Abstract: This is our third major piece on ICOs. In our first piece in September 2017 we focused on the interrelationships between ICO team members. In our second piece, in October 2018, we tracked the Ethereum balances in the ICO treasury accounts. In collaboration with TokenAnalyst, this piece focuses on the treasury balances of the ICO tokens themselves, on the Ethereum network. This report is based on tokens where the team controlled holding’s were worth an astonishing US$24.2 billion on issuance (in reality liquidity was too low for this value to be realized). Today this figure has fallen to around US$5 billion, with the difference primarily being caused by a fall in the market value of the tokens, alongside US$1.5 billion of transfers away from team address clusters (possibly disposals).

(Source: BitMEX Research)

(Note: A reminder of the various interconnections between ICO team members, from our September 2017 interactive graphic)

Team controlled token holdings (Own tokens) – summary data

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Price data up to Jan 2019, token data up to Dec 2018, based on data for 108 tokens)

Of the US$24 billion worth of tokens ICO project teams issued to themselves, 54% of the value has been lost due to coin price reductions. The peak valuation of the team holdings of their own tokens, using the individual price peak for each coin, is over US$80 billion. This larger figure implies US$70 billion of “losses” from the peak. Although peak valuation highly is dubious due to a lack of liquidity and most of the tokens were granted to the teams essentially for nothing, therefore classifying these price movements as losses may not be appropriate. Unlike ICO investors, the teams did not have an offering price or initial investment. However, some trading activity occurred at these ridiculously high valuations, therefore we believe it’s still interesting to consider these figures, while bearing these caveats in mind.

Based on current illiquid spot prices, the ICO teams still appear to own around US$5 billion of their own tokens, money they essentially got from nothing, depending on ones view. At the same time the teams may have realized gains of US$1.5 billion by selling tokens, based on coins leaving team address clusters. Although this figure may also be an overestimate, as coins could have left the team address cluster for a variety of reasons.

Data Caveats & weaknesses in calculation methodology

• The liquidity of many of these tokens is low and therefore the US Dollar values may be gross overestimates, this applies to both the initial allocation, current value and the value of any losses. In some cases, the value of tokens given to the team, for instance with projects such as Veritaseum or Noah, were almost comically large relative to the real trading volume in the coins. Therefore it can be considered unrealistic to value the team holdings based on the exchange price of the tokens.
• The challenge and uncertainty involved in producing this dataset surrounds the allocation of the tokens to the team address cluster. TokenAnalyst conducted this allocation. The methodology used was imperfect and we have not dug into individual projects. The data was obtained by analysing the token smart contracts and transaction patterns on the Ethereum blockchain and applying machine learning type techniques to establish a team controlled address cluster for the team of each project. The data is therefore a probabilistic estimate and is likely to be inaccurate at the individual project level. However, the primary motivation for this report was to produce macro data about the team holdings of ICO tokens on Ethereum. Although this analysis has produced results which are far from perfect, we believe one can draw reasonable macro conclusions from the analysis.
• As mentioned above, our analysis is based on reviewing smart contract data and transaction patterns, not documents and policies of individual projects. Therefore, it’s possible we included tokens as part of a team balance, although in reality they are held as part of another form of reserves, escrow or some other category, where it’s inaccurate to attribute the coins to the team’s own funds.
• The data assumes the issuance date is the same date as when the first price data appeared on Coinmarketcap, this may not be a reliable assumption.

Summary data

Value of coins issued to team controlled address clusters (own tokens) – US$ million – Top 10

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Token data up to Dec 2018, data based on prices at the time(s) of issuance)

Loss in value of team controlled holding (own tokens) – US$ million – Top 10

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Price data up to Jan 2019, token data up to Dec 2018)

Proportional loss in value of coins in team controlled address clusters (own tokens) – Top 10

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Price data up to Jan 2019, token data up to Dec 2018)

Value of coins transferred out of team controlled address clusters (Own tokens) – US$ million – Top 10

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Price data up to Jan 2019, token data up to Dec 2018. Huobi and Qash are exchanges and the tokens appear to have been sent to their respective platforms. It is possible the above figures represents sales/”cashing out”, although there could be other reasons for the transfers)

Current value of coins in team controlled address clusters (Own tokens) – US$ million – Top 10

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Price data up to Jan 2019, token data up to Dec 2018)

The raw data – Team holdings of own tokens – US$ million

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Price data up to Jan 2019, token data up to Dec 2018)

Conclusion & summary data

This analysis highlights the lack of standards and transparency in the ICO market, especially when it comes to the allocation of tokens to the founding team’s wallet. Teams were often able to mint, burn, buy, and sell (their own) tokens at will, without analysts being able to easily track what is occurring. We would often see tokens in exchange clusters, and it was hard to tell whether the token project “paid” the exchange to list tokens or the token project just transferred their treasury to the exchange to cash out.

