Coin Metrics' State of the Network: Issue 13

Tuesday, August 20, 2019

Intro and Updates

Dear crypto data enthusiasts,

Welcome back to this week’s edition of Coin Metrics’ State of the Network, an unbiased, focused view of the crypto market informed by our own network (on-chain) and market data.

This week’s housekeeping items:

  • Coin Metrics was recently featured in the Wall Street Journal! Checkout the full article here.

  • Last week, we released a new research report about evaluating fork legitimacy. The long-form piece examines whether an exchange, index provider, investment manager, or any market participant should support a new fork or credit holders of the parent chain with units of the forked asset. Read the full report here.

  • Coin Metrics is hiring! We recently opened up 7 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.

Weekly Feature

Analyzing Wealth Distribution in Crypto

The distribution of wealth in crypto assets has been a recent topic of debate. The debate has centered around whether a lack of wealth distribution -- i.e., wealth centralization -- could prevent future adoption of crypto. 

While this is an important question to answer, before it can be answered, we must first ask how is wealth actually distributed in crypto? Is distribution unequal? How does it compare to other asset classes? And by what metrics can we measure this?

In this week’s feature, we’ll discuss how to define and measure wealth distribution, and look at some data for the top crypto assets. This will be the first of several pieces to look at wealth distribution data and Coin Metrics will continue to explore this topic in the future. 

To begin, it’s important to distinguish between wealth distribution and income distribution. Wealth distribution differs from income distribution in that it looks at the distribution of ownership of the assets in a society, rather than the current income of members of that society. In all state economies, wealth is significantly less equally distributed than income. 

According to The World Economic Forum (WEF) Inclusive Development Index 2018, “this problem has improved little in recent years, with wealth inequality rising in 49 economies." The table below highlights this discrepancy across the 5 most productive state economies and the most distributed (Iceland) and least distributed (Namibia) economies among the sample studied. In the United States, wealth is almost 2.3 times less equally distributed than income when measured by the Gini Coefficient. The Gini Coefficient is a statistical measure of distribution. The coefficient ranges from 0 (or 0%) to 1 (or 100%), with 0% representing perfect equality and 100% representing maximal inequality.


Table 1: Wealth and Income Distribution Across Select Countries in the WEF Inclusive Development Index 2018

Before we turn to crypto, there is another critical point worth making: "wealth" in the WEF Index report is defined as the value of all financial assets plus real assets (principally housing) owned by households, minus their liabilities. The Wealth Gini Index therefore measures the distribution of multiple assets and it measures distribution at the household, not individual, level. 

When making comparisons of such metrics to crypto or other asset classes, it is therefore important that we compare apples to apples. 

Measuring Wealth Distribution in Crypto Assets: The Trouble With Addresses

Because crypto assets are not state economies, and because we cannot get exact numbers on individuals or households participating in crypto networks, we i) cannot measure income distribution and ii) can only measure wealth distribution using proxies for individuals such as addresses (an address is the alphanumeric identifier of an account of the ledger of a crypto asset). This creates two problems:

  • Addresses can be owned by individuals and businesses (or other groups of individuals)

  • One entity can own multiple addresses

Addresses not only pertain to individuals but also to businesses and other groups. Complicating things further, because any one individual or group can own many addresses, determining the number of individuals represented across all addresses holding a crypto asset is impossible. On one hand, a single exchange address could represent millions of individual owners. On the other hand, one individual could own millions of addresses. 

Ultimately, this means that measuring the wealth distribution of a crypto asset via addresses is a unique exercise, one that should not be used to compare to traditional methods used for other asset classes. 

With that said, let’s look at some useful metrics for measuring wealth distribution in crypto. 

Wealth Gini Coefficient

The Wealth Gini Coefficient of crypto assets is often used as a means of highlighting the supposed inequality in crypto with many citing previous attempts such as this piece by Balaji S. Srinivasan. For a description of how Gini is calculated, please see Balaji’s piece. 

Calculating Wealth Gini across various crypto assets takes considerable effort. It is a metric that Coin Metrics is working to add to its arsenal. In the interim, it’s useful to reiterate a couple challenges with i) calculating this metric and ii) in using it to compare crypto to external networks such as state economies. 

First, is the choice of sampling unit. As described above, for state economies, the sampling unit of choice is often a household. For crypto assets, there is no way to measure individuals or households so we must work with addresses (and choosing which subset of addresses to sample is tricky). 

Not only does the sampling unit differ in crypto but here we are also measuring the distribution of a single asset, the crypto asset itself, and not of all of a household’s assets minus liabilities as we do when calculating Wealth Gini in state economies. It’s very likely that the distribution of a single asset in a state economy, such as real estate, is far less equally distributed than all assets combined, particularly when subtracting liabilities. 

Other Wealth Distribution Metrics

Beyond Wealth Gini, there are several other metrics that we can look at to give us insight into the distribution of crypto assets. Below is a snapshot from August 17, 2019 for the top 5 crypto assets. 

Table 2: Wealth Distribution of the Top 5 Crypto Assets by Market Capitalization

BTC, the oldest asset, is by far the most distributed by metrics such as the number of addresses with meaningful balance (defined as owning one in one-billionth of supply). However, Bitcoin addresses also have the highest mean/median address balance and Bitcoin boasts the most address USD millionaires. 

Aside from BCH (a recent but prominent BTC fork), ETH appears the next most distributed by these data despite being the youngest. Not only does it have a large number of addresses with meaningful balance but it has a low mean address balance. Comparing between different networks however isn’t straightforward. Ethereum’s gas fee mechanics tends to leave more dust behind (dust refers to balances smaller than the fee necessary to move them). This could make ETH appear more equally distributed by lowering mean account balances. On the other hand, Ethereum is also an account-based protocol. Compared with UTXO-based protocols, users of account-based protocols often re-use addresses which can make account-based protocols appear less equally distributed when using address-based metrics. 

Of this sample of assets, XRP appears the least equally distributed.

Keep in mind that many of the above metrics are influenced by the market capitalization of the asset. Since BTC has the highest market capitalization, it might appear to have higher wealth centralization. If we scale the non-BTC assets to the same market capitalization and multiply all metrics by this multiplier, an interesting picture emerges. We would however caution placing too much emphasis on this data since scaling in this way makes a number of assumptions that are unlikely to hold true (particularly for direct forks such as BCH). 

Table 3: Wealth Distribution of the Top 5 Crypto Assets by Market Capitalization Scaled to BTC’s Market Capitalization

Finally, an important consideration in the wealth distribution of an asset is time. This is clearly evidenced with BTC, the oldest asset, in the chart below. Taking the slopes of the trendline of these curves tell us the current rate of distribution. For example, using the slope of the trendline from chain launch, every new day we would expect 218 new addresses to hold at least 1 BTC. However, since the early days of distribution on the Bitcoin network are unlikely to represent distribution patterns today, taking a more recent slope might make more sense.  

Chart 1. The Number of Addresses With At Least X Native Units of BTC

Table 4: Slope of the Curve of BTC Distribution Bands

Below are distribution charts for the other five assets. 

Chart 2. The Number of Addresses With At Least X Native Units of XRP

Chart 3. The Number of Addresses With At Least X Native Units of ETH

Chart 4. The Number of Addresses With At Least X Native Units of BCH (From Fork Date)

Chart 5. The Number of Addresses With At Least X Native Units of LTC

To summarize, measuring the wealth distribution in crypto requires novel approaches. It requires using addresses which do not map perfectly to individuals or households and it measures wealth in only a single asset (not all household assets minus liabilities) so it is not directly comparable to traditional measures of wealth distribution of state economies. Coin Metrics will continue to publish more research on this topic in the months to come. 

