Coin Metrics' State of the Network: Issue 44

Is the Upcoming Bitcoin Halving Priced In? - Understanding Miner Economics From First Principles 

Understanding Miner Economics From First Principles 

By Kevin Lu and the Coin Metrics Team | Tuesday, March 31st, 2020

The next halvening is approaching, yet debate about its impact on asset prices remains mired in controversy. 

Two camps have formed. One believes the halvening is already priced in by market participants, citing the efficient market hypothesis. The other camp believes it isn’t yet fully priced in and expects the halvening to plant the seed for further increases in prices due to the increase in perceived scarcity and the change in supply-side dynamics.  

Source: Coin Metrics Network Data Pro

We believe the intensity of the debate partially stems from the limited empirical record. Bitcoin has only experienced two halvings in its history and only a handful of other proof-of-work coins have gone through the same events. Discussions are stalled because of the lack of shared terminology, small sample size, and inaccessible data regarding critical questions. 

In this week’s State of the Network, we present a framework for understanding miner economics and how to best navigate the upcoming block reward halving. The intention is to present a framework reasoned from first principles rather than relying purely on empirical data. We also apply this framework in examining the upcoming halving for Bitcoin, Bitcoin Cash, and Bitcoin SV. 

Three Miner Axioms and Inferences 

We present a set of three miner axioms which we believe to be largely true as a starting point for further reasoning. We say “largely true” because there are always edge cases -- they may not hold for certain assets or for certain miners. But for the most part, these axioms hold water. 

We also present three miner inferences that are built upon our three axioms. These inferences form the foundation of our framework for understanding miner economics. 

Axiom 1 

Miners operate as profit-maximizing commercial enterprises with large economies of scale

Mining has gotten so difficult and resource-intensive that is largely uneconomical for an individual or hobbyist to participate. Instead, there are large economies-of-scale to mining. Large miners locate themselves in areas of the world where electricity is cheap. They are able to negotiate lower rates with electricity utility companies, purchase large quantities of the most efficient mining equipment, and rent large facilities to operate the equipment. 

The ability to mine at scale lowers the cost of mining a single coin. And since mining is a competition, miners organize as a profit-maximizing commercial enterprise. Miners do not operate for ideological or altruistic purposes and cannot continue operating in the long-term if they are not profitable. 

Axiom 2

Mining is a competition with a fixed total reward that is split among all participants with a regular cadence

Issuance is mandated by the protocol and controlled via a difficulty adjustment. In the case of Bitcoin, the protocol generates a block reward of 12.5 coins per block (currently) and regularly adjusts mining difficulty such that blocks are generated on average every 10 minutes. All miners compete for this reward, along with transaction fees. The total block reward revenue for all miners over a given period of time is predetermined and cannot be changed except for marginal amounts and for brief periods of time between difficulty adjustments. 

Axiom 3

Miner revenue is denominated in crypto while miner costs are denominated in fiat 

Miner revenue consists of the block reward and transaction fees, both of which are denominated in crypto. 

Mining costs include mining hardware, electricity to operate the miners, cooling fees, facility rental fees, server maintenance, internet connectivity, salaries, insurance, legal services, taxes, and so on. These costs are denominated in fiat since most traditional companies do not currently accept crypto as payment (electricity utility companies will not take Bitcoin as payment, for example). Even if certain expenses end up being paid using crypto, such as instances where miners pay for equipment or employee salaries using crypto, the price of the good or service is still quoted in fiat currency. 

Inference 1

Mining is a (Nearly) Perfectly Competitive Industry 

Based on the first two axioms above, the first inference we introduce is that the mining industry operates under an equilibrium of nearly perfect competition where the market price faced by each miner equals the miner’s marginal cost. This is achieved by two mechanisms. 

First, profit-maximizing miners enter the industry or invest in more equipment when mining is profitable and exit the industry or turn off miners when it is unprofitable. Second, the change in hash rate triggers a difficulty adjustment which constantly seeks to bring the cost of mining a single coin equal to the current market price. 

Mining is zero-sum (in the long-term) in that each miner is in competition with other miners over the same block reward. This also means that miners operate in an equilibrium state of zero economic surplus -- that is, in the long-run, miners earn only normal profits and are compensated only for the opportunity cost of their time plus an allowance for risk. Due to the competitiveness of the miner economy, it seeks a long-term equilibrium where miners profit margins are small and close to zero. 

Miner profit margins, however, can meaningfully fluctuate around this equilibrium due to delays inherent in the system which has important implications on miner-led selling pressure. We discuss this more in the following two inferences. 

Furthermore, the industries that reside upstream to mining such as miner hardware and semiconductor manufacturers show elements of oligopoly market structure. Based on this supply chain, certain miners (such as the Bitmain affiliated mining pools) can leverage information advantages or access mining hardware earlier than their competitors which reduces the degree of perfect competition in the mining industry.

Inference 2

Miners Are a Continuous and Significant Source of Selling Pressure

Combined with the third axiom, we present an important inference: miners represent the single largest cohort of natural, consistent sellers. Their selling pressure is significant because miners must sell the crypto that they earn to cover their fiat-denominated costs. And since their profit margins tend to gravitate towards zero, miners must sell nearly all of the crypto that they earn. 

Here we use Bitcoin to contextualize the magnitude of miner-led selling pressure. Miner revenue in 2019 was nearly $5.5 billion dollars. Some researchers compare this number to the annual trading volume of Bitcoin, which is several magnitudes bigger, and conclude that miner-led selling pressure has a negligible impact on the market. However, selling from miners represents net capital outflows from the space and the fiat obtained by miners is unlikely to ever return to the market, which is not necessarily the case for other trading volume. Therefore, miner selling has an outsized influence on the rest of the market

Put differently, the best estimates indicate Coinbase has roughly 1 million Bitcoin in customer deposits. At current prices, this is equivalent to $6.8 billion dollars, an amount similar to annual miner revenue in 2019. Under the assumption that miners sell the majority of the crypto they mine, miner-led selling pressure is nearly equivalent to all customers on Coinbase liquidating their Bitcoin over the course of a year and permanently exiting the market. 

Source: Coin Metrics Network Data Pro

We extrapolate miner revenue for the entire year of 2020, assuming prices remain at current levels and accounting for the halving of the block reward. Under these assumptions, we should only see half-of-a-Coinbase worth of selling pressure this year -- a significant reduction. 

Inference 3

Miners Have a Pro-Cyclical Impact on Asset Prices 

While the mining industry is constantly seeking a long-term equilibrium where miner profit margins are small but close to zero, the reality is that profit margins experience large fluctuations around this steady state. 

Elements influencing the cost side of the equation are slow moving and react with a meaningful lag. Decisions regarding entering or exiting the industry, purchasing additional equipment, and scaling up operations all take time. And difficulty adjustments by their nature have an approximately two week lag. 

On the opposite side, revenue is fast moving because one of the main determinants is the price of the coin which is subject to extreme levels of volatility. Bitcoin regularly experiences annualized volatility of over 50 percent. 

Source: Coin Metrics Reference Rates

Varying profit margins due to these factors mean that the amount of selling pressure by miners to cover their fixed, fiat-denominated costs varies as well. When prices are particularly volatile or trend in one direction over a sustained period of time, miner profit margins can be consistently positive or negative for meaningful amounts of time. These deviations are more likely to occur when prices are rising, since delays regarding more capital investment in mining hardware are more prominent compared to delays when prices are declining. The decision to shut off miners when prices fall below electricity costs can be made quickly. 

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 slow moving and fairly constant in fiat terms, miners are required to sell less of their block rewards to cover their expenses during periods of rising crypto prices. 

On the other hand, when crypto prices are falling, they are required to sell more. Under this theory, miners have a pro-cyclical effect on the market, in that they further exacerbate price increases. There are limitations to this dynamic, however. Sustained increases in prices can compel miners to sell more of their block rewards to fund additional capital investment in new mining hardware suggesting a counter-cyclical impact on prices under certain market conditions. 

