO transaction consists of two parts: which previously unspent outputs it spends and what new outputs it creates. UTXO transactions describe how they are going to change the asset’s ledger. On all UTXO protocols, only valid transactions are included in valid blocks. There cannot be partially applied UTXO transactions.

  • Account-based transactions, especially smart contract invocations, only describe the intent of the user, not its effects on the ledger. To be able to recover their impact on the ledger, nodes often need to be run with what is often called “tracing”. Tracing consists of recording exactly what each transaction’s impact on the ledger was. Non-tracing nodes just apply transactions without making detailed information available on a per-transaction basis. Furthermore, transactions can be included in a block without being completely executed.

For some assets, there are additional factors listed below to take into account.

Implicit Block Rewards

Most protocols include a reward for whoever (miner or staker) added a new block to the chain. The reward’s amount is the implementation of the asset’s monetary policy as this is how most assets generate new coins. Therefore, tracking this is essential to determine an asset’s supply.

In most UTXO assets, this amount is visible in each block, as the first transaction of every block encodes this reward being given to the miner. However, this is not always the case for account-based ones, most notably Ethereum, where blocks just encode which account should get the reward. The exercise of determining the reward’s amount is left to nodes and auditors.

As Ethereum block reward changed twice so far (5 ETH→3 ETH→2 ETH), auditors and nodes have to keep track at which blocks those changes happened.

Implicit Ledger Edits

While the block reward being implicit is only a minor inconvenience, there are other times where an asset’s ledger can change without those changes being made explicit by the transaction or blocks.

For example, following the DAO attack, Ethereum experienced a hard fork to return funds withdrawn from the DAO to another address not controlled by the person behind the unexpected DAO withdrawals. Those changes to the ledger are implemented in the code run by the nodes, not in a transaction nor in a block. Unfortunately for auditors, neither the block raw data nor the tracing data indicate that those changes occurred. The only way to capture those credits and debits is to find the hardcoded list of affected addresses and emulate what edits the code ran over the ledger.

This type of software-only changes to the ledger also recently happened with Tezos. In the making of the Babylon hard fork, someone realized that thousands of accounts would have to be recreated by users in order to access some of their funds: an operation that costs 0.257 XTZ. In order to avoid having thousands of users pay this fee, the hard fork was changed to credit affected accounts with a tiny amount of XTZ to “recreate” them at a lesser cost. Once again, auditors were out of luck as this subtle change was not documented anywhere.

A final example of how implicit ledger edits make auditing assets more complicated lies with ERC-20 tokens. ERC-20 is a standard interface for Ethereum smart contracts. It lists a few methods and events they should implement to maximize compatibility with existing wallet software and explorers. In practice, ERC-20 is just a standard and lacks strong guidance on the semantics of its events. Developers are free to stray from it, leaving auditors like Coin Metrics the hard task of piecing together the asset’s full transactional history. For example, token generation and burn events are often recorded using token-specific methods (if recorded at all).

Ledger Reconstruction Ranking

We’ve ranked each of the top 10 assets in several tiers (A, B, C, and F) depending on the ease of rebuilding their ledger for any point in time:

Ripple and Stellar are not graded as we do not reconstruct their ledger completely independently as we rely on APIs provided by third parties.

Bitcoin and its derivatives (Bitcoin Cash, Litecoin, BSV) receive an A as tracking their UTXO set is a simple task.

The Omni protocol, used by Tether to operate on the Bitcoin blockchain, receives a B because it has many different ways to move native units which makes it harder to track.

EOS also receives a B because its sheer scale (tens of millions of transfers per day) makes it unwieldy to audit.

For Ethereum, the current state of the tools we use don’t allow a full reconstruction of the ledger only using the data exposed by tracing, the changes made in the DAO hard fork have to be manually implemented. It therefore receives a C.

Finally, Binance Chain received an F because we could not rebuild Binance Chain’s ledger using our node’s data, due to the complexity of its DEX and the absence of source code to look up the details of its implementation.

Validating the Supply

Once the historical supply of an asset can be computed, it still has to be validated against what it should be to ensure it’s correct. This category doesn’t have a ranking as it’s binary: either we can validate the supply or we can’t due to being unable to reconstruct its ledger. There’s been no case of an asset for which we couldn’t determine what the expected supply should be.

A few assets’ nodes let users query what the actual supply is (most notably Bitcoin and its derivatives) which makes this task easy.

Example of fetching Bitcoin’s supply

For the other assets, most of the time, they have a straightforward issuance (or none at all). Given the formula that gives the expected supply at a given height and the supply we found rebuilding the ledger, we can verify whether there’s been any unexpected inflation. It’s possible to find a lower supply than the formula’s due to users or entities burning funds.