Network Data Insights

Summary Metrics

It was another rocky week for the major crypto assets. After a brief surge, metrics dipped during the middle of the past week as Bitcoin fell back under $10,000. On average, BTC’s Market Cap fell by over 10% over the last week. ETH, XRP, and LTC market cap also all fell by at least 10% as well. Realized cap, however, remained relatively stable for all five metrics.

Transfer count, adjusted transfer value, and daily fees were also down across the board. LTX and XRP were both hit particularly hard; XRP’s adjusted transfer value fell by 31.5%, and LTC’s daily fees fell by 39.6%.

LTC’s hash rate also dropped significantly, down 11.3% from the previous week. BTC’s hash rate also fell (4.6%) while ETH’s stayed relatively stable. BCH’s hash rate, however, increased over the past week, rising by 5.7%.

Network Highlights

LTC’s hash rate has continued to fall after its recent block reward halving. Hash rate has dropped from 426 TH/s on August 5th (which was the day of the halving) to 317 TH/s as of August 17th.

BTC’s all-time aggregate mining revenue is on pace to reach $14 billion by the end of the week. As of August 17th, BTC has generated over $13,918,000,000 of total mining revenue.

The number of addresses that hold any balance of USDT (Omni) fell precipitously over the past week, as USDT users continue to shift over to the Ethereum version of the protocol.

Market Data Insights

Short-term Correlation Remains High

Prices of major crypto assets declined modestly over the past week. Correlation over short-time periods remains high with almost all crypto assets moving in lockstep when examined intraday or over a period of a few days. 

An examination of the three largest crypto assets more clearly illustrates the high intraday correlation. When examined over this time period, crypto assets tend to trade as a single asset.

Despite High Correlation, Dispersion of Returns is Large

The high correlation among assets obscures large dispersion of returns when examined over moderate timescales. Despite all asset prices having near identical directional reactions in response to systematic events that affect the asset class as a whole, over moderate timescales asset-specific fundamentals do matter. 

The high correlation with large dispersion of returns indicates that a long-short strategy can be effective expressing market views. For certain assets, it may be easier to determine which ones are becoming fundamentally stronger or weaker rather than attempt to anticipate the direction of the asset class as a whole which is vulnerable to external event-driven shocks that are unpredictable. 

For example, a long Bitcoin, short ZCash position would have returned +31 percent over the past month and a long Bitcoin, short TRON position would have returned +38 percent. Even adjusting for high cost of borrowing and trading costs, there long-short trades can be highly profitable. 

Volatility Remains Elevated 

Volatility for many assets remains elevated compared to recent lows made in early 2019. Despite the safe haven narrative for Bitcoin, it’s volatility is similar to other major crypto assets. The asset class as a whole has experienced realized volatility of almost a magnitude higher than traditional asset classes. The high volatility combined with large dispersion of returns suggests that opportunities for actively-managed long-short strategies remain high. 

CM Bletchley Indexes (CMBI) Insights

All CMBI indexes fell sharply this week after a crypto asset market wide correction. As is evident through the returns of the Bletchley Indexes, this week’s correction was uniform across the large cap (Bletchley 10), mid cap (Bletchley 20) and small cap (Bletchley 40) crypto assets.

This is a very interesting result given the recent trend over the last three months. Over that period, in a positive week, Bitcoin (and as a result the Bletchley 10) has increased more than the rest of the Indexes. In a negative week, Bitcoin (and as a result the Bletchley 10) has either slightly increased or fallen less than the rest of the Indexes. This week that trend broke with mid cap and small cap assets performing better than large cap assets.

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Coin Metrics' State of the Network: Issue 12

Tuesday, August 13, 2019

Intro and Updates

Dear crypto data enthusiasts,

Welcome back to this week’s edition of Coin Metrics’ State of the Network, an unbiased, focused view of the crypto market informed by our own network (on-chain) and market data.

This week’s housekeeping items:

  • Coin Metrics is hiring! We recently opened up 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.

Weekly Feature

Bitcoin Shows Potential as A Unique Safe Haven Asset

Bitcoin was born as a response to a deep, global recession caused by a financial system driven to the brink of collapse. Afterwards, central banks around the world responded with unprecedented and unconventional monetary policy. Amongst questions about its sustainability, Bitcoin got off to a slow start – in 2009, there were several days when less than one Bitcoin was transacted. But Bitcoin was able to survive in its early years partially because of the extreme macroeconomic environment that existed during the time. 

Macroeconomic conditions were supportive of Bitcoin’s growth for several years after its creation. The Fed alone initiated three rounds of quantitative easing between 2008 and 2013. Such extreme monetary policy decisions combined with the willingness of governments to bailout critical financial institutions led many to question the sustainability of such policies, creating many ideological-converts to Bitcoin in the process.

For the past several years, the world has enjoyed relative stability with moderate growth and the longest U.S. economic expansion in history. Thus, most recently, Bitcoin and other cryptoassets have grown without the supportive macroeconomic environment in which they were born in.

Recent developments present a radical shift in the macroeconomic and geopolitical environment. Faced with some softness in the latest macroeconomic indicators, widespread inversion of most developed world economy yield curves, negative nominal interest rates, a persistent inability to achieve central bank inflation targets, falling inflation expectations by market participants, and the possibility of a full-blown U.S.-China trade war, the Fed is once again leading the way in easing monetary policy. In the recent meetings of the Federal Open Market Committee, it is clear that the Fed is growing increasingly concerned about the potential impact of a negative shock to the economy and are willing to consider “insurance-type” interest rate cuts to sustain the current economic expansion.

Other central banks around the world have responded similarly. The ECB, although not yet cutting key interest rates, has adjusted its forward guidance to indicate more monetary easing. The PBoC recently has indicated its willingness to allow the yuan to float above the psychologically-important 7 level against the dollar (which they have defended in the past) to blunt the negative impact of additional U.S.-imposed tariffs. And a trio of emerging market central banks in New Zealand, India, and Thailand surprised market participants by announcing larger than expected rate cuts. 

Bitcoin has not been immune from the impact of this dramatic pivot – it too has risen in concert with the decline in global yields and rise in gold. Bitcoin’s intrinsic qualities indicate that it could effectively serve as a safe haven asset – particularly its decentralized nature making it immune to the control of and the policy errors of any centralized institution, as well as its high stock-to-flow ratio. Such qualities are important for something to serve as hard money. Analyzed under this lens, it shares many qualities with gold, and it is theoretically sound and logical to make the comparison between Bitcoin and gold.

This theory, combined with a look at the year-to-date price action, has breathed new life in the Bitcoin as a safe haven narrative. Indeed, the decline in real interest rates and increased concerns of geopolitical instability have driven gold to six-year highs and, as the narrative goes, has also driven Bitcoin to steeply recover from its lows.

Looking at a plot of the prices of Bitcoin and gold can easily lead to the conclusion that there is some positive relationship. Correlation coefficients, a summary statistic that is simple to interpret and calculate, is commonly used to provide an objective measure of the linear relationship between two timeseries. Despite the widespread use of correlation and its ease of interpretation, it is prone to misuse. Some analysts mistakenly calculate correlation using the prices (or level) and not the returns (or changes) of the two timeseries. Such an analysis can lead to misleading conclusions. Our analysis uses daily returns to calculate an economically-meaningful correlation coefficient.