During periods of capitulation where profit margins for many miners are negative, miner-led selling flow is likely to be high. Miners may attempt to endure periods of short-term pain, and perhaps may temporarily operate at a loss until less cost-efficient miners exit the industry. Miners may 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. 

All of these behaviors reinforce the direction in which crypto prices are moving and are a key determinant in why crypto prices regularly experience bubbles and crashes. 

While we believe this framework characterizes the pro-cyclical behavior of most miners, the rise of a robust lending market has the potential to change this dynamic. This allows miners to speculate on the future price of Bitcoin and engage in market timing where they pay for their fiat expenses using borrowed funds that are collateralized with the Bitcoin on their balance sheet. Miners that engage in this behavior believe that Bitcoin’s price will rise in the future and delay selling. The rise of a derivatives market which allows miners to hedge against future price movements can play a similar role. 

While the overall impact on the amount of miner-led selling flow depends on how accurate miners are in their market timing efforts, we believe that miners will tend to borrow fiat under certain market conditions. Assuming that miners intrinsically have a long-bias for Bitcoin, miners will tend to borrow fiat when they believe prices are well below the long-term fundamental value and when they believe we are firmly in a bull market. This should moderate the pro-cyclical impact when prices are declining but accentuate the impact when prices are increasing. 

The Upcoming Halving 

Bitcoin will soon experience its third halvening where the block reward will be reduced from 12.5 coins per block to 6.25 coins per block, equivalent to annualized issuance being reduced from 3.6 percent to 1.8 percent. This is anticipated to occur in approximately 45 days or May 14, 2020. 

Source: Coin Metrics Network Data Pro

Prices have sharply declined over the past several weeks in concert with risk assets in traditional markets. The pro-cyclical behavior of miners implies that miner-led selling pressure should be increasing as well. Prices have almost certainly declined below the breakeven price for the set of miners who are least efficient and have the lowest profit margins. These miners have likely either temporarily or permanently shut off their machines. This can be seen in the most recent difficulty adjustment where difficulty declined by 16 percent, one of the largest drops in history.

Source: Coin Metrics Network Data Pro

Such a large difficulty adjustment indicates that inefficient miners are already reaching a point of capitulation where they are forced to sell all the coins they mine to cover their costs. 

Miner-led selling pressure for Bitcoin is likely to continue to increase because both Bitcoin Cash and Bitcoin SV will be experiencing their halving on April 8 and April 9, respectively. All three assets share the same SHA-256 mining algorithm and miners can seamlessly redirect their hash power to the asset that provides the highest return on investment. 

When Bitcoin Cash and Bitcoin SV halve their block rewards, this should force miners to direct even more hash power to Bitcoin as it will still have a 12.5 native unit block reward (instead of 6.25) for about a month longer. Therefore, we should expect difficulty increases for Bitcoin that should further squeeze profit margins for all miners. 

Source: Coin Metrics Network Data Pro

It is concerning that miners are in a state of capitulation even before the halving. Once the block reward halves, miner revenue will be cut in half while miner costs will remain constant, so we expect even more miners to capitulate in the months ahead. 

Miner capitulation increases selling pressure until inefficient miners are forced off the network, but in the long run these events are supportive for prices. Culling inefficient miners allows only the most efficient miners with the lowest cost of production to remain. Once inefficient miners exit the network, profit margins will improve for the remaining miners, which reduces selling pressure, increases prices, and should repeat in a virtuous cycle. Eventually, if prices bottom and recover, the pro-cyclical behavior of remaining miners should support further price increases. 

Conclusion 

Using a set of axioms, we provide a framework reasoned from first principles that illustrates how miners are a continuous and significant source of selling pressure that has a pro-cyclical impact on prices. Miner-led selling pressure for Bitcoin, Bitcoin Cash, and Bitcoin SV is currently high and is likely to increase further in the coming months as all three coins undergo their halvings.

We expect miners to follow a cycle of decreased profit margins, increased selling, capitulation, and a culling of the least efficient miners from the network. Once this cycle is complete, the miner industry should return to a healthier state that is supportive of future price increases. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

The major cryptoassets remained relatively stable this past week. Although market cap increased, realized cap stayed stable or dipped for all five assets in our sample. The ratio of realized cap to market cap (MVRV) can be used to help gauge market tops and bottoms, and also gives insight into the behavior or holders vs speculators, as explored in State of the Network Issue 41.

Bitcoin’s estimated hash rate rose week-over-week after plummeting in the aftermath of Black Thursday, which led to Bitcoin’s second largest difficulty percentage drop in history. Although fees have been down this past week, mining revenue increased due to Bitcoin’s price gains. 

Network Highlights

Binance USD (BUSD) market cap has almost tripled since March 1st, increasing from about $68M to over $181M. Huobi USD (HUSD) market cap has almost doubled, growing from $78M to $136M.

The following chart was created using our free community charting tool. We recently added BUSD and HUSD to fill out our stablecoin data set.  

Source: Coin Metrics Community Charts

Tether also continues its rapid growth. There has been $1.4B worth of Tether issued on Ethereum (USDT-ETH) since March 1st. Tron-issued Tether’s (USDT-TRX) market cap has increased by about $165M since March 1st, while Omni-issued Tether (USDT) has stayed relatively stable. Tether’s total market cap is now over $6.4B

Source: Coin Metrics Network Data Pro

The amount of Bitcoin held by most exchanges has decreased over the last 30 days. Out of the exchanges in our coverage, only Kraken and Bitfinex have increased their BTC supply over the last month (1% growth each). 

Source: Coin Metrics Network Data Pro

The amount of Bitcoin held by BitMEX has been in freefall over the past two weeks after experiencing mass liquidations on March 13th (see State of the Network Issue 43 for our coverage on the BitMEX liquidation spiral). As of March 29th, BitMEX held 244k BTC, down from a peak of 315k on March 13th. 

Source: Coin Metrics Network Data Pro

Market Data Insights

Most cryptoassets remained largely unchanged over the past week but with significant volatility. Bitcoin and other coins continue to show intermittent periods of high correlation with risk assets, particularly during pre-market trading. Volatility remains at high levels with Bitcoin’s rolling one month volatility at 148%, nearly the same level as during the late 2017 bubble. 

Source: Coin Metrics Reference Rates

Stablecoins are seeing large increases in issuance but their pegs to the U.S. dollar remain relatively stable outside of an unstable period on March 12. The reason for the increase in issuance across the board is still unknown, but stablecoins do not appear to be selling at a meaningful premium. While most stablecoins remain close to the $1 U.S. dollar peg (with the exception of Dai), there appears to be a small but marked regime shift between and after March 12. Stablecoin prices and bid-ask spreads appear to have entered a more volatile regime. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

Cryptoasset markets had a turbulent week with most CMBI and Bletchley Indexes experiencing intraweek highs of over 10% above last week’s close. However after a strong start to the week, all indexes fell significantly through the weekend, but still managed to finish up between 0-5%. 

The Bletchley 40 (small-cap) finished the week strongest, up close to to 5% against the U.S. dollar and 3.5% against Bitcoin. All Bletchley multi-asset indexes outperformed the CMBI Bitcoin and CMBI Ethereum single-asset indexes this week. 

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • We are happy to announce that we completed a $6 million round of funding led by Highland Capital Partners with participation from FMR (Fidelity Management & Research), LLC, Castle Island Ventures, Communitas Capital, Collaborative Fund, Avon Ventures, Raptor Group, Coinbase Ventures, and Digital Currency Group.

  • 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.

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 43 - The BitMEX Liquidation Spiral

Tuesday, Month 23rd, 2020

The BitMEX Liquidation Spiral - Analyzing How Crypto’s Nascent Market Structure Held Up During the Crash

By Antoine Le Calvez and the Coin Metrics Team

In the previous issue of State of the Network, we presented some preliminary analysis of the recent dramatic crash in cryptoasset prices. We showed that on-chain data seem to indicate that few long-term Bitcoin holders capitulated when Bitcoin’s price dropped by nearly 40% in a single day.