Some assets, due to their use of privacy features, sacrifice supply visibility for transactional privacy. One interesting example is Zcash which has the particularity of having both a visible part of its supply (so-called transparent supply) and a private part (so-called shielded supply). Auditors have perfect visibility into the makeup of the transparent ledger but can only have an estimation of the size of the private part. Movements in and out of the private supply can be tallied to estimate its size, but if there’s an inflation-causing bug happening inside fully private transactions, it is undetectable by auditors.

Conclusion

It’s important to note that a lot of the issues we encounter in auditing crypto assets lie with the nodes and tooling available to users, not with the protocol themselves. We hope that over time, they will improve to make auditing assets easier, and we are already starting to see this today. Coin Metrics may therefore revisit this exercise in the future. 

While this exercise of validating an asset’s supply independently may seem futile, it nonetheless led to several discoveries of hidden inflation.

Coin Metrics detected that Bitcoin Private supply had anomalies using these auditing techniques:

Stellar suffered an inflation bug visible through supply auditing that was later remediated by the Stellar Development Foundation burning some of its own supply. As a further argument to why this process matters, the total supply as reported by the Stellar blocks headers diverged from the actual supply of XLM obtained by summing up all the account’s balances.

These two examples once again highlight the relevance of one of the industry’s adages: do not trust, verify.

Network Data Insights

Summary Metrics

The major crypto assets continued to downslide over the past week. BTC and ETH market cap both fell by over 2.6% and realized cap dropped 0.2% and 0.6%, respectively.

ETH active addresses count, however, grew 21.3% week over week. This large increase is potentially related to Ethereum’s recent Istanbul hard fork.  ETH transfer and transaction count were also up over the past week, despite a large decrease in transfer value.

XRP transactions, however, continued to decline after a large surge in recent weeks. XRP active addresses dropped by over 13%, far more than the other four assets in our sample. 

Network Highlights

Bitcoin SV (BSV) transaction count hit new yearly highs this past week. However, as we reported back in SOTN Issue 8, a majority of BSV transactions are being used for data storage, and do not involve monetary transfers. At one point, over 90% of all BSV transactions were being initiated by WeatherSV, an app that records daily weather data onto the blockchain for a small fee. There is now another BSV app that is generating a large number of transactions: Preev, which allows users to write once-per-minute price updates for BTC-USD onto the BSV blockchain ledger.

The number of addresses with small balances of Tezos (XTZ) has been growing since early November. The following chart shows XTZ addresses with balance greater than X, where X ranges from 0.1 XTZ to 1K XTZ. 

On November 7th, Coinbase introduced Tezos staking, and added Tezos to Coinbase Earn, which allows users to earn up to $6 worth of XTZ by completing some lessons to learn how it works. There were a little over 82,000 addresses with at least 0.1 XTZ (worth about $0.16 at current prices) on November 6th. As of December 15th, there are over 107,000 addresses with at least 0.1 XTZ.

Market Data Insights

Crypto markets continued with a steady but moderate decline in prices over the past week, with a few noticeable exceptions. After consistently underperforming other major assets for the majority of this year, ZCash has achieved two consecutive weeks of positive price growth. 

ZCash has underperformed other major assets this year in part because of its high issuance rate. As a relatively young proof-of-work asset modeled off of Bitcoin’s issuance schedule, ZCash was launched in October 2016 with no premine and a block reward of 12.5 ZEC per block. ZCash has yet to experience a block reward halving and its annualized issuance rate is relatively high compared to other proof-of-work assets. 

Notably, ZCash annualized issuance rate has been declining rapidly as the constant block reward represents a smaller percentage of its total supply. Over the course of 2019, the annualized issuance rate has declined from 47% to 32%. By late 2020, the annualized issuance rate will further decline to 25% just prior to the block reward halving and will then decline to 12.5% immediately after the halving. These reductions in miner-led selling pressure should be broadly supportive to prices assuming that demand for ZCash remains constant. 

Other notable performers this week include ChainLink (+1%), Tezos (+5%), and Cosmos (+15%). All three assets are extending significant gains over the course of this year. 

CM Bletchley Indexes (CMBI) Insights

As the year comes to a close it is time to reflect back on where we have come from a year ago to put the current market performance into context. Despite the recent weakness in the market, crypto asset performance has been relatively strong over 2019 after an abysmal 2018. With renewed confidence in the market, it seems most of the attention has gone into larger assets, with Bitcoin close to finishing the year up over 80%, the Bletchley 10 (large cap) returning 52% over the year, the Bletchley 20 (mid cap) returning 28% and the Bletchley 40 (small cap) falling 40%. 

However, after a soft week for crypto asset markets that saw prices dwindle across the board, all Bletchley Indexes finished the week ~5% down. There was very little differentiation in performance between small, mid and large-cap assets as is evidenced by the below charts, demonstrating very little variance in weekly returns. 

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We have 6 roles posted including Blockchain Data Engineer and Data Quality and Operations Lead. Please check out our Careers page to view the openings.

As always, if you have any feedback or requests, don’t hesitate to reach out at info@coinmetrics.io.

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