The actual data provides only moderate support for the safe haven narrative. An analysis of a 90-day rolling correlation indicates that the Bitcoin and gold return has historically been uncorrelated with values oscillating around zero. Interestingly, the correlation has been steadily increasing since the beginning of this year as theory would expect. Current correlation is +0.20 – high relative to its historical range and increasing, but still low on an absolute scale where correlation coefficients can range from -1.0 to + 1.0.

Such a result should cause market participants to critically examine the safe haven narrative and be open-minded to the possibility that the relationship between Bitcoin and gold is spurious. Although backed by strong theory and the presence of compelling evidence that Bitcoin and gold both respond similarly to specific geopolitical events, a proper correlation analysis suggests that the relationship between the two is weak.

How can we reconcile these empirical results with the prevailing narrative? Perhaps Bitcoin has been rising in concert in gold not because they both respond similarly to the same macroeconomic and geopolitical factors but because Bitcoin has already experienced an 85 percent drawdown (historically the bottom of previous cycles) in combination with Bitcoin-specific factors like the news of Facebook launching its own cryptocurrency and continued institutional interest.

Still, this explanation does not fully explain the entire range of observations. Certain specific geopolitical events, not priced in by market participants, have caused strong intra-day movements in both Bitcoin and gold. Some of the most compelling of these events include Donald Trump’s presidential election, the Brexit referendum, and most recently the depreciation of the yuan in response to growing U.S.-China trade tensions. Such events suggest that the relationship between Bitcoin and gold is market regime dependent.

Under normal times, gold is responsive to standard macroeconomic variables, particularly changes in real yields. Bitcoin, an asset still in the process of maturing into a full-fledged asset class, is unresponsive to macroeconomic data. This explains the typically low levels of Bitcoin-gold correlation that oscillates around zero.

During times of heightened geopolitical risk, the desire for the stability of haven assets takes center stage over the macroeconomic situation. Under such circumstances, the intrinsic qualities of both Bitcoin and gold attract capital and can experience short-lived periods of high correlation.

Examining the Bitcoin-gold rolling correlation over a shorter time period like 30-days lends evidence to this narrative. Thus far, geopolitical tensions are rising but contained, and any flare up has been short-lived. A shorter rolling correlation window is more responsive to these short-lived events. Indeed, the current 30-day rolling correlation is +0.49, high relative to its historical range and also on an absolute basis. This trailing 30-day periods has been characterized by the highest escalation of U.S.-China trade war tensions thus far and suggests that Bitcoin serves as a unique safe haven asset – unresponsive to macroeconomic surprises but reactive to geopolitical tensions.

Bitcoin shows qualities of a unique safe haven asset, able to hedge against true black swan-type events where centralized institutions fail or commit policy errors while simultaneously being unresponsive to normal macroeconomic surprises. Bitcoin’s unique hedging capabilities combined with its volatility (almost a magnitude higher than traditional financial assets) makes it extremely desirable from a portfolio construction perspective, particularly portfolios that tend to volatility-weight asset classes.

The world is taking a decisive step towards a macroeconomic environment and geopolitical climate that is more similar to conditions that were present at Bitcoin’s genesis – low interest rates, unconventional monetary policy, and rising geopolitical tensions. This shift should be supportive of Bitcoin’s price in the long-run. Moreover, the probability of some severe event has risen sharply – driven either by some policy error in a major developed world economy, the ineffectiveness of current monetary policy tools to address slowing economic growth, unexpected election outcomes, social unrest, or sovereign debt defaults and wars at the extreme. Most troubling is that the undercurrent of social tensions is occuring in a world where macroeconomic conditions and asset prices are quite good. Under a global recession, these social tensions should increase in intensity and could lead to a watershed moment in Bitcoin’s status as a safe haven asset.

Network Data Insights

Summary Metrics

On August 5th, LTC’s block reward halved from 25 LTC to 12.5 LTC. Since then, LTC’s market cap and realized cap have both declined; LTC’s market cap is down 4.7% week over week, while BTC’s market cap is up 13.9% over the same period. 

LTC mining revenue is down 54.3% over the previous week, due to the decrease in issuance per block. This sudden drop in total mining revenue will force many inefficient miners out of the market, unless they are able to adapt and quickly cut costs. LTC’s hash rate fell by over 12% from the previous week which signals that miners are already starting to leave the network. 

LTC transfers and active addresses, on the other hand, both grew by over 65% since last week. Additionally, LTC’s adjusted transfer value is up over 32%, while BTC’s adjusted transfer value is up only 1.2%. 

BTC’s average daily fees also shot up by over 44%, even though transactions and transfers stayed relatively flat. BTC and ETH hash rate both rose, in contrast to LTC’s hash rate drop.

Network Highlights

The number of addresses owning at least 1 billionth of Bitcoin’s supply is at an ATH. At current prices, only addresses owning >$200 in BTC are counted towards this metric.

LTC’s hash rate began to drop after the block reward halving on August 5th, and bottomed out at 358 TH/s on August 7th. However, it began to rebound after the 7th, and climbed back to 413 TH/s by August 10th.

The number of addresses that held any LEO balance (on Ethereum) plateaued over the last month. On August 10th, there were 1,789 addresses with any balance, up by only 79 addresses (1,710 total) on July 10th. 

Market Data Insights

Bitcoin is up over 80% over the past year, outperforming almost all other crypto assets. Although many market participants track the value of smaller assets in prices quoted against the U.S. dollar, occasionally it is useful to view prices quoted against Bitcoin. Bitcoin-quoted markets are not only the major market for many of the smaller assets, it also represents the foregone appreciation of holding non-Bitcoin assets and not holding Bitcoin. 

The following chart shows indexes prices denominated in Bitcoin over the past year. Among the major assets that Coin Metrics tracks, only Binance Coin has outperformed Bitcoin by 44%. All other major assets are down significantly in Bitcoin terms.  

Smaller assets have even steeper declines. Such declines are similar in magnitude to the U.S. dollar denominated declines experienced in the depths of crypto winter. Smaller assets have been doubly hit -- declining sharply on the way down and also appreciating less as the overall market (represented by Bitcoin) has recovered. 

CM Bletchley Indexes (CMBI) Insights

Bitcoin dominance, a measure of Bitcoin’s market cap relative to the total crypto assets marketcap, has been increasing significantly since April. The last 3 months have seen Bitcoin’s dominance increase from 50% to 70%, a level that has not been witnessed since April 2017. To add some context to this, the last time Bitcoin commanded a 70% market dominance the price of Bitcoin was ~$1,200 and the price of Ether was ~$20. 

As can be concluded from the weekly performance of the Bletchley Indexes, low cap crypto assets have experienced the biggest drawdowns recently. Not only have they experienced negative USD price action, but since Bitcoin finished the week up 4%, their price in Bitcoin terms has depreciated significantly. 

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

Coin Metrics' State of the Network: Issue 11

Tuesday, August 6, 2019

Intro and Updates

Dear crypto data enthusiasts,

Welcome back to this week’s edition of Coin Metrics’ State of the Network, an unbiased, focused view of the crypto market informed by our own network (on-chain) and market data.