Crypto markets are still nascent and this has been one of the first large downward price movements since the MtGox debacle six years ago. Since then, many new exchanges have sprung up, derivatives products have emerged and the amount of capital allocated to trading cryptoassets has skyrocketed.

In this feature, we’ll look at how the markets held under the pressure from the recent sell-off and whether crypto’s unique market structure exacerbated the problem.

The BitMEX Liquidation Spiral

Two large Bitcoin price moves occured on March 12th and 13th which were registered by Coin Metrics’ Real Time Reference Rate:

  • On March 12th, from 10:00 to 11:00AM UTC, Bitcoin’s price fell from $7,300 to a low of $5,690. 

  • From March 12th 11:00PM to March 13th 2:15AM, Bitcoin’s price fell from $5,800 to a low of $3,900.

One exchange played a particularly pivotal role during the second price drop: BitMEX.

BitMEX (Bitcoin Mercantile Exchange) is one of the largest new derivatives markets that emerged post-MtGox. It created the “perpetual inverse swap”, a financial product allowing leveraged trading of dollar-denominated Bitcoin perpetual futures contracts using Bitcoin as margin collateral.

Created in 2014, BitMEX’s popularity grew immensely and by March of 2020 it handled billions of dollars of trading volume per day. Studies have shown that its flagship perpetual contract is critical to Bitcoin’s price discovery.

On March 13th, during the second downward price movement at 2:16AM UTC, trading on BitMEX slowed to a crawl as the exchange faced what was first thought to be a hardware issue, but was later determined to be an intentional DDOS attack. This made it nearly impossible to trade on BitMEX.

As soon as BitMEX was attacked, the price recovered and surged to $5,300.

The red area indicates when BitMEX suffered DDOS attacks.

From March 12th 9AM to March 13th 6AM UTC, long positions worth 1.1B contracts (one contract represents a $1 position) were liquidated. As traders got liquidated, the open interest (the number of contracts held by traders) decreased:

BitMEX allows leveraged trading of Bitcoin, but also guarantees that no trader can lose more than their margin (i.e. you cannot lose more than what you bet). In traditional markets, this is often not possible. BitMEX achieves this using two features. 

First, if a position gets liquidated (its remaining margin is not high enough), an automated system takes over the position: the liquidation engine. Run by BitMEX, it aims to close the trader’s position at a price favorable enough that not all the remaining margin gets used. If it manages to do so, the profits go to an insurance fund. If it doesn’t, funds get withdrawn from that insurance fund (which stands at more than 30k BTC as of writing). 

The second feature is auto-deleveraging. If the liquidation engine cannot close liquidated positions profitably and the insurance fund runs low, it resorts to taking money from traders with winning positions to cover losses from losing positions. This is the last recourse, as arbitrarily changing traders’ positions on one exchange can affect their overall financial health since they often run strategies on many other exchanges. Following this crash, BitMEX posted a good in-depth explainer of these mechanics. 

This bloodbath was partially stopped when BitMEX suffered a reported DDOS attack. This led many to wonder whether the crash was partially caused or aggravated by the exchange’s handling of all the liquidated positions.

The theory goes as follows:

When long positions get liquidated, as was the case when the price went down, the engine has to sell contracts. As liquidations mounted and liquidity waned, the engine was put in a difficult spot: it had lots of contracts to sell, but faced a worsening price leading to more liquidations and more contracts to sell. This can create a vicious cycle that is difficult to stop.

When trading on BitMEX became very difficult due to the DDOS attack, the biggest seller on the market, BitMEX’s liquidation engine, disappeared and the price naturally went up.

A Lingering Impact on Liquidity

A common way to measure market conditions is looking at the bid-ask spread, which is the difference between the best bid (i.e. the price a buyer is willing to pay) and the best ask (i.e. the price a seller wants to receive). It is commonly measured in basis points (0.01% equals 1 basis point or bps).

For Bitcoin, still an emerging asset class and with varying fees per trading venue, the bid-ask spread is mostly below 20 bps in normal trading conditions. This can be seen across three exchanges in the chart below, observed from February 1 to 3 of this year:

Source: Coin Metrics Market Data Feed

Large price movements directly affect the bid ask spread as market makers react to the volatility by widening their bids and asks. In the next chart, we can see the impact of a price drop from $9,500 to a low of $8,000 in the span of 2 hours in September 2019  (the Y-axis is capped at 50bps to make this more visible):

Source: Coin Metrics Market Data Feed

Once the move is over and the price stabilizes, the spreads come back to their pre-move levels.

The March 12th-13th move was different. Spreads still haven’t come back to their previous levels.

Source: Coin Metrics Market Data Feed

There could be multiple explanations as to why spreads haven’t come back to pre-March 12th levels. Market participants could be expecting volatility to continue and are preparing themselves by increasing their spreads. Bitcoin’s realized volatility measured over the past one month is at the high end of its historical trading range over the past six years. 

Source: Coin Metrics Reference Rates

It could also be that some market participants left altogether, reducing liquidity. For example, futures open interest hasn’t grown following the market crash and bid-offer spread for a $10M quote has grown significantly:

Source: Coin Metrics Market Data Feed

Stablecoins Galore

The supply of all stablecoins Coin Metrics tracks started growing around the time COVID-19’s impact on global markets started to be visible (S&P all-time-high was on Feb 19th). It seems that the growth of stablecoins’ supply increased after Bitcoin’s massive drop.

Source: Coin Metrics Network Data Pro

The dual impact of Bitcoin’s USD value halving and massive issuance of stablecoins led to stablecoins’ market cap as a percentage of Bitcoin’s doubling in a matter of days:

Source: Coin Metrics Network Data Pro

Conclusion

This recent market move was spectacular, the largest in Bitcoin’s modern history. It had many implications: spreads on spot and futures markets widened, on-chain fees spiked as people rushed to deposit coins, and stablecoins gained market share.

It also raised many questions: should circuit-breakers be instituted? Is Bitcoin really a store of value if its value can drop in half in a matter of hours or is this merely a function of nascent market structure? 

While a lot of these questions are still unanswered, one is getting closer to having an answer: Huobi has recently implemented a liquidation circuit breaker on all their derivatives products. Despite its name, it isn’t a traditional circuit breaker in which trading stops if the traded product’s price drops too quickly. Instead of stopping trading, it throttles the liquidation engine to avoid vicious liquidation cycles. It is still unclear whether this would prevent any such cycle. It could also end up exposing the exchange to large losses if the drop in price was warranted and not caused by its liquidation engine.

While the price mostly recovered, this event left lasting marks on Bitcoin’s market structure from spreads to concerns about its stability. BitMEX might have lost traders’ confidence, as the number of Bitcoin it holds has been steadily decreasing since the crash.

Times of stress and sudden change often lead to innovation and restructuring. Crypto market structure will likely continue to be tested during these turbulent times, and will hopefully mature and grow stronger as a result.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Most usage and security metrics were down for the major cryptoassets this past week as the dust began to settle following the March 12th crash. Notably, Bitcoin transactions are down over 14% week-over-week, more than any other large cryptoasset. This is at least partially because Coinbase introduced transaction batching on March 12th, which helped reduce transactions and lighten the load on the Bitcoin blockchain. 

Also of note, Ethereum active addresses increased by almost 17% week-over-week while decreasing for all other cryptoassets in our sample. This may be due to the increase in usage of Ethereum-based Tether (more on this in the “Network Highlights” section).

Bitcoin estimated hash rate fell 12.1% over the week, as mining revenue tumbled due to the drastic price decrease. As a result, it looks like Bitcoin difficulty will likely readjust to its lowest level in 2020 at the next difficulty retarget. 

Network Highlights

Stablecoin transfer value hit an all-time high amidst the market turmoil. On March 13th, the aggregated transfer of all stablecoins that we track (listed below) reached a new all-time high of $444.21M. 

The following chart shows the total transfer value (smoothed using a seven day rolling average) for the following stablecoins: Tether issued on Omni (USDT), Ethereum (USDT-ETH), and Tron (USDT-TRX), DAI, PAX, USDC, TUSD, and GUSD.