To be fair, perhaps we could improve the analysis by spending more time reading the specific documentation of the individual projects and by speaking to the teams involved. This would have resulted in a more robust dataset.

But one thing about ICOs that many people often overlook, is that ICO teams often make profits in two ways from the issuance:

1. Selling the newly issued tokens (often for Ethereum), and,
2. Issuing themselves their own tokens.

Our October 2018 report focused on the former, while this report focuses on the latter. The summary table below combines the figures from both of our reports.

(Source: BitMEX Research, TokenAnalyst, the Ethereum blockchain, Coinmarketcap (for token prices))
(Notes: Ethereum price data to October 2018, Own token price data to January 2019)

Although, as we have repeatedly explained, there are many inaccuracies and assumptions involved in producing the data. Based on our methodology, it appears as if ICO teams have profited by almost US$13 billion from this ICO process. In our view, this money was made incredibly easily, with very little work, accountability or transparency. Therefore, ICOs have proven to be an extremely attractive way for project founders to raise funds. The results for investors of course, have not been as attractive.

The ICO cycle now appears to be dying down to some extent and it’s much harder to raise funds than it was in late 2017. But with so much money made and lost, the events of 2017 and early 2018 are not likely to be quickly forgotten. Entrepreneurs will remember the success (and keep trying to raise money) while investors will remember the pain. A repeat of this cycle within a few years is therefore less likely than many may think.

Abstract: In this piece, we look at a common problem facing both distributed exchanges and cross-chain atomic swaps: what we call the “inadvertent call option.” Non-custodial fully-distributed trading systems often inadvertently create an American-style call option, rather than the more simple desired operation of exchanging one asset for another. We review how this same issue applies to some specific distributed trading platforms like Bisq and particular cross-chain atomic swaps constructions. We then look at how IDEX solves this problem, but then requires users to trust the platform operator, to some extent, by removing some benefits of distributed exchanges. We conclude that despite the added complexity, in some circumstances it may be better to embrace the call option feature as a viable product, rather than ignoring or fighting it.

Overview

Alongside distributed stablecoins, distributed exchanges (DEXs) are often seen as one of the two holy grails within the cryptocurrency ecosystem. However, similar to distributed stablecoins, the challenges involved in DEXs are often underestimated. In this piece, we focus on one specific challenge with distributed exchange systems: instead of allowing simple exchange, these systems often inadvertently produce American-style call options.

The Theory Of The Inadvertent Call Option

When trading one cryptocurrency asset for another in any fully non-custodial system, one party must act first and the second party must follow. In theory, at some point, this second party then has optionality: – he or she can either follow through and complete the trade, or take no action and stop the trade. In the time interval between the first party taking the necessary action and the second party being required to act, if the price of the token the second actor is attempting to buy falls in value, or the price of the token he is selling increases in value, he could refuse to complete the trade. This means the following:

1. The trader who acts first has written an American call option on the spread between the two assets.
2. The trader who acts second has purchased an American call option on the spread between the two assets.

These exchanges can either happen atomically or as two separate transfers. Let’s consider Alice buying Bitcoin from Bob, using Litecoin.

As the table above illustrates, whether the trading is atomic or not, the same optionality principle applies.

One may think this is an insignificant issue, as the time periods can be short or the option value may be low; however, this is typically not the case: the option period is often around 24 hours and cryptocurrency prices can be very volatile. This high volatility is typically the reason traders wish to exchange the tokens in the first place. Therefore, the option value can be significant and impact trading.

It may be possible to mitigate or solve this problem by using more steps involving more deposits, but we have not yet observed a system achieving this. The other way to mitigate the problem is via the reputation of individual traders and a distributed web of trust-based systems, with traders revealing a form of identity. Traders can then lose reputation if they cancel trades based on price volatility. However, this may greatly increase the complexity of the systems, as functioning sybil attack resistant distributed reputation systems are also challenging to construct.