This week’s housekeeping items:

  • Coin Metrics is pleased to announce the launch of block-by-block data for its popular institutional network data product, CM Network Data Pro. This Real-Time Block-by-Block feed features 83 metrics aggregated across every block. Metrics include transactions, transfers, active addresses, fees and miner revenue, on-chain exchange flows, and more. Please reach out to Coin Metrics (info@coinmetrics.io) for more information on the CM Network Data products.

  • Coin Metrics is hiring! 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.

Weekly Feature

A Look Back at the Last Year of ETH On-Chain Data

Last week, Ethereum (ETH) celebrated its 4th birthday. In honor of the occasion, we looked back at the last 365 days of on-chain data for ETH and some of the biggest ERC-20 tokens. 

After a wild third year in which ETH price climbed to a peak of just over $1,400 USD, ETH came back down to earth over the past year. Starting at a realized cap of over $42 billion in August 2018, ETH’s realized cap fell to $28.5 billion as of July 30th, 2019. However, ETH’s realized cap began to stabilize and increase again in late May 2019. 

Realized cap is calculated by valuing each unit of supply at the price it last moved. Realized cap can be thought of as the cost basis for the average holder:

We also looked at the realized market cap for ten of the largest ERC-20 tokens: Basic Attention Token (BAT), Dai (DAI), FunFair (FUN), Gnosis (GNO), Golem (GNT), Decentraland (MANA), Maker (MKR), OmiseGO (OMG), Augur (REP), and 0x (ZRX).

Similar to ETH, realized cap fell for most of these ERC-20 tokens over the past year. MKR and DAI, however, both rose. MKR’s realized cap grew to over $608 million on July 30th, 2019, up from $479 million twelve months earlier.

The following chart shows each ERC-20’s daily average market cap plotted against its daily average realized cap (averaged from 7/31/2018 to 7/30/2019). This shows the tokens compared against each other on an absolute basis, while the above charts are scaled to each particular asset (i.e. each subchart has its own y-axis scale). 

OMG has a high realized cap relative to its market cap. However, OMG also had a relatively large airdrop in September 2017, which may skew some of its metrics.

Despite the drop in realized cap, the number of ETH addresses that held any balance (i.e. greater than zero) grew steadily over the past year. The below chart shows the daily count of ETH addresses that closed the day with a balance above zero. As of July 30th, 2019, ETH had over 28.8 million addresses with a balance. 

Addresses with balance also grew for all of the ERC-20s over the past year. DAI addresses with balance have been growing particularly quickly, rising from under 4,600 to over 63,000 over the past year. BAT addresses with balance also grew significantly, going from under 67,000 on July 31st, 2018 to over 175,000 by July 30th, 2019. OMG’s addresses with balance, on the other hand, plateaued almost a year ago.  

The below chart shows each ERC-20’s daily average number of addresses with a balance plotted against its daily average number of unique active addresses (daily average from 7/31/2018 to 7/30/2019). BAT has an average of 99,128 addresses with balance, and an average of 1,496 active addresses a day. OMG has about 649,000 addresses with balance, but an average of only 929 daily active addresses.

ETH adjusted transfer value has fluctuated with price over the past year, staying mostly between $250 million and $750 million per day.

DAI is increasingly becoming the dominant ERC-20 for transfers. DAI’s daily adjusted transfer value has been picking up steam since April 2018.

The below chart shows each ERC-20’s daily average adjusted transfer value plotted against its daily average transaction count (daily average from 7/31/2018 to 7/30/2019). DAI, the only stablecoin out of the tokens we analyzed, is way ahead of any of the other ERC-20’s, with an average of over $25 million in adjusted transfer value a day. DAI also has a significantly higher transaction count than the rest of the tokens, which indicates that users are relying on DAI for transfers much more than the less stable tokens.

Network Data Insights

Summary Metrics

On-chain activity rebounded over the past week. BTC led the way in most of the major metrics, with a 5% gain in market cap and 2% gain in realized cap. BCH also had a relatively strong week, gaining 6% in market cap.

Adjusted transfer value rose across the board, led once again by BTC at 24%, with XRP in close second at 22%. ETH and LTC’s adjusted transfer value also rose, but less dramatically, increasing by 11% and 6%, respectively.

Network Highlights

BTC’s realized cap continues to break all-time highs. On August 4th, the BTC realized cap reached over $97.2 billion.

While realized cap has been rising, BTC’s median fee has been falling. The median BTC fee dropped to under $0.16 on August 4th, which is the lowest it has been since late March.

Market Data Insights

Empirical Data Supporting the Safe Haven Narrative is Mixed

Over the past several months, global markets have begun pricing in increasingly higher levels of geopolitical risk (primarily driven by flare ups of U.S.-China trade tensions but also driven by increased risk of European Union fragmentation, and increased likelihood of disruption in shipping in the Persian Gulf). These geopolitical events have been occurring against a backdrop of slowing global growth and yield curve inversions. Additionally, inflation measures coming in consistently below central bank price stability targets have put pressure on the world's major central banks to initiate easier monetary policy in order to uphold their mandates and sustain the current economic expansion. 

Under this macroeconomic environment, Bitcoin has experienced strong gains this year which has coincided with similarly strong gains in classic safe haven assets -- chief among them gold, but also U.S. sovereign bonds, the Swiss franc, and the Japanese yen. This relationship has breathed new life in the narrative that Bitcoin can serve as a haven asset. 

Testing this theory using empirical data is difficult because of the number of confounding variables at play that can affect price. In this week's State of the Network, we examine the price impact and trading activity surrounding the previous 16 meetings of the Federal Open Market Committee (FOMC). 

The Fed holds eight regularly scheduled meetings each year in which a statement describing their policy decision is released, sometimes held concurrently with a press conference in which reporters can ask questions to the Fed Chairman. Such events are interesting because they are scheduled far in advance, widely monitored and anticipated by market participants, and often contain new macroeconomic information that affect the prices of nearly all assets. Indeed, it is common to observe an immediate reaction in major asset prices (e.g. equities, bond yields, gold) precisely at the moment that the FOMC statement is released at 14:00 EST. 

An examination of Bitcoin’s price to Fed meetings shows that, with a few exceptions, Bitcoin is unresponsive to such macroeconomic surprises. The chart below presents Bitcoin’s price indexed to the time of the publication of the FOMC’s statement, twelve hours before and twelve hours after the event. Even allowing for a delayed reaction in Bitcoin’s price due to market inefficiency, price reaction is generally quite muted in contrast to traditional financial assets, including haven assets that Bitcoin is often compared to. 

A lot of attention was given to the most recent Fed meeting that concluded on July 31 because this was the first time in Bitcoin’s history that the Fed cut interest rates. Despite the historical significance of this event, virtually no price reaction was observed. However, beyond some comments that indicate that the Fed is slightly less dovish than expected, little new information was released in this meeting as this cut was widely telegraphed in advance and priced in. 

The most impactful Fed meeting of this year is likely the one that concluded on March 20 in which the Fed made a dramatic shift in their forward guidance -- a shift from monetary policy tightening to loosening, combined with the publication of projections that reduced this year’s anticipated interest rate increases from two to zero. In response to this meeting, there were large movements in asset classes with U.S. sovereign bonds rallying and the U.S. dollar declining. Despite this somewhat unexpected dovish pivot by the Fed, Bitcoin price was unresponsive. 

Bitcoin’s response to Fed meetings in 2017 and 2018 are also quite muted, although slightly larger compared to recent meetings due to the higher volatility that existed during those periods.