Source: Coin Metrics Network Data Pro

Money continues to pour into stablecoins as investors look for stability amidst volatile price action. USDC has been the biggest gainer percentage-wise, with a 57% market cap increase over the last 30 days. USDC is mainly used on Coinbase but is now also being used as collateral on MakerDAO in addition to other DeFi applications.

Source: Coin Metrics Network Data Pro

MakerDAO made the decision to add USDC as a collateral option (in addition to ETH and BAT) after the price of their own decentralized stablecoin, DAI, increased to as high as $1.06 on March 12th. DAI’s destabilization was the result of a mass MakerDAO collateral liquidation. As of March 22nd, DAI price remains above $1.02. 

GUSD also slipped off of its $1 peg over the past two weeks. Its price is less than $0.98 as of March 22nd.

Source: Coin Metrics Network Data Pro

Tether issued on Ethereum (USDT-ETH) has also had a large increase in market cap, and now accounts for over 50% of the total stablecoin market cap out of the stablecoins that we cover. USDT-ETH market cap has increased by over $660M since March 10th to $3.7B as of March 22nd.

Source: Coin Metrics Network Data Pro

Market Data Insights

After starting the week down, Bitcoin rallied to finish up 9% on the week. The major Bitcoin forks (Bitcoin Cash and Bitcoin SV) also finished the week strong, up 13% and 28% respectively. Most other cryptoassets are up or relatively unchanged for the week. 

Source: Coin Metrics Reference Rates

Recent coronavirus-related events have provided more evidence in understanding Bitcoin’s unusual reaction function. After selling off in concert with global equities two weeks ago, leading to the highest correlation between Bitcoin and the S&P 500 in its history, it has since experienced a few days with less correlated movement. 

Source: Coin Metrics Community Charts

Bitcoin’s inconsistent correlation with the S&P 500, with some days being highly correlated and some days being completely independent, suggest that its reaction function is still not fully understood. The common explanation that Bitcoin is a risk-off asset during periods of negative growth shocks is compelling and appears to fit some of the facts. The other commonly cited explanation is that fiat-based bills, debt servicing requirements, and margin calls combined with the de-risking of portfolios has led to a liquidity crisis, which in turn has contributed to the Bitcoin sell-off. 

We examine an alternative explanation based on inflation expectations. Here we show the five year inflation expectations. Five years forward is a standard barometer of where market participants think inflation is heading in the long-term. 

During normal times, we see inflation expectations well-anchored around the Fed’s two percent inflation mandate. But over the past week, inflation expectations have cratered as the economic impact of the coronavirus has been realized and as oil prices (a key determinant of headline inflation) have declined. This is happening despite unprecedented monetary policy stimulus by the Fed and most central banks around the world. 

One of the main reasons why we are so interested in Bitcoin is because it is a store-of-value, especially in environments where there are high levels of inflation. Under this lens, Bitcoin declining value should be completely expected and reinforces rather than hurts the store-of-value thesis. 

Source: Federal Reserve Bank of St. Louis

CM Bletchley Indexes (CMBI) Insights

Despite the dreariness of global markets that continue to reel from the impacts of COVID-19, CMBI and Bletchley Indexes managed to claw back some of last week’s significant losses. The CMBI Bitcoin index was the strongest performer of the week, returning 11%, with the CMBI Ethereum Index experiencing the slowest recovery, only jumping 1%. 

Despite Bitcoin’s strong performance, the Bletchley 40, small-cap assets was the best of the multi-asset indexes, demonstrating Bitcoin was an outlier among its large-cap peers.

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • 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.

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 42 - Data Shows Cryptoasset Sell-off Was Driven by Short-term Holders

Tuesday, March 17, 2020

Data Shows Cryptoasset Sell-off Was Driven by Short-term Holders

by Nate Maddrey and the Coin Metrics Team

On March 12th, amidst growing concerns over the COVID-19 pandemic, Bitcoin (BTC) suffered one of its largest one-day price drops in history. The rest of crypto followed, with most major assets down over 30% on the week.

Source: Coin Metrics Reference Rates

In this special edition of State of the Network, we take a deep dive into on-chain and market data to analyze the aftermath of the historic crash.

BTC & S&P Correlation Reaches New All-Time High

BTC’s historic price drop was concurrent with the equity markets’ worst day since 1987

On March 12th, the Pearson correlation between BTC and the S&P 500 soared to a new all-time high of 0.52. The previous all-time high was 0.32. This suggests cryptoasset markets are becoming more intertwined with existing markets, and are reacting to external events more than we have ever seen before. 

The following charts are sourced from our community charting tools which you can access for free here.

Source: Coin Metrics Community Data

Over the past week, BTC price has seemingly reacted to several key events, including President Trump’s announcement of a thirty day travel ban between the United States and Europe, as well as the Federal Reserve’s announcement that interest rates would be cut to 0.00%-0.25%. 

Source: Coin Metrics Reference Rates

BTC Sellers Appear to Mostly be Short-term Holders 

On-chain data shows that recent price movements were likely mostly driven by shorter-term and relatively new holders.

Coin Metrics’ revived supply tracks how many old coins come back into circulation after being untouched for a specific period of time. For example, thirty day revived supply tracks how much supply is moved on-chain (i.e. transacated) after being untouched for at least thirty days. 

On March 11th, about 281k BTC that had been untouched for at least thirty days were revived. But only 4,131 BTC that had been untouched for at least one year were revived. This signals that a vast majority of the activity on March 11th and March 12th involved BTC that had been held for less than a year. 

Source: Coin Metrics Network Data Pro

March 11th was the fourth largest spike in BTC thirty day revived supply over the last eight years. 

Source: Coin Metrics Network Data Pro

But long term holders appear unfazed in spite of the severe market downturn. March 11th’s one-year revived supply was not unusually large, as seen in the below chart. 

Source: Coin Metrics Network Data Pro

Transfer value days destroyed paints a similar picture. Transfer value days destroyed multiplies transfer value by the amount of days that the coins being transferred last moved on-chain. This gives older coins a much higher weight. For example, a coin that had not been transacted in 100 days is weighted 100x more than a coin that had been transacted 1 day ago.

There was not a significant spike in BTC transfer value days destroyed on March 11th or March 12th. This signals that there was not a relatively high amount of long-held coins moved prior to the recent price action.

Source: Coin Metrics Network Data Pro

Additionally, BTC SOPR dropped to 0.843 on March 12th, the lowest it’s been since February of 2012. In essence, SOPR is a network-wide indicator of profit/loss. It is the ratio of price sold (the price of BTC at the time new outputs are created) over the price paid (the price of BTC at the time a transaction’s inputs were created). Therefore a SOPR below one signals that investors are selling at a loss. 

Source: Coin Metrics Network Data Pro

BTC MVRV Drops Below One

For only the fourth time in history, BTC market value to realized value (MVRV) dropped below 1.0. MVRV compares a cryptoasset’s market cap to its realized cap. Realized cap can be thought of as an estimation of the asset’s aggregate cost basis.

As we wrote about in State of the Network Issue 41, an MVRV above one can signal that speculators have a higher average market valuation than holders. An MVRV below one, on the other hand, can signal that holders have (or had) a higher market valuation than current speculators. Holders are tested when MVRV swings below one, as it becomes less and less likely they will be able to immediately sell their holdings at a profit.

BTC MVRV fell by 0.5 on the 12th, which is the largest one-day drop since December 2013. In hindsight, the past periods where MVRV dropped below one have been the best times to accumulate BTC at a relatively discounted price.

Source: Coin Metrics Network Data Pro

The large drop in MVRV was caused by BTC’s market cap dropping by over 30% since March 9th, while realized cap has only dropped by about 3% (again suggesting that older coins were not being sold).

Source: Coin Metrics Network Data Pro

Realized cap dropped for all major cryptoassets. Ethereum (ETH) and Tezos (XTZ) were hit especially hard, with 6.09% and 9.12% drops, respectively, since March 9th. Maker (MKR) was the biggest loser with a massive 21% realized cap drop after MakerDAO was forced to weigh an emergency shutdown after the drastic decrease in ETH price. 