Below we examine three differently constructed distributed exchange type systems (or quasi DEXs) and explain how the call option problem arises.

Case Studies

Bisq

Summary table

Bisq (previously known as Bitsquare) is a peer-to-peer application, which enables one to buy and sell cryptocurrency with fiat money, as well as trade between crypto-tokens. Bisq is essentially a DEX, as traders connect to each other over a peer-to-peer network and transact with each other directly.

Bisq Daily Trading Volume (USD)

(Source: Coinmarketcap)

Screenshot from the Bisq platform

(Source: BitMEX Research)

Below we explain some examples of potential trading activity on Bisq and describe the resulting options.

Example 1: Acquiring Bitcoin with USD on Bisq

Alice wishes to purchase 1 BTC from Bob, using U.S. dollars:

• Step 1: Bob places 1 BTC in a 2 of 3 multisignature account. The three signatures belong to Bob, Alice, and a third-party arbitrator. This is Bob’s offer, which includes a price (e.g. US$3,800 per BTC).
• Step 2 – Alice can accept Bob’s offer by paying a small refundable deposit into another multisignature account. The fee is set by Bob (e.g. 0.01 BTC).
• Step 3 – Alice has 24 hours to conduct a bank wire transfer, paying US$3,800 into Bob’s account. If there is no dispute and the wire transfer occurs, Alice receives the 1 BTC and her deposit back. If no wire transfer occurs, Alice loses the deposit and the 1 BTC is returned back to Bob. Any dispute is mediated by the third-party arbitrator.

The above represents Alice buying Bitcoin; however, when considering the economic incentives involved, since Alice can back out of the trade with limited consequences, one could consider that, after step 2, she has acquired the following American-style call option:

Therefore, when Bob determines the value of the deposit Alice is required to pay, in theory he should consider Bitcoin’s volatility and use options pricing systems to ensure Alice is unable to acquire the option for a cheap price. Based on the prices currently available on Bisq, it appears many of these options are undervalued.

Example 2: Acquiring Bitcoin with Monero on Bisq

Alice wishes to purchase 1 BTC from Bob, using Monero (XMR):

• Step 1 – Bob places 1 BTC in a 2 of 3 multisignature account. The three signatures belong to Bob, Alice, and an arbitrator. This is Bob’s offer, which includes a price (e.g. 80 XMR per BTC).
• Step 2 – Alice  can accept Bob’s offer by paying a small refundable deposit and a fee set by Bob (e.g. 0.01 BTC).
• Step 3 – Alice has 24 hours to do an on-chain Monero transfer. If there is no dispute and the transfer occurs, Alice receives the 1 BTC and her deposit back. If no wire transfer occurs, Alice loses the deposit and the 1 BTC is returned back to Bob. Any dispute is mediated by the arbitrator.

Again, the above example may be considered as Alice buying Bitcoin; however, when considering the incentives, since Alice can back out of the trade with limited consequences, one could consider that she has acquired the following American-style call option:

If one is trying to capture the benefits of buying a call option with a low premium, this Monero trade may be more beneficial than the U.S. dollar version, since the Monero price is more volatile, and therefore the value of the option is higher. Since the Monero price is more volatile than Bitcoin, it may be more economically correct to conclude that Alice has acquired the following put option, rather than a call option.

As a trader, if one wants to take advantage of this structure, one could purchase these Monero puts for a low premium and then hedge the exposure by going long Monero on a centralised platform. However, Bisq has small position limits and therefore the size of the profit-making opportunity is limited.

Although it may make marketing the platform more challenging, it might make Bisq more robust to rebrand these trades as options and encourage sellers of Bitcoin to set the deposit price such that it’s consistent with the premium payment for the equivalent option based on the price volatility of the assets involved, for example by using the Black–Scholes model.

Cross-Chain Atomic Swaps

Summary table

We believe cross-chain atomic swaps were first described by TierNolan on the Bitcointalk forum in May 2013. Cross-chain atomic swaps allow users to exchange one asset for another atomically, such that the entire process either succeeds or fails. This allows for no risk for either party losing out by only one of the two transfers completing.

The following illustration describes the on-chain atomic swap process.  It is based on a swap between Alice and Bob, with Alice exchanging 1 Bitcoin for 100 Litecoin belonging to Bob.