Examining trading volume surrounding the conclusion of Fed meetings reveals a similar picture. With a few exceptions, there is no widespread evidence that market participants adjust their Bitcoin positions in the face of new macroeconomic information. 

However, there was a burst in trading activity surrounding the Fed meeting on May 1st of this year with a small but concurrent movement in price. Interestingly, there was also evidence of moderately increased trading activity precisely at the moment of the conclusion of the most recent Fed meeting on July 31st. If this type of reaction is sustained in future Fed meetings, this would represent a milestone in Bitcoin’s development as an asset class. In subsequent issues, Coin Metrics will continue to examine Bitcoin’s reaction to critical geopolitical events and macroeconomic surprises, including this week’s Chinese yuan devaluation. The yuan devaluation and the US Treasury's subsequent labeling of Chinese as a currency manipulator happened too late in the week to cover in this week’s issue, but we plan to cover this in depth next week.

CM Bletchley Indexes (CMBI) Insights

Weekly performance of Bletchley Indexes indicate that the large cap crypto assets performed the best this week, once again led by Bitcoin.

However, looking at the monthly performance of indexes, the market experienced a cool-down in July after 3 impressive months of positive gains. Most interestingly, the low cap assets sold off hardest over the period. 

In recent months, Bitcoin has been more volatile and has had larger returns during uptrends. But during downtrends small cap assets are more volatile and experienced large losses. This trend has not been common over the last two years.

During the August rebalance there were a few changes to the Bletchley Indexes. The most surprising result was Decred falling out of the Bletchley 20 due to failing an eligibility criteria regarding minimum monthly trade volumes. Below is a summary of all of the changes:

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Coin Metrics' State of the Network: Issue 10

Tuesday, July 30, 2019

Intro and Updates

Dear crypto data enthusiasts,

Welcome back to this week’s edition of Coin Metrics’ State of the Network, an unbiased, focused view of the crypto market informed by our own network (on-chain) and market data.

This week’s housekeeping items:

  • We recently released an in-depth research report on the major Bitcoin forks (BCH and BSV). Read the full report here

  • Coin Metrics is hiring! 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.

Weekly Feature

Analyzing BitMEX Net Flow Since Investigation Announcement

On July 19th, Bloomberg reported that the CFTC is conducting a probe on BitMEX. Since then, BitMEX has had an aggregate net outflow of over $145,000,000. But after a large outflow on the 19th, the net flow (i.e. the net amount sent and withdrawn) appears to have stabilized. The net flow on July 27th and 28th were $9,019,262 and -$2,131,269, respectively. 

The following chart shows the daily net flow (i.e. the net amount sent and withdrawn) from BitMEX in USD since July 19th:

On July 19th, over $67,000,000 was transferred out of BitMEX. This was BitMEX’s largest daily outflow (i.e. daily withdrawal) of 2019, as seen in the below chart (July 19th is marked in red). 

However, after the 19th, BitMEX’s daily outflow returned to relatively normal levels. About $12,500,000 was withdrawn from BitMEX on July 28th:

BitMEX daily inflow (i.e. amount sent to the exchange) has decreased slightly since July 19th, which is marked in red below. Daily inflow for July 27th and July 28th was $18,283,823 and $10,436,451, respectively, compared to $22,981,818 on July 19th:

BitMEX has had the largest aggregate net outflow since July 19th ($145,000,000) out of all the exchanges we track. Bitfinex came in second, with a net outflow of $71,247,801 over that same period:

BitMEX holds a little more than 171,000 BTC as of July 28th, down from a peak of 245,964.85 on March 4th, 2019:

Network Data Insights

Summary Metrics

After another market retreat, network data metrics were mostly down over the past week. 

Adjusted transfer value is down in all five of the biggest crypto assets. Leading the way, XRP’s adjusted transfer value is down 55% from last week. 

Active addresses also fell, down 12% for both XRP and LTC, and 18% for BCH. BTC and ETH’s daily active addresses also declined, but not as severely. BTC active addresses dropped 5% from last week, while ETH dropped 3%.

Despite a drop in most other metrics, BTC hash rate and mining revenue continue to hold steady. Mining revenue grew by 1%, to a daily average of $19.4M, while hash rate grew 7% over the past week. 

Network Highlights

On July 26th, Coinbase added a new lesson to their “Earn” education platform that allowed users to earn up to $14 worth of DAI. Since then, DAI user activity has grown dramatically. On July 28th, there were 52,575 addresses that held some DAI balance, compared to 38,450 on July 25th:

Bitcoin is closing in on one billion dollars worth of cumulative transaction fees. As of July 28th, BTC has $955,797,817 of cumulative fees:

Market Data Insights

An Examination of Market Efficiency in TRON

Justin Sun, the founder of the cryptocurrency platform TRON, has been making headlines over the past week for cancelling a scheduled lunch with Warren Buffet. This sequence of events allows for a contemporary case study of market efficiency in cryptocurrency markets in which a large price decline was observed in TRON, an asset with intermediate levels of volume and liquidity. 

Moreover, news was released through the various mediums and languages, including traditional financial media sources and social media channels, with varying levels of clarity. How fast are market-moving announcements priced in by market participants?

This study examines three events that occurred between July 22 and July 24 in which TRON experienced a peak-to-trough decline of 23 percent:

  1. At 2019-07-22 21:28:00 UTC, the TRON Foundation Twitter account announces the postponement of Justin Sun’s lunch with Warren Buffet after Justin Sun falls ill with kidney stones. In the subsequent minutes, Bloomberg would write an article summarizing the contents of the tweet at 21:35:00, Justin Sun would announce on Weibo to his 1.2 million followers that he was canceling the lunch with Warren Buffet at 21:49:00, and Dovey Wan would tweet an English translation of Justin Sun’s announcement at 22:39:00.

  2. At 2019-07-23 14:45:00 UTC, Beijing-based Caixin first reports that Justin Sun is under border control and unable to leave China. This article would be syndicated to many other Chinese media publications over the next fifteen minutes.

  3. At 2019-07-23 17:45:00 UTC, Justin Sun tweets a picture of himself timestamped with a TRON blockchain hash in front of San Francisco’s Bay Bridge, proving to his followers that he is residing abroad. Approximately 10 minutes later, he livestreams himself with the Bay Bridge in the background.

In each case, the market reacts relatively swiftly to each announcement, regardless of the medium and language of announcement. Major markets in TRON traded in a very tight spread during this period of price discovery. This is empirical evidence that cryptocurrency markets have reached a level of maturity where market participants are able to efficiently and swiftly price in unexpected and material events.

A closer look at each of the three events reveals the limitations of the current state of market efficiency, however. Below we examine TRON’s intraday price two hours before and two hours after each event. The initial announcement of Justin Sun falling ill with kidney stones and the postponement of the lunch with Warren Buffet was not immediately acted on by market participants. Price movement in the initial hour of publication was muted, despite an article by Bloomberg and a post by Justin Sun. In fact, the price did not start to violently react until nearly an hour after publication.

As events unfolded, market efficiency increased due to widespread reporting by media sources and focused trader attention. An article published by Beijing-based Caixin in Chinese had almost immediate market impact as the story was syndicated across more media outlets. For this material event, strong market impact was felt within 15 minutes of publication.