Source: Coin Metrics Network Data Pro

Money Pours Into Exchanges and Stablecoins

While market cap for most cryptoassets fell, the market cap for most stablecoins increased. This potentially signals that investors are piling into “cash,” or at least crypto cash equivalents. 

Ethereum-issued Tether (USDT_ETH) market cap increased by about $300M from March 10th through March 15th. USD Coin (USDC), which is used on Coinbase as well as other platforms, also had a huge gain, growing close to $150M in market cap since March 10th. 

Source: Coin Metrics Network Data Pro

On March 13th, over 160k BTC flowed into the exchanges in our coverage universe, which includes Binance, Bitfinex, BitMEX, Bitstamp, Bittrex, Gemini, Huobi, Kraken, and Poloniex. This was the largest one-day inflow since November 13th, 2017.

Source: Coin Metrics Network Data Pro

Similarly, over 171k BTC flowed out of exchanges on March 13th, which was the largest daily total since November 2017.

Source: Coin Metrics Network Data Pro

BitMEX, which is a leading destination for futures trading, had the most inflows out of the exchanges in our coverage, with 43.2k and 37.5k of BTC inflow on March 12th and 13th, respectively. 

Source: Coin Metrics Network Data Pro

Both Binance and Huobi, however, had more daily outflows than BitMEX. 

Source: Coin Metrics Network Data Pro

As a consequence, the amount of supply held by BitMEX soared to an all-time high. On March 13th, the amount of BTC held by BitMEX peaked at 315.7k.

Source: Coin Metrics Network Data Pro

A large spread of around 16% was observed between BitMEX and Coinbase during the sell-off. This is likely because forced liquidations from leveraged perpetual swap futures tend to exaggerate the direction of any move. The market recovered after BitMEX went down for 23 minutes reportedly due to unscheduled maintenance. BitMEX recently published an update detailing two DDoS attacks.

Source: Coin Metrics Market Data Feed

Conclusion

After a crazy week, the initial data from the aftermath is somewhat reassuring. Most of the sell-off appears to have been driven by relatively short-term holders, and longer-term holders seem to be holding strong, at least for now. BTC has also entered a historically attractive price zone, with an MVRV below one.

But the markets are still volatile, and it is unclear what lies ahead. We will continue to track events very closely through this unprecedented time, and will provide updates and new analysis over the upcoming weeks.

CM Bletchley Indexes (CMBI) Insights

All of the CMBI and Bletchley Indexes had a week to forget after global financial markets fell sharply on fears as to the impact COVID-19 may have on the broader economy. All indexes lost over a third of their value, with the CMBI Bitcoin Index falling 36% and the CMBI Ethereum Index falling 42%. Whilst this was a market wide capitulation, the large-caps were the ‘least’ impacted in a shocking week, as evidenced by the Bletchley 10’s positive performance against BTC and the negative performance of all other indexes against BTC.

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • This is a special edition of State of the Network as a response to the recent market crash. Regular State of the Network sections including Network Data Summary and Market Data Insights will be back next week.

  • Coin Metrics is hiring! We recently opened up 4 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 41 - Using MVRV To Analyze Investor Behavior

Tuesday, March 10th, 2020

Weekly Feature

Speculators vs Holders: Using MVRV To Analyze Investor Behavior

By Nate Maddrey and the Coin Metrics Team

In two previous issues of State of the Network (Primer on Cryptoasset Valuation Part 1 and Part 2) we conducted a comprehensive review of cryptoasset valuation research. In this issue we take a deep dive into one specific valuation metric: the market value to realized value (MVRV) ratio. 

MVRV is composed of two metrics: realized capitalization and market capitalization. In the following section we give an overview of how realized capitalization is calculated, as a prerequisite to an explanation of MVRV.

All of the data used in this report including realized cap and MVRV is available as part of Coin Metrics Network Data Pro. More information is available on our new website.

Realized Capitalization Overview

Realized capitalization is a metric created by Coin Metrics that is calculated by valuing each unit of supply at the price it last moved on-chain (i.e. the last time it was transacted). This is in contrast to traditional market capitalization which values each unit of supply uniformly at the current market price. 

For example, if Bitcoin’s (BTC’s) current price was $10,000, traditional market cap would value each coin equally at $10,000. If the current total BTC supply was 18 million, this would result in a total market cap of $180,000,000,000 (18 million multiplied by $10,000). 

Realized cap, on the other hand, values each coin at the time it was last moved on-chain. So if a coin was last transacted when BTC was $2,500, that particular coin would be priced at $2,500 instead of the current market price. The realized cap is the total sum of all coins priced this way. 

Realized cap can be thought of as an estimation of the aggregate cost basis of a cryptoasset.  This provides a valuable view into investor behavior that is not really possible with most traditional, non-crypto assets.

It’s important to note that this is just an estimate and not an exact measurement of investor cost basis. Realized cap measures the value of coins the last time they were transacted, not necessarily the last time they were traded or exchanged. But since cryptoassets are mostly used for investing/trading and not for payments (at least for now), realized cap can be used as a generalized proxy for cost basis. 

Realized cap also accounts for lost coins better than market cap. For example, if 100 BTC were last moved in 2011 when BTC price was $1, there is a decent chance that those particular BTC are permanently lost (see State of the Network Issue 26 for our analysis on the amount of BTC that has been permanently lost).  Realized cap would value these coins at a total of $100 (100 BTC multiplied by $1), while market cap would value them at current market prices.

Market Value to Realized Value Overview

MVRV is the ratio of a cryptoasset’s market cap (aka market value) to realized cap (aka realized value). It can be used to help gauge cryptoasset market tops and bottoms, and also to gain more insight into a cryptoasset’s investor behavior.

One way to view MVRV is to think of it as a comparison between speculator and holder valuation of a cryptoasset. Under this interpretation, market cap can be thought of as an estimation of speculators’ current market value (assuming sudden market cap changes are mostly driven by speculation). Realized cap, on the other hand, is a gauge of holders’ market valuation, since it reflects prices at time of last transaction and is not as affected by sudden price swings. 

An MVRV of one is therefore an important cutoff. An MVRV above one signals that speculators have a higher average market valuation than holders. An MVRV below one, on the other hand, signals that holders have (or had) a higher market valuation than current speculators. Holders are tested when MVRV swings below one, as it becomes less and less likely they will be able to immediately sell their holdings at a profit.

MVRV has historically been a good indicator of market tops and bottoms, at least for BTC. Peaks in MVRV have typically indicated that the market is at a top, while lows have occurred during times when a the market is at a bottom or in an accumulation period. 

But up until this point, most of the research around MVRV has focused on BTC and not other cryptoassets. BTC’s MVRV has mostly stayed above one, with a few accumulation periods where it briefly dropped below. However this is not the case for all cryptoassets. 

In the following section we analyze the MVRV ratio for a variety of cryptoassets, and explore what differing MVRV patterns tell us about each specific asset.  

Market Value to Realized Value Analysis

Historically, peaks in BTC MVRV have coincided with peaks in BTC price. MVRV spiked above 5.5 in Apr. 2013 and Nov. 2013, and above 4.5 in Dec. 2017, all three of which were local market tops. 

Conversely, there have been three periods since 2011 where BTC MVRV dipped below one: Sept. - Dec. 2011, Jan. - Oct 2015, and Nov. 2018 - Apr. 2019. In hindsight, all three of these periods have been some of the best times to accumulate BTC.

BTC MVRV shows relatively healthy patterns of growth followed by accumulation periods. MVRV has rebounded back above one after all three times it dropped below, which shows that there has been long term support by holders that has balanced out cycles of speculation. 

Source: Coin Metrics Network Data Pro

In its first few years of existence Ethereum (ETH) MVRV was well above one, which signaled a relatively speculative period. Fueled by the ICO craze, ETH MVRV spiked to 2.94 in March 2017 and 3.14 in June 2017 during local market tops. But it has declined since then, and has not topped 3.0 since the mid-2017 peak. 