Cross-chain Atomic Swap Construction

(Source: BitMEX Research)

As the table illustrates, although one is attempting to structure an atomic swap, similar to Bisq, it has inadvertently resulted in an American-style call option. The same issue appears to apply to either multi-currency routing via the lightning network or off-chain lightning-based cross-chain atomic swaps, during the construction of the channels. It could be possible to solve these issues with more steps and a longer series of deposits, although this added complexity may make implementation more challenging. Just as for Bisq above, it may be more appropriate for cross-chain atomic swap developers to embrace the call options and make it the product, rather than to try to brush this problem under the carpet or solve it with added complexity.

IDEX

Summary table

IDEX is an exchange platform using the Ethereum network. Traders deposit funds into an Ethereum smart contract, where the signature of both the traders and the IDEX platform is required to submit orders, execute trades, or make payments.

After a certain time horizon, users can withdraw funds from the smart contract without a signature from IDEX, which protects user deposits in the event that IDEX disappears. Order submission, order cancellation, and order matching is conducted off-chain on the IDEX servers, to allow for a fast and seamless user experience. The events are then submitted in sequence to the Ethereum blockchain and are only valid with a valid signature from the users. Therefore, IDEX is unable to steal user funds or conduct trades without user authorisation.

According to Dex.Watch, IDEX is the global number one Ethereum-based DEX, with an approximate market share of 50%. IDEX-type platforms are in many ways more advanced than the exchanges above as they can solve the call option problem by having both party’s funds partially held in escrow during the trading period.

IDEX Daily Trading Volume ( USD)

(Source: Coinmarketcap.com)

Although IDEX cannot steal user funds or conduct trades without authorisation, the order of events is determined centrally by IDEX. IDEX could fail to execute an order in a timely manner as well as front run orders or fail to execute an order cancellation in a timely manner. Therefore, while users are protected from some risks common in centralised exchanges, in practise they are still exposed to many of the risks most often talked about with respect to typical centralised exchanges. However, we still consider IDEX type platforms to potentially be a significant improvement compared to the fully centralised alternatives.  IDEX also has other limitations such as one can only trade Ethereum-based assets and the platform is eventually constrained by Ethereum network capacity.

Conclusion

In some ways Bisq’s model is more ambitious than IDEX and cross-chain atomic swaps. IDEX limits itself to tokens that exist on the Ethereum network while atomic swaps only deal with some cryptocurrencies. In contrast, Bisq attempts to handle fiat currencies such as the U.S. dollar. While solving the call option problem may be possible using Ethereum smart contracts or more complex lightning network constructions when, fiat currency is involved, it may be impossible to solve.

Of course atomic swaps and an IDEX type platform could work with US dollars if there is a working distributed U.S. dollar stablecoin. This illustrates how the two holy grails, distributed stablecoins and distributed exchanges, are interrelated. In a catch-22 type situation, each can only function robustly if the other exists.

Without a distributed stablecoin, in our view, when trading fiat currency for cryptocurrency through distributed systems, the use of call options could be inevitable. Bisq is potentially a useful distributed onramp into the cryptocurrency ecosystem; however, rather than trying to solve the call option problem, perhaps Bisq should embrace it. Maybe an effective onramp into the cryptocurrency ecosystem could be via American-style call options. While this may not be easy, it may be the only way to structure a robust highly censorship-resistant way in.

Abstract: Cryptocurrency prices have fallen significantly in the past few weeks. In this note, we analyse the impact this price decline may have on the mining industry. The Bitcoin hashrate has fallen around 31% since the start of November 2018, equivalent to around 1.3 million Bitmain S9 machines. We conclude that many miners are struggling; however, we point out that not all miners have the same costs and that it’s the higher cost miners who switch off their machines first, as the price declines.

Overview

Since the start of November 2018, the Bitcoin price is down around 45%, while in the same period the amount of mining power on the Bitcoin network has fallen by around 31%. According to our estimates, this represents around 1.3 million Bitmain S9 miners being switched off. The mining industry may therefore be under considerable stress right now, due to the falling prices of cryptocurrency.

The prices have so far caused two large downward difficulty adjustments to Bitcoin, 7.4% and 15.1%, on 16th November and 3rd December, respectively. The 7.4% adjustment was the largest since January 2013 and the 15.1% adjustment was the largest since October 2011. The charts below are based on the daily chainwork and therefore reflect changes in network difficulty.