The impact of Justin Sun’s selfie in front of San Francisco’s Bay Bridge, refuting widespread rumors that he is unable to leave China, reveals that cryptocurrency markets can be highly efficient under the proper circumstances. In this case, market impact was felt immediately.

TRON paints a picture of moderate market efficiency in cryptocurrency markets. Under normal market conditions in which news is unexpected, it can take a meaningful period of time for market participants to price in the impact of material developments. This stands in contrast to equity markets in which new developments are priced in nearly instantaneously. But as events unfold over the course of several hours or days, markets can become highly efficient in connection with increased news reporting and focused trader attention. 

Engineered Price Movements Continue 

Recent price movements over the past week reveal that engineered price movements designed to trigger stop losses, margin calls, and forced liquidations of leveraged positions continue with high frequency. Cryptocurrency prices have been characterized by periods of low trading activity and price movement interspersed with extremely concentrated trading designed for maximum market impact. Weekends can be targeted by traders seeking to engineer these price movements because there is strong seasonality in trading volume with much lower trading volume on Saturdays and Sundays, particularly in the morning hours in the UTC timezone. 

Volatility Continues to Increase

The maximum volatility experienced by Bitcoin has continued a long-term secular decline as the asset class matures. However, despite continued increases in trading volume, market participant sophistication, and trading infrastructure, the lower range of recent volatility appears elevated relative to historical minimums. 

This is driven by increased fragmentation of liquidity across trading venues (whereas in the past, trading was concentrated only on a handful of large exchanges) and the increasing popularity of margin and derivatives trading, both of which can trigger forced liquidations during times of large market movements. 

Recent three-month annualized volatility is at 101%, a level rarely reached in the past five years, and continues to increase. Volatility is not far from it’s most recent local high of 135%, last reached in early 2018, immediately following the peak of the bubble. 

CM Bletchley Indexes (CMBI) Insights

Correlation charts can provide interesting insight into the expected price relationship between assets. A correlation of 1 or -1 implies a perfect positive or negative relationship between two assets. Through assessing the correlation of Bletchley assets we can derive insight into how the market has been behaving.

During the bear market of 2018, generally speaking, much of crypto was correlated with Bletchley Indexes all having a correlation score >0.9 (i.e. If any of the Indexes increased, the most likely scenario was that the others increased as well, the same can be said for a decrease). However, since the beginning of the year Bitcoin has continually outperformed most of its peers. Since the Bletchley 10 is comprised ~70% of Bitcoin, the performance of the Bletchley 10 has outperformed the Bletchley 20 and Bletchley 40. Additionally, the level of correlation between them has reduced to around 0.7. This demonstrates a lower relationship between the price movement of the Bletchley 10 with the Bletchley 20 and Bletchley 40. However, more recently there is a flattening and even a slight increase in correlation, potentially signalling an improvement in short term strength for mid and low market cap assets.

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A Comparative Analysis of Bitcoin Forks

Monday, July 29, 2019

Bitcoin (BTC) has had many forks over the years, most of which have faded into obscurity. But one fork in particular has separated from the pack: Bitcoin Cash (BCH). 

In August 2017, BCH forked from BTC with a goal of “fulfilling the original promise of Bitcoin as ‘Peer-to-Peer Electronic Cash.’” Proponents of BCH believed that BTC was increasingly becoming a store of value as opposed to a medium of exchange, the latter of which they saw as the original purpose of BTC. To achieve this, they argued that it was necessary to increase BTC’s block size from 1 MB to 8 MB (and eventually to 32 MB), which would allow for more transactions per block and lower transaction fees (only a limited amount of data can be added to each block -- the smaller the block size the more users are incentivized to pay fees to make sure their transactions are included in a timely manner). 

In contrast, opponents of the BCH fork argued that increasing block size would ultimately lead to greater centralization. Larger block sizes mean that the total size of the ledger grows at a faster rate. Each full node operator (which includes, but is not limited to, miners, merchants, and auditors) needs to be able to download and store the entire ledger. They also need to propagate blocks across the peer to peer network. If the ledger grows too large too fast it becomes increasingly difficult for average full node operators to maintain the necessary hardware and internet bandwidth, which can lead to concentration of power. 

In November, 2018, a new fork split from BCH: Bitcoin Satoshi’s Vision (BSV). BSV forked from BCH with a similar goal of returning to Satoshi’s “original vision” (hence the name) of Bitcoin as peer-to-peer electronic cash. BSV expanded BCH’s scope, and further increased block size to 128 MB. Additionally, BSV eliminated the size restriction on OP_RETURN transactions, which resulted in a higher capacity for data storage on the BSV blockchain. BSV also elected not to adopt the OP_CHECKDATASIG opcode (which extends the scripting language to enable verification of signatures of arbitrary data), which was added by BCH. Ultimately, BSV aimed to “replace every payment system in the world with a better user experience, a cheaper merchant cost, and a safer level of security.” 

BCH and BSV currently have the 5th and 11th highest realized cap, respectively, out of all of the assets that we compute this metric for. Realized cap is calculated by valuing each piece of the supply at the price it last moved. In other words, it prices the supply at the time holders “realized” their gains or losses. The below chart shows realized cap for BTC, BCH, and BSV on a log scale:

In this piece, we compare on-chain activity for BTC, BCH and BSV, and analyze whether the two forks have achieved their proponents’ stated goals. First, we examine if there is evidence that they are being used as “peer-to-peer electronic cash,” which we henceforth refer to as a “medium of exchange.” Next, we look at differences in block size, and analyze whether and how the increased block space is being utilized. Finally, we examine security, and analyze the effects the forks have had on metrics like hash rate and mining revenue.

Medium of Exchange Analysis 

In this section we examine on-chain activity for BCH, BSV, and BTC, and analyze the degree to which these assets are being used as a medium of exchange. Although there’s no exact definition of how to measure a “medium of exchange” asset, we expect a medium of exchange asset to have relatively low fees, a high number of transactions, and large amount of value transferred. Additionally, there should be a high number of unique users actively using the network. We analyze various metrics, including adjusted transfer value, transaction count, and active addresses to gauge economic usage of each of the three assets.

Fees

BSV and BCH are both designed to be low fee blockchains. Low fees are an important aspect of medium of exchange tokens, because users are less likely to use an asset for regular payments if they are forced to pay significant fees each time. 

BSV and BCH have both had a median transaction fee of $0 for a majority of 2019. BTC’s median fee dipped to as low as $0.03 in early 2019, but has mostly remained between $1 and $3 over the last three months: 

But low fees can also be a long-term security risk. Miners are rewarded by a combination of block rewards and transaction fees. Fees become increasingly important as block reward issuance decreases. If total fees are too low, miners may not be incentivized to keep securing the chain after block rewards go to zero.

BTC’s total daily fees regularly top $1M, while BSV and BCH’s total fees have remained below $1,000 a day for the majority of 2019:

Transaction Count

BTC also has a lead in terms of total transaction count. But BSV and BCH are not quite as far behind. Specifically, BSV has a high number of transactions starting from November 2018 through early 2019. The following chart shows daily total transaction count for each of the three assets on a log scale:

However, a majority of BCH and BSV transactions do not transfer any value. Instead, they store data on the blockchain as part of an OP_RETURN output.

Although blockchains are predominantly used to record value transfers, they can also be used as a distributed, immutable database for non-transaction related data. Short messages (Bitcoin OP_RETURN messages must be less than 80 bytes), like “The weather in New York City on July 15 was 80 degrees,” can be written onto the blockchain and stored forever.