ETH’s MVRV reached its lowest point in December 2018, when it dipped below 0.3. It then swung upward in early 2019 and again in early 2020, which signals that ETH potentially also has a base of holders who help support speculative growth spurts. ETH’s recent MVRV spikes have not been as high as BTC’s though, which suggests its in a slightly more precarious position. 

Source: Coin Metrics Network Data Pro

Similar to ETH, Ripple (XRP) initially had an MVRV well above one, which signaled that it was a relatively speculative asset. But in mid-2018 XRP’s MVRV abruptly dropped below one, and has not broken back above since. XRP’s MVRV inability to rebound back above one signals that speculative enthusiasm for XRP may be waning. If that is the case, holders are may increasingly be underwater.

Source: Coin Metrics Network Data Pro

Tezos (XTZ) MVRV shows an opposite pattern to XRP. XTZ MVRV remained below one for most of its history, and then suddenly shot above one in early 2020. This signals that XTZ likely had strong holder support for most of its early years. But its future is less clear - the sudden rise in MVRV could potentially signal that XTZ is turning the corner to an upswing, and/or that it is entering a period of high speculation.

Source: Coin Metrics Network Data Pro

Bitcoin SV (BSV) MVRV has been above one since its inception, which likely signals a relatively speculative market. Although BSV MVRV has fluctuated up and down, the level of holder support at MVRV of below one remains to be seen.

Source: Coin Metrics Network Data Pro

Conclusion

Cryptoasset valuation is still a burgeoning field, but there has already been a lot of interesting research about novel crypto-specific indicators. MVRV is a powerful metric that uses on-chain data to gauge market tops and bottoms, as well as provide information into the overall health of a cryptoasset. But it’s also important to look at other on-chain data and fundamental indicators in addition to MVRV to get a full picture of whether a cryptoasset is undervalued, or just underwater. We will continue to track MVRV across all major cryptoassets and provide updates through the latest market volatility.

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

Despite the market slide, usage metrics for most of the major cryptoassets were up this past week. BTC active addresses grew 5.3% week-over-week, while Litecoin (LTC), XRP, and Bitcoin Cash (BCH) active addresses all increased by 17% or more.  ETH active addresses saw a slight decline, however, dropping 4.9%.

ETH fees also dropped more than the other assets in our sample, declining by over 15%. However, it’s important to note that ETH still had an average of $96.2K of daily fees over the last week, while XRP, LTC, and BCH all had an average of less than $1K.

Network Highlights

We recently partnered with Blocknative to provide data for their research on transaction growth. The following excerpt and chart, taken from their report, shows aggregate transactions from 2009 until 2019:

“Significantly, we crossed the 1 billion aggregate transactions per year threshold in 2019. In fact, more than 37% (>1.1 billion) of all blockchain transactions in history occurred in 2019.”

Source: When One Billion Ethereum Transactions?

Over the last 180 days, Paxos (PAX) has outgrown Omni-issued Tether (USDT), Ethereum-issued Tether (USDT_ETH), USD Coin (USDC) and TrueUSD (TUSD) in terms of daily transactions count. PAX has grown about 545% over the period, while USDT and USDT_ETH transactions count has actually slightly declined. The following charts show percent growth smoothed using a seven day rolling average.

Source: Coin Metrics Network Data Pro

USDC, however, led the way in terms of adjusted transfer value growth. USDC grew by about 80%, while PAX was about even. 

Source: Coin Metrics Network Data Pro

Market Data Insights

Most cryptoassets experienced downturns this week as broader financial markets steeply declined in response to the coronavirus and crude oil price war. 

In a previous State of the Network, we showed quite strong evidence that BTC responded efficiently as military tensions escalated between the United States and Iran earlier this year. In the past week, BTC has been highly correlated with global equities with a near identical reaction to the Fed’s surprise 50 basis point interest rate cut and a coordinated sell-off on Sunday as futures markets opened. While events similar to this have happened in BTC’s history (such as during the Cypriot banking crisis, Greek default fears, and the initial passing of the Brexit referendum), the increased frequency of such events indicate that the “uncorrelated asset class” part of BTC’s narrative may no longer ring true in the future. 

Source: Coin Metrics Reference Rates

While gold has seen brief moments of weakness due to increased liquidity needs, it has nonetheless continued to serve as a relative safe haven asset with prices at seven year highs. BTC’s poor performance, in contrast, has raised legitimate questions about its ability to serve as a safe haven. 

In order to provide some historical benchmarks, we investigated the performance of BTC during acute moves in various risk-off indicators. 

S&P 500

To start, we investigated the S&P 500. Equities are typically considered to be risk assets and, as a key benchmark for equities, the S&P 500 typically falls during risk off environments. We selected the 20 worst days for the S&P 500 since the beginning of BTC’s price availability (7/18/10). 

During these 20 days, the S&P 500 had an average return of -3.77% and a median return of -3.49%. The average return of BTC during these 20 days was -0.78%, with a median return of -0.40%. 

Source: Coin Metrics Reference Rates

VIX

We also took a look at the VIX, a volatility index commonly referred to as the “Fear Index”. Volatility increases during periods of uncertainty, driving this index higher. We reviewed the 20 largest single day gains in the VIX since the beginning of BTC’s price availability.

During these 20 days, the VIX had an average gain of 44.6% and a median increase of 42.6%. The average return of BTC during these 20 days was 0.1%, with a median return of 0.5%. 

Source: Coin Metrics Reference Rates

10Y Treasury Rates

During risk off environments, investors typically purchase treasuries (which are considered safe haven assets), funded by sales of risk assets such as equities. We looked at 10-Year Treasury Constant Maturity Rates, selecting the 20 largest rate drops since the beginning of BTC’s price availability.

During these 20 days, the 10 year treasury rate had an average decline of 0.1560 percentage points and a median rate decline of 0.1600 percentage points.

The average return of BTC during these 20 days was 2.8%, with a median return of 3.1%. 

Source: Coin Metrics Reference Rates

As can be seen from the summary table below, BTC’s behavior relative to other risk indicators is inconclusive. At a superficial level, BTC appears to fall less than the S&P 500, but it also gains significantly less than the VIX. BTC’s average gains during instances where 10 year treasury rates fell significantly is interesting and an opportunity for the kind of future research required to provide a more comprehensive and thorough picture of BTC’s performance during times of market stress. 

Summary of Bitcoin’s Performance during days of acute market stress

Despite the performance during certain days of market stress illustrated above, historical correlations between BTC and financial assets have remained close to zero. Recent events, however, suggest a stronger relationship between BTC and events that affect broader financial markets. In light of recent data, BTC’s lack of correlation may be explained by its lack of maturity as an asset class rather than an inherent property. 

CM Bletchley Indexes (CMBI) Insights

All CMBI and Bletchley Indexes fell again this week as the cryptoasset market experienced volatility and poor performance. 

After starting the week strongly with most indexes up 10% on Friday, sentiment changed quickly through the weekend. The CMBI Ethereum Index was the best performer of the week, down only 0.7% for the week but returning 1.6% against BTC. Small-cap cryptoassets performed the best this week with the Bletchley 40 only experiencing a 1.5% drawdown. 

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 4 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 40 - Cryptoasset Valuation Research Primer, Part 2

Tuesday, March 3rd, 2020

Weekly Feature

Cryptoasset Valuation Research Primer, Part 2

By Kevin Lu and the Coin Metrics Team

In a previous State of the Network, we published the first part of our cryptoasset valuation research primer focused on summarizing and synthesizing this emergent field in the literature. 

Our introduction in the first part describes our approach: 

We conducted a comprehensive literature review to identify all major facets of cryptoasset valuation research that has been conducted so far. All methods were considered, from theoretical valuation frameworks, to empirical valuation models, to novel indicators that have application to valuation. 

In short, we are interested in all research that can be used to understand the current value of cryptoassets, estimate the value of cryptoassets, or predict future values of cryptoassets. All publication mediums are considered, regardless of pedigree, from forum postings to academic journals. The most salient articles from both academic and industry researchers are included. 