Bitcoin Daily Work Compared to the Falling Price

(Source: BitMEX Research, Poloniex)

Daily Mining Revenue and Cost

As the chart below illustrates, Bitcoin mining industry revenue has fallen from around $13 million per day at the start of November to around $6 million per day, at the start of December. This drop in incentives was even larger than the fall in the Bitcoin price, due to a delay in the way difficulty adjusts. In the six-day period ending 3rd December, 21.8% fewer blocks than the expected 144 per day were found, as miners left the network before the difficulty adjusted, and as a result, fewer blocks were found. Therefore in the short term, there was a 21.8% fall in mining incentives on top of the impact of the declining price.

Bitcoin Daily Mining Revenue and Expected Electricity Spend – US$m

(Source: BitMEX Research, Poloniex)

(Notes: Assumes an electricity cost of US$0.05 per KWH, assumes advertised Bitmain S9 specification)

Bitcoin Cash ABC Daily Mining Revenue and Expected Electricity Spend – US$m

(Source: BitMEX Research, Polonies)

(Notes: Assumes an electricity cost of US$0.05 per KWH, assumes advertised Bitmain S9 specification)

Ethereum Daily Mining Revenue and Expected Electricity Spend – US$m

(Source: BitMEX Research, Polonies)

(Notes: Assumes an electricity cost of US$0.05 per KWH, assumes 32Mh/s at 200W)

Miner Profit Margins

The chart below shows that prior to the recent crash, the industry was making gross profit margins of around 50% (these figures assume electricity is the only cost included in gross profits), while after the price crash, this fell to around 30% for Bitcoin and 15% for Ethereum.

Miner Profit Margin

(Source: BitMEX Research, Poloniex for prices)

Ethereum Mining Profitability

In the period, the Ethereum hashrate has only fallen by 20%, much lower than Bitcoin, (representing around 1.5 million high-end graphics cards), while the price decline has been more significant than Bitcoin, at 54%. Therefore, gross profit margins have declined even more sharply for Ethereum, but it is not clear exactly why this is the case.

There are a few potential reasons. It could be that Ethereum miners are more hobbyist minded and less profit focused, or Ethereum miners could have started from a higher gross profit margin position than Bitcoin, so they are less inclined to monitor the network and switch the miners off when necessary. As the data shows, Ethereum miner gross profit margins now appear significantly lower than Bitcoin, falling to 15% in the last few days, so this could change (Note: This analysis only included electricity costs, when including other costs, mining may be a loss making operation).

Bitcoin Cash ABC Mining Profit Margins

As the above chart shows, the Bitcoin Cash ABC gross profit margin went negative during the split into two coins, Bitcoin Cash ABC and Bitcoin Cash SV. The two camps mined uneconomically in a race to have the most work chain. Ten days after the split, on 25th November, the profitability of mining Bitcoin Cash ABC rapidly climbed up to around the same levels as Bitcoin. This appeared to indicate the end of the “hashwar,” which proved to be almost completely pointless, as the war ending had no clear noticeable impact on either the coins or their value.

As the latest data in the below table shows, the two sides are getting closer again with respect to total work since the split and its possible uneconomic mining resumes.

(Source: BitMEX Research, Poloniex for prices)

Flaws in the Above Analysis

The above gross profit margin charts do not show a complete picture. While the revenue figures are likely to be accurate, the only cost included is electricity. Obviously miners have other costs, such as the capital investment in the machinery as well as maintenance costs and building costs. Therefore, although the charts below show that the industry is highly profitable when only considering electricity costs, given other costs, the recent price crash is likely to have sent almost all the miners into the red. This indicates that miners invested too much in equipment and have achieved large negative ROIs.

Electricity Cost is Not Uniform

Another crucial point not reflected in the above analysis is the variance in electricity rates. The charts above assume a flat cost of $0.05 cent per KwH; however, not all miners have the same electricity costs and there will be a distribution.

As we mentioned above, 31% of the hashrate was shutdown in the period, logically those with the highest electricity costs should turn off their machines first. Therefore the average electricity cost on the network should have fallen considerably in the past month.