As a result, blockchains can be used as notaries or time stamping services (e.g. Proof of Existence). To do this, users need to create a cryptographic hash (which serves as a unique cryptographical identifier) of a document that they want to timestamp, and include that hash as part of a transaction. The transaction then serves as proof that the document existed at that time, since it is included as part of a specific block on the Bitcoin blockchain. This can then be used to disprove plagiarizers; if someone comes in at a later date and tries to claim that they created the document, the document’s original creator can use their transaction as proof that they already created the document at an earlier date.

To use the blockchain as a database, users need to be able to include arbitrary data as part of a transaction. Bitcoin added the OP_RETURN script opcode in 2013 to allow users to do this. OP_RETURN transactions can be used to record metadata on-chain, but cannot be used to effectively exchange value. Any outputs with OP_RETURN are unspendable. 

BSV transactions are increasingly including OP_RETURN. The below chart shows the daily count of BSV transaction with OP_RETURN, vs BSV transactions without OP_RETURN:

As of July 1st, over 94% of daily BSV transaction include an OP_RETURN:

Any app or user can use OP_RETURN to arbitrarily record data, for a variety of different reasons. A large portion of BSV’s OP_RETURN transactions, for example, come from a weather app called “WeatherSV.” WeatherSV records and retrieves climate data on the BSV ledger. According to the WeatherSV website, a weather channel “can be activated for $5 AUD and includes approximately 142 days of hourly broadcasts, based on current fees.”

The following chart shows the percent of total BSV OP_RETURN transactions sent by individual applications. Since May, a majority of BSV OP_RETURN transactions have been sent by WeatherSV:

In fact, a majority of BSV’s overall transactions (including transactions with and without OP_RETURNS) are now coming from WeatherSV. As of July 14th, over 94% of all BSV transactions are being sent by WeatherSV:

Similarly, BCH is increasingly trending towards transactions with OP_RETURN. The following chart shows the daily count of BCH transaction with OP_RETURN, vs BCH transactions without OP_RETURN:

As of July 1st, over 67% of daily BCH transaction include an OP_RETURN:

Comparatively, only about 25% of BTC transactions include an OP_RETURN: 

A majority of BTC’s OP_RETURN transactions come from Omni and Veriblock. The below chart shows OP_RETURN transaction count for each:

Relative to BTC, BSV and BCH are increasingly being used as a way to store data, as opposed to as a medium of exchange. Additionally, BCH or BSV could potentially become a data storage layer for other blockchains, as recently proposed by Ethereum’s Vitalik Buterin.

Adjusted Transfer Value

Total value transferred gives an approximation of total goods exchanged. We define value transfer as “movements of native units from one ledger entity to another distinct ledger entity.” Only transfers that are the result of a transaction and that have a positive (non-zero) value are counted. Total transfer value therefore serves as a proxy for total economic activity. 

However, it’s not a perfect measure; not every value transfer is necessarily a true exchange of economic goods. For example, many transfers are due to users cycling assets between various addresses that they own. 

To account for this, we use a metric which we call ‘adjusted transfer value,’ which  attempts to remove non-economic activity and other artifacts like self-sends and deliberate spamming. BTC dominates in terms of total amount of value transferred. The below chart shows total adjusted transfer value for BTC, BSV, and BCH:

BSV and BCH’s adjusted transfer value have both been growing. BSV’s 2019 daily adjusted transfer recently value peaked at $144.2M on June 26th, 2019, while BCH reached its 2019 peak of $325.5M on June 27th, 2019. However, this is still orders of magnitude less than BTC, which reached $3.58B daily adjusted transfer value on June 20th, 2019.

During the month of June, BTC had over 85% of the total market share (between the three assets) of adjusted transfer value, as seen below:

Median Transfer Value 

BTC’s median transfer value is also significantly higher than both BCH and BSV. While BTC’s median transfer value has fluctuated between $50 and $100 USD over the course of 2019, BSV and BCH’s median transfer value has mostly stayed between $1 and $10. BSV, in particular, has been relatively volatile over the past few months, dropping to a median transfer value of $0 on several separate days:

A larger total transfer value or median transfer value doesn’t necessarily mean that an asset is being used more as a medium of exchange while another is not; perhaps BSV is being used for small exchanges and/or microtransactions (similar to Kin, which we investigated in a previous research report), while BTC is being used to exchange more valuable goods and services. But it will be an important metric to monitor moving forwards, as it can shed more light on what these assets are actually being used for.

Active Addresses

Active addresses are a way to get an approximate measure of the total number of unique people using a crypto asset. We define “active addresses” as the count of unique addresses that were active in the network (either as a recipient or originator of a ledger change) that day. Active addresses represent a maximum number of potential daily unique users, assuming that each user needs at least one address. However, it’s important to note that many users control multiple addresses, which means the actual amount of unique users may be significantly lower than the total amount of unique addresses. Addresses can be one person to many addresses or many people to one address (like an exchange wallet).

BTC once again dominates in terms of active addresses. The below chart shows daily active addresses on a log scale. While BTC has fluctuated between 600,000 and 1,000,000 daily unique active addresses for most of 2019, BCH and BSV have remained below 100,000 and 50,000, respectively (outside of a few outliers):

Address Balance Distribution Bands (USD)

Address balance distribution bands show the count of unique addresses holding a specific amount of dollars worth of currency at the end of that day. 

This metric also represents a proxy of potential unique users, again assuming that each user needs at least one address holding a non-negligible amount of value. BTC is approaching 20M unique addresses with at least $1 (and growing), while as of July 1st BCH and BSV had 5.05M and 4.19M, respectively

The below charts show the amount of unique addresses holding at least $1, $100, $1k, $10k, $100k, and $1M:

Medium of Exchange Summary

Although BSV and BCH have some of the desirable features of a medium of exchange asset, like low fees, this has not yet led to a large increase in activity as compared to BTC. Both BCH and BSV still only have a small fraction of the usage of BTC when measured by metrics like adjusted transfer value and active addresses.

Furthermore, BSV and BCH are increasingly being used as ways to store data on chain, and not as a medium of exchange. BSV, in particular, is predominantly being used as a way to record data on-chain, with over 94% of transactions containing OP_RETURN, a majority of which come from a single weather application. BSV may ultimately be used as a data storage blockchain, likely due to their removal of the size restriction on OP_RETURN transactions. 

As of now, BCH and BSV are not gaining real usage over BTC as a medium of exchange. It remains to be seen whether they can take more of BTC’s market share moving forward. 

Block Size Analysis

Block size was a main point of contention for both the BCH and BSV fork. After much debate, BCH increased block size to 32MB, and BSV increased it once again to 128MB. Theoretically, bigger block size allows for more transactions per block. But is this increased block size being utilized? In this section, we analyze various metrics related to block size and block fullness. 

Total Block Size (Bytes)

In terms of total block size, BTC still leads both BSV and BCH, despite having a smaller maximum block size. The below chart shows total block size (the sum of the size, in bytes, of all blocks created) on a daily basis. Much of BSV’s total block size is due to the proliferation of transactions with OP_RETURN, as noted in the “medium of exchange” section.:

Mean Block Size (Bytes)

BTC also leads both BSV and BCH in terms of mean bytes per block. While BTC has consistently remained around an average of 1MB per block, BSV and BCH have for the most part remained well below the 1MB per block threshold. BSV has had full blocks, but has not yet had consistently full blocks over the course of a day. 