In the second part to our cryptoasset valuation primer, we survey five additional facets of the literature: fundamental ratios, UTXO age analysis, realized capitalization-based analysis, factor investing, and social media-based analysis. 

Fundamental Ratios 

The use of fundamental ratios is one of the most widely used approaches to cryptoasset valuation. Taking inspiration from the field of fundamental equity research (particularly ratios such as the price-earnings ratio), fundamental ratios are frequently used to determine periods of overvaluation and undervaluation. 

Woo (2017) was the first to make the connection that fundamental ratios could be applied to cryptoassets by introducing the network value to transactions (NVT) ratio, calculated as a cryptoasset’s market capitalization divided by its daily value transacted over the network. The logic behind this approach is that daily transaction value represents the usage and utility of a cryptoasset. High values of the NVT ratio have reliably detected bubbles and low values have indicated attractive entry points in the past. 

Kalichkin (2018a) extends the idea behind the NVT ratio by introducing additional smoothing to correct for certain shortcomings in the original formulation that prevent it from being used as a real-time trading indicator. Kalichkin’s version of NVT is often referred to as NVT Signal. 

Source: Coin Metrics Network Data Pro

Franek (2018) introduces a new ratio, based on a valuation derived from Metcalfe’s Law called the network value to Metcalfe ratio, which Kalichkin (2018b) extends by empirically testing on other similar laws. 

Arun (2018) also explores alternatives methods of smoothing and more precise estimates of daily transaction value. Combining ideas from both Metcalfe’s Law and the NVT ratio, the article introduces a network value to transactions to growth (NVTG) ratio. As a critical input to the NVT ratio, Coin Metrics (2018a) more precisely estimates transaction value by removing change outputs and non-economic transfers.

Bitcoin network momentum, introduced in Swift (2018), does not use a fundamental ratio, but instead introduces daily transaction value denominated in native units as a leading indicator for prices. 

Several other ratios have been proposed that are derived from miner revenue which represents the dollar value of capital that secures a network and a cryptoasset’s intrinsic value. Miners are also a consistent and significant source of selling pressure. For these reasons, Leibowitz (2018) defines a fee ratio multiple which provides a measure of how much of a cryptoassets security spend is dependent on block rewards versus transaction fees. And cryptopoiesis (2019) defines the Puell ratio as daily issuance divided by a 365 period moving average of daily issuance. 

Research using fundamental ratios touches upon many facets of the literature. Several additional fundamental ratios leveraging other inputs have been introduced in the fields of UTXO age analysis and realized capitalization ratio, including the the liveliness ratio, market capitalization to realized capitalization (MVRV) ratio, the spent output profit (SOPR) ratio, and the realized capitalization to transaction value (RVT) ratio and others. These areas of the literature and their associated ratios are discussed in the following sections. 

Fundamental ratios are perhaps the most developed thread in the literature due to their straightforward interpretation and application to market timing. Still, more work can be done in this area to address certain shortcomings. The most salient criticism points to reduced out-of-sample accuracy in predictions for some ratios such as the NVT ratio and the increasing tendency for more transactions to occur off-chain, either on second layer networks or within an internal ledger of an exchange or custodian. Furthermore, the extremely strong impact that the  bubble-and-crash cycle has on price means that any transformation (such as using ratios) that de-trends price tends to show excellent within-sample predictions but might not necessarily generalize well out-of-sample. 

UTXO Age Analysis 

Unspent transaction output (UTXO) age analysis is an area of the literature that studies the supply side of a cryptoasset by examining the behavior of holders. UTXO refers to the output of a transaction that a user holds and is able to spend by serving as inputs into future transactions. This accounting model is used by Bitcoin (BTC) and several other UTXO-based chains. Although the naming of this area of the literature makes specific reference to UTXOs, several of the concepts developed here have been successfully adapted to account-based chains, such as Ethereum. 

The earliest known contribution to this field was in ByteCoin (2011) where the term “Bitcoin days destroyed” was first defined as an alternative measure to transaction value. Bitcoin days destroyed is calculated as the number of BTC transacted over a period of time multiplied by the number of days since those BTC were last transacted. This gives a higher weight to coins that have not been spent in a long time, and less weight to coins spent more recently. For example, a coin that had not been transacted in 100 days is weighted 100x more than a coin that had been transacted 1 day ago. This fundamental insight, that inferences can be made by analyzing the age of last use for each coin, set the foundation for subsequent research. 

The following chart shows BTC transfer value weighted by days destroyed, smoothed using a seven day rolling average. 

Source: Coin Metrics Network Data Pro

The next significant contribution was in jratcliff63367 (2014), which partitioned the total supply of BTC into various bands based on the age of last use. In subsequent years, industry terminology has converged on the terms active supply or more informally, “HODL waves.”

The same idea was revisited several years later in Bansal (2018) which was instrumental in introducing active supply to a broader audience. The article was the first to draw inferences from active supply with respect to understanding and predicting market cycles and with applications to trading. 

Blummer (2018) defines liveliness as, using terminology introduced above, “the Bitcoin days destroyed divided by the total Bitcoin days that currently exist.” Liveliness provides insight into investor behavior by quantifying the behavior of long-term and short-term holders. 

Hauge (2019) presents several extensions to Bitcoin days destroyed, including adjusted binary Bitcoin days destroyed, value of coins destroyed, and reserve risk, all with applications to market timing. 

The unifying theory behind this approach to valuing cryptoassets is that different cohorts of holders may have differing motivations, risk tolerances, informational advantages, and sentiment depending on their holding time preferences. For instance, long-term holders hold a disproportionately large amount of the supply for many cryptoassets, and their behavior has large implications for price discovery. In our opinion, this area of the literature remains one of the promising areas in which more foundational discoveries can be found. 

Realized Capitalization 

Realized capitalization represents a novel, cryptoasset-specific approach to valuation that has significantly advanced the field of on-chain analysis. Unlike market capitalization, which values each coin at its current price, realized capitalization values each coin at the time of its last on-chain movement. For example, if 10 BTC were last moved when BTC price was $1,000, those 10 BTC would collectively be valued at $10,000 (10 x $1,000). If 5 different BTC were last moved when the price was $10,000, those 5 BTC would be valued at $50,000 (5 x $10,000).

Under an additional assumption that each on-chain movement represents a transfer of ownership between a willing buyer and willing seller, such that the price at the time of the transfer represents the cost basis of the buyer, realized capitalization can also be interpreted as the aggregate cost basis of all holders. 

While UTXO age analysis is concerned about the age at which a coin was moved on-chain, realized capitazalition-based analysis is concerned with the price at which a coin was last moved on-chain.

The core ideas were introduced in Coin Metrics (2018b) which provides a method of calculating realized capitalization for UTXO-based blockchains and account-based blockchains. The market capitalization to realized capitalization (MVRV) ratio is also presented in this article and is further explored as an indicator to identify periods of overvaluation and undervaluation in Mahmudov and Puell (2018). Awe & Wonder (2018) extends the MVRV ratio by applying a z-score transformation which allows it to serve as a more reliable trading indicator. 

Source: Coin Metrics Network Data Pro

Checkmate (2019) formulates the realized capitalization to transaction value (RVT) ratio which uses the same fundamental principles behind the NVT ratio but uses realized capitalization instead of market capitalization in the numerator of the ratio. 

Carter (2018) introduces thermo capitalization, a closely related concept of realized capitalization, which values each coin at the price at which the coin was originally mined. Under the assumption that miners operate at a long-term profitability equilibrium of barely above breakeven, thermo capitalization represents the accumulated security spend of the network. 

Puell (2019) introduces delta capitalization, a related concept that is calculated as the realized capitalization minus average capitalization (a cumulative, trailing moving average of market capitalization). A series of trading signals based on this indicator are explored with good within-sample performance. 

Similarly, Demeester, Blummer, and Lescrauwaet (2019) develops a measure to quantify the unrealized profit or loss of investors by calculating the market capitalization minus realized capitalization. Using liveliness, the article defines an indicator representing the change in long-term investor behavior. Shirakashi (2019) originated the spent output profit (SOPR) ratio by quantifying realized gains and losses and uses the ratio to predict local bottoms and tops. 