The below chart is an illustration of the above, it assumes that electricity costs are normally distributed with a standard deviation of $0.01 per KwH and that higher-cost miners switch their machines off first. Although this assumption is likely to be highly inaccurate and energy prices will not be normally distributed across the mining industry, from a macro level it illustrates a point and it may be more accurate than the above chart.

According to this analysis, average Bitcoin mining gross margins have only declined from around 50% to 40%, implying a far more healthy situation for the remaining miners.

Bitcoin Mining Gross Profit Margin (Illustrative)

(Source: BitMEX Research, Poloniex for prices)

When evaluating the potential negative impact of price declines on Bitcoin, analysts sometimes forget that not all miners have the same costs. It is these cost variances that should ensure the network continues to function smoothly despite large sudden price declines and allows the difficulty to adjust.

What Caused the Price Crash?

There has been considerable speculation around the causes of the price crash, with some saying miners sold Bitcoin in order to finance a costly hashwar in Bitcoin Cash. The cryptocurrency intelligence monitoring platform Boltzmann flagged to us that their platform had detected unusually large miner selling of Bitcoin on 12th November, a few days before the Bitcoin Cash split.

Boltzmann detected that net Bitcoin sales from miners were “17.5 standard deviations below [the] 3-month trailing average.” On further analysis, it appears these miners may have been a member of Slushpool.

Bitcoin miner net flow & price

(Source: Boltzmann, 12 hour aggregation of miner net flow)

Conclusion and Price Commentary

While it may be true that mining pools selling Bitcoin to fund losses in the Bitcoin Cash hashwar may have been a catalyst for the reduction in the price, we think it’s easy to overestimate the impact of this. We are in a bear market and prices are falling regardless of the news or investment flows.

Furthermore, in a bear market prices seem to fall on non-news or bad news and ignore good news, while in a bull market the reverse appears true. We think it’s likely that prices would have been weak regardless of any miner selling prior to the Bitcoin Cash split. For cryptocurrency, trader sentiment is king.

This is likely to be a very tough time for the mining industry. However, for miners with lower costs, our basic analysis indicates that the situation may be better than people expect. If the miners acquired their equipment from Bitmain at below-cost prices, they could still be in the green, even when including depreciation and other administrative expenses.

Abstract: We evaluate Bitcoin Cash ABC’s new rolling 10 block checkpoint system. The new system does defend against “deep” hostile reorgs; however, it increases the risk of consensus chain splits and provides new opportunities for a would-be attacking miner. Another tradeoff is that the change increases the damage hostile miners can do to the network, but it reduces the potential reward for such behaviour. It is not clear at this point if this change is a net benefit, although it is a fundamental change to the system and it may therefore be better to spend more time assessing the dynamics involved before the network adopts this technology.

Overview

Bitcoin Cash ABC added a new rolling checkpoint system in software version ABC 0.18.5, which was released on 21st November 2018. Essentially, the new mechanism finalizes a block once it has received 10 confirmations, which prevents large blockchain reorgs. Therefore even if an alternative chain has more proof of work, if it conflicts with a checkpoint, the node will not switch over to the most work chain.

This feature may have been added as a defence against potential attackers including from supporters of the rival Bitcoin Cash SV chain, who have indicated they may wish to attack Bitcoin Cash ABC.

Security Analysis of the New Checkpointing Mechanism

The new rolling checkpoint mechanism includes a trade-off:

• The risk of a deep reorg is reduced.
• The risk of a consensus chainsplit is increased.

Network Risk Analysis of the New Checkpoint System

Attacking Miner: An Alternative Option to a Reorg

As indicated above, if a hostile miner is producing a shadow chain, once this diverges from the “honest” chain by more than 10 blocks, it is essentially useless as it cannot reorg the honest chain, even if it has more work. Therefore the attacker might as well give up and stop extending the shadow chain.

However, this also means that as soon as the 10th block since the split has been produced on the “honest chain,” the attacker might as well publish the shadow chain at this point, depending on the attacker’s objectives. (i.e. release the shadow chain as soon as the attacker receives the block in red indicated in the below diagram.) This could then cause a consensus chain split, with some nodes having received the red block first and some receiving the shadow chain first, resulting in conflicting checkpoints.