Full BSV blocks also led to several orphanings. Orphan blocks are valid blocks that do not end up getting included in the main chain. Orphan blocks occur when multiple miners successfully mine a new block at approximately the same time. One of the blocks gets accepted to the blockchain, while the other is “orphaned,” and does not get accepted. This is exacerbated by larger blocks, because larger blocks take significantly longer to propagate and validate, which can lead to miners getting out of sync. In April, 2019, six consecutive BSV blocks were orphaned, which included a 128 MB block. 

Both BSV and BCH have occasionally surpassed a 1MB per block daily average, as seen in the below chart (on a log scale):

Mean Transaction Size (Bytes)

Broken down by individual transactions, BSV actually has more mean bytes per transaction than both BCH and BTC. This again is most likely related to OP_RETURNS; many BSV transactions contain arbitrary data, which increases the overall transaction size:

Block Size Summary

Although both BCH and BSV have larger maximum block sizes than BTC, they have not yet utilized that extra space. For the most part, BCH and BSV’s daily average block size has remained well below BTC’s 1MB average. 

Both BSV and BCH have had blocks that have exceeded BTC’s largest blocks. BSV blocks, in particular, are increasingly being filled by OP_RETURN transactions, as alluded to in the “medium of exchange” section. 

BSV and BCH’s increased block size may become a factor if either gain adoption as a data storage blockchain. But it does not appear to currently be a factor in terms of being used as a medium of exchange. 

Security and Mining; Impact of Hash Rate

Network security is arguably the most important consideration for any blockchain. A major security failure has the potential to destroy a crypto asset’s value in a very short period of time. In this section we analyze metrics like hash rate and total mining revenue, to measure the security of each of the three crypto networks.

Hash Rate 

When blockchains go through a contentious hard fork (where the hashing algorithm stays the same for both off-shoots), their hash rate is inevitably affected. Hash rate is the speed at which proof of work computations are being completed across all miners in the network, and serves as a proxy for energy expenditure. Miners choose whether to stay on the original chain, or to leave and start mining the new forked chain. Hash rate increases as more miners join the network, and when more powerful mining hardware is used. Conversely, it decreases if miners leave the network and are not replaced by either new miners or more efficient hardware.

BTC has a huge hash rate lead over both BCH and BSV. Although BCH temporarily rivaled BTC’s hash rate in late 2017 (due to miners gaming the BCH difficult adjustment algorithm), BTC has since decisively pulled away. Furthermore, BCH’s hash rate decreased significantly when BSV forked in November 2018.

The below chart shows the daily mean daily hash rate for BTC, BCH, and BSV on a log scale. BTC’s hash rate recently peaked at 74.55M TH/s on July 5th, while BCH and BSV’s peak daily hash rate of the year (2019) so far have been 2.7M and 1.49M, respectively:

Overall, BTC still has a huge majority of hash rate compared to both BSV and BCH. As seen below, BTC has over 95% of the hash rate market share (amongst BTC, BCH, and BSV) as of July, 2019:

Mining revenue 

Mining revenue is another important security metric. We define mining revenue as “the sum USD value of all miner revenue (fees plus newly issued native units, i.e. block rewards) on a given day.” Mining revenue represents the incentive pool for miners; increase in mining revenue incentivizes more miners to join the market.

The below chart shows total mining revenue of the three blockchains. BTC has millions more dollars of daily mining revenue than both BCH and BSV combined:

Transaction fees are an increasingly important part of total mining revenue. The BTC (and by extension, BCH and BSV) block reward halves every 210,000 blocks, with the next halving expected to occur in May 2020. As block rewards move towards zero, transaction fees become a larger proportion of mining revenue. This will be an especially important consideration for BCH and BSV, both of which currently have less than $500 of daily total fees.

The below chart shows daily mining revenue, on a log scale:

Rewrite Time

We also looked at the amount of time it would take BTC miners to rewrite ten days of the BCH and BSV blockchains. In this theoretical attack, all BTC miners stop mining the BTC blockchain, and instead collectively work to rewrite one of the other two chains. It would take BTC miners three hours to rewrite ten days of the BSV blockchain, and seven hours to rewrite ten days of the BCH blockchain (if BTC miners performed the same attack on BTC, it would take them approximately ten days to rewrite ten days worth of history):

On BCH, this attack is only theoretical as the developers introduced a deep reorg protection. Any fork starting deeper than 10 blocks ago has to accumulate much more work than the main chain to be accepted.

Security Summary

BTC currently has a big lead over BCH and BSV in the four metrics we used to measure security. Although BCH briefly threatened BTC’s hash rate, it has since declined, and was further hurt by a hash rate split at the time of the BSV fork. BTC has over 95% of the hash rate market share (amongst BTC, BCH, and BSV) as of July, 2019.

BTC also dominates in terms of daily mining revenue. BTC has over 30 and 60 times more daily mining revenue than BCH and BSV, respectively. This will become even more of an issue as block rewards continue to halve, as BCH and BSV’s total transaction fees are negligible compared to BTC’s. 

We also found that if BTC miners were to theoretically attack BCH they could rewrite ten days of the blockchain in 7 hours. If they were instead to attack BSV, they could rewrite it in 3 hours.

Ultimately, BTC remains a much more secure blockchain than both BCH and BSV. Both are currently losing ground on BTC, and have a long way to go to catch up.

Summary

Although BSV and BCH have some of the desirable features of a medium of exchange asset, like low transaction fees, this has not yet led to a large increase in activity as compared to BTC. Both BCH and BSV still only have a small fraction of the usage of BTC when measured by metrics like adjusted transfer value and active addresses.

Furthermore, BSV and BCH are increasingly being used as ways to store data on chain (often without an associated economic transaction), and not as a medium of exchange. BSV, in particular, is predominantly being used as a way to record data on-chain, with over 94% of transactions containing OP_RETURN, a majority of which come from a single weather application. BSV may ultimately be used as a data storage blockchain, likely due to their removal of the size restriction on OP_RETURN transactions. 

Additionally, although both BCH and BSV have larger maximum block sizes than BTC, they have not yet utilized that extra space. For the most part, BCH and BSV’s daily average block size has remained well below BTC’s 1MB average. 

Both BSV and BCH have had blocks that have exceeded BTC’s maximum blocks. BSV blocks, in particular, are increasingly being filled by OP_RETURN transactions. BSV and BCH’s increased block size may become a factor if either gain adoption as a data storage blockchain. But it does not appear to currently be a factor in terms of being used as a medium of exchange. 

Additionally, BTC currently has a big lead over BCH and BSV in the four metrics we used to measure security. BTC has over 95% of the hash rate market share (amongst BTC, BCH, and BSV) as of July, 2019. 

BTC also dominates in terms of daily mining revenue. BTC has over 30 and 60 times more daily mining revenue than BCH and BSV, respectively. This will become even more of an issue as block rewards continue to halve, as BCH and BSV’s total transaction fees are negligible compared to BTC’s. 

We also found that if BTC miners were to theoretically attack BCH they could rewrite ten days of the blockchain in 7 hours. If they were instead to attack BSV, they could rewrite it in 3 hours.

As of now, BCH and BSV are not gaining real usage over BTC as a medium of exchange, and are not utilizing their larger block sizes. BTC also remains a much more secure blockchain than both BCH and BSV. It remains to be seen whether BCH and BSV can take more of BTC’s market share moving forward.

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