The realized capitalization line of analysis represents a truly cryptoasset-specific approach to valuation due to our ability to derive insights from the blockchain ledger. Being able to estimate the cost basis for all individual investors is a profound discovery (that is impossible to replicate in traditional financial assets) with serious applications to measuring investor sentiment and advancing the field of behavioral economics. Actively managed trading strategies that leverage deeply-rooted human cognitive biases and derived from realized capitalization insights are likely to be effective. 

Factor Investing 

Factor investing makes reference to models which identify specific characteristics of cryptoassets to explain returns. It further extends a very developed area of the literature in traditional financial assets, founded on Fama and French’s seminal work which identified three factors (market risk, size, and value) that explain U.S. equity returns. Since then, researchers have significantly expanded the field of factor investing by identifying hundreds of factors, not only in U.S. equities, but  in other geographies and asset classes. Cryptoassets are a natural next candidate of study. 

While other articles previously conducted cross-sectional studies to identify characteristics relevant to cryptoasset values, the first serious study using a traditional factor investing methodology was conducted in Hubrich (2017). It is the first known application of momentum, value, and carry factors to cryptoassets. The paper introduces innovative interpretations of value as the ratio of market value to on-chain transaction volume, and carry as the rate of supply issuance. The evidence suggests cryptoasset factor investing can earn excess returns. 

Liu and Tsyvinski (2018) significantly adds to the factor investing literature. It tests a wide number of traditional, macroeconomic, and cryptoasset-specific factors and finds evidence that a momentum factor and factors based on investor attention consistently explain cryptoasset returns but also finds a lack of predictive power for other factors. Kakushadze (2018) confirms the strong finding of a significant momentum effect and also finds lack of predictive power for a liquidity factor. Liu, Tsyvinski, and Wu (2019) extends the work on previously identified factors by introducing discussion regarding portfolio construction. 

Additional progress on this thread of the literature is dependent on the evolution of cryptoasset markets. Factor investing is concerned with evaluating large numbers of assets to determine characteristics that explain returns. Additionally, it seeks to construct portfolios consisting of many assets with exposure to certain factors. Therefore, the degree to which investors desire exposure and can obtain exposure to assets in the long-tail is important. The ability for researchers and data providers to identify conceptually consistent network data across assets, regardless of the underlying blockchain architecture, is also a prerequisite for further advances. 

Social Media 

The study of the relationship between the price of cryptoassets and social media-related data has a long history in the literature. Cryptoasset fundamentals are still only beginning to be understood (and the short history available to us shows that prices can deviate from fundamentals by a wide margin and for sustained periods), so quantifying investor attention is an active area of research. 

Kristoufek (2013) was the first article to use search query volume on Google and Wikipedia to serve as proxies for investor attention and to perform a study of its correlation to BTC’s price as well as tests on causation and co-integration. Garcia, Tessone, Mavrodiev, and Perony (2014) uses a broader set of data beyond search volume which includes Twitter and Facebook activity as well as data outside of social media. Two positive feedback loops are identified: one driven by word of mouth, and the other by new BTC adopters. 

Using a very similar methodology and an even broader set of data that includes several measures of on-chain activity, Georgoula, Pournarakis, Bilanakos, Sotiropoulos, and Giaglis (2015)finds that Twitter sentiment, among other indicators, has a positive short-run impact on BTC prices. A related study in Polasik, Piotrowska, Wisniewski, Kotkowski, and Lightfoot (2014) finds that BTC price returns can be explained by newspaper mentions, among other indicators. Mai, Shan, Bai, Wang, and Chiang (2018) present an empirical study using more updated data and concludes that social media sentiment is an important predictor for BTC prices. 

Conclusion 

Conventional wisdom states that cryptoassets are difficult to value because they lack a firm anchor to existing methods of asset valuation. But a close examination of the current state of cryptoasset valuation research reveals that this statement is not necessarily true. 

Over the past 10 years, existing concepts from classical economics, monetary economics, discounted cash flow analysis, fundamental equity research, and other fields have been successfully adapted to valuing cryptoassets. 

Simultaneously, several researchers have made noteworthy progress on cryptoasset-specific approaches to valuation which leverage on-chain data. An open ledger containing a historical record of all transactions allows for study of investor behavior, with unprecedented clarity compared to traditional financial assets. Foundational concepts upon which a formal discipline of cryptoasset valuation can be built have been established and many additional concepts likely remain undiscovered for the moment. 

Network Data Insights

Summary Metrics

Source: Coin Metrics Network Data Pro

The major cryptoassets had a big drop-off this past week amid a general market downturn. As fear continues to build about the spread of coronavirus, Bitcoin (BTC) dropped back below $9,000 and the equities market had its worst week since 2008.

Other cryptoassets fell even more than BTC. Ethereum (ETH) market cap dropped 12.7% week over week. Ripple (XRP), Litecoin (LTC), and Bitcoin Cash (BCH) all dropped between 14% and 16%. ETH and other smaller assets outpaced BTC in the recent run past $10,000, and it appears they may also be outpacing BTC on the way down.

Network Highlights

The percent of BTC untouched in at least two years is approaching levels unseen since mid-2017. As of March 1st, about 42% of all BTC has not been moved on-chain (i.e. transacted) for at least two years. The amount of BTC untouched in more than two years has not eclipsed 42% since July, 2017.  

Source: Coin Metrics Network Data Pro

There was not a large spike in transfer value days destroyed prior to the recent BTC price slide under $9,000. Although there were a few peaks in early February on the 3rd and 7th, there have not been any abnormally large spikes since. 

As covered in the Weekly Feature, BTC transfer value days destroyed is defined as BTC transfer value multiplied by the number of days since those BTC were last transacted. This gives a larger weight to transfers that involve coins that have not been moved in a long time. Spikes in transfer value days destroyed signal that long-dormant coins have been transferred, which could potentially precede sell-offs.

Source: Coin Metrics Network Data Pro

Market Data Insights

Cryptoassets sold off in concert with risk assets over the past week due primarily to the realization of the economic cost required to contain the coronavirus as the number of confirmed cases accelerate outside of China. During times when need for liquidity is high, reputed safe haven assets such as BTC and gold can be sold since liabilities can typically only be paid in fiat currency. Liabilities can take the form of margin calls in its most immediate form but also include debt service obligations like interest and principal payments. 

Source: Coin Metrics Reference Rates

Interestingly, BTC has seen a gain, along with global equities, after comments from the Bank of Japan (which held an emergency meeting on Monday) stating that they would take steps to stabilize markets. Such events should not be examined too closely in isolation due to the random walk that asset prices can take, but it continues to add to the body of evidence that BTC and the broader cryptoasset market do react to events beyond the immediate industry. 

Despite the sharp declines in cryptoassets, forced liquidations on BitMEX and other futures exchanges remain modest in sharp contrast to the pattern seen last year. Perhaps more dispersed volume across derivatives exchanges is lessening the impact of any one exchange. 

Realized volatility still remains moderate for BTC but a firm trend of increasing volatility for almost other assets remains. 

Source: Coin Metrics Reference Rates

CM Bletchley Indexes (CMBI) Insights

The best performing CMBI  index this week was the CMBI Bitcoin Index, despite its 14% drop. This is evidenced by the negative performance of all other CMBI indexes when denominated in BTC value.

After its record run of 9 consecutive weeks of positive performance, the CMBI Ethereum Index was one of the worst performing indexes, falling over 20% during the week. Of the multi-asset indexes it was the Bletchley 20 (mid-caps) that were most impacted experiencing a 20% fall.

Source: Coin Metrics CMBI Index

Despite the poor weekly performance, the CMBI Ethereum Index was by far the best performer in February, returning 25% for the month whilst most other indexes experienced between -5% and +5% returns. The CMBI Bitcoin Index was the worst performer of the month falling 6%.

Source: Coin Metrics CMBI Index

Coin Metrics Updates

This week’s updates from the Coin Metrics team:

  • Coin Metrics is hiring! We recently opened up 4 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.

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