(Source: BitMEX Research)

This attack may cause a consensus chain split, which could be just as damaging to the network as continuing on to do a hostile reorg. It is also cheaper than continuing on to do a deep reorg, since the hostile miner can stop earlier. Therefore it is not clear to us why this new checkpointing defence is a material improvement. Although the risks in this section are unlikely to materialise (and could require the attacker to have a majority of the hashrate), they seem at least as likely to occur as the problem the new checkpointing system is trying to mitigate against.

Advantages of the Checkpointing System

• Although the new checkpointing mechanism may have a limited impact on security within a 10 block window, when looking back more deeply from the current chain tip, security may be increased over longer timeframes. This may be very useful to some exchanges or merchants who can now wait for more than 10 blocks before crediting a user account and achieve a higher level of assurance. However, a key focus of Bitcoin Cash is to increase transaction speeds, so this benefit may not be desirable for the Bitcoin Cash community.
• Although a new attack vector is opened up by this mechanism, providing a new way for hostile miners to instigate a consensus split as we explained above, the incentive to do this is less clear than for a “normal” deep reorg attack. A normal reorg attack can be used to initiate a double spend against an exchange, whereby the attacker could profit. While it is possible to also attempt a double spend attack using this new chain split-related attack vector, the outcome is less clear, as it is not obvious which side (if any) will be the winner or which chain an individual exchange may follow. Therefore, although this attack is potentially more devastating on the network, the incentives for it are less obvious. We view this as a significant positive.

Other issues

Centralisation and More Developer Power

Another common criticism of checkpoints is that it gives developers more power and increases centralisation since developers normally manually insert the checkpoints when they release new versions of the software (like Bitcoin used to have). However in our view, this does not apply in this case as the checkpoints are automatically generated by the node software and not manually generated by the development team. Therefore this a non-issue.

Long Range Attack and the Initial Sync

As Eric Wall explained on Twitter, the new checkpoint mechanism opens up the ability to sybil attack nodes not on the latest chaintip. For example, nodes still in the initial sync or nodes related to users who temporarily shut down their nodes for several days. An attacker needs to launch his own relay nodes and generate a new 10 block long chain at any point in the past.

This lower work chain can then be broadcast to nodes (including the specific targeting of nodes not at the current tip), potentially causing these nodes to conduct the checkpoint prematurely, on an alternative chain. Not only does this leave these nodes on a different chain, but this chain is under the control of the attacker. This seems to be a significant flaw of the checkpointing system.

Satoshi’s “original vision” appears to imply that the ability of nodes to be switched off and then verify what happened when it was gone is potentially important:

Nodes can leave and rejoin the network at will, accepting the proof-of-work chain as proof of what happened while they were gone.
(Source: Bitcoin Whitepaper)

To some extent this Bitcoin Cash ABC upgrade abandons that philosophy, and requires nodes to be online 24×7.

Conclusion

The new Bitcoin Cash ABC checkpointing system is a fundamental change to the core network and consensus dynamics, resulting in a number of trade-offs. These changes may not have been adequately explored before the upgrade. Although we do not think it is likely such a change will result in an immediate crisis, it’s not likely to prevent one either.

Overall Summary of the Checkpointing System’s Impact

Positives:

• Reduces the incentive for a miner to attack the chain
• Provides more assurances for merchants and exchanges for transactions with over 10 confirmations

Negatives:

• Increases the ability of a miner to instigate a devastating attack on the network
• Introduces new attack vectors on nodes which are still syncing to the main chain

Abstract: We present an in depth report into the cryptocurrency exchange ecosystem. The market is broken down by almost all the possible characteristics (Exchange type, exchange region and trading pairs). The robustness and authenticity of exchanges are evaluated  using metrics such as web traffic, average trade sizes, order book depth, security polices and price reliability. The report was produced by CryptoCompare and uses the CryptoCompare’s Aggregate Pricing Index (the CCCAGG), for much of the analysis.

(Note: Current CCCAGG Constituent Exchanges, Sized by 24H Volume)

Please click here to download a PDF version of CryptoCompare’s report

Executive Summary

Major Exchange News in October

• Bitstamp was acquired by Belgium-based Investment Firm NXMH for ~400 million USD according to reports.
• Cryptoassets on Gemini are now fully insured with Aon.
• Coinbase adds 0x to its trading platform as well as USDC after announcing its collaboration with Circle on the CENTRE Consortium.
• Korean exchange Bithumb starts a new DEX, while Huobi and OKEX list stablecoins GUSD, TUSD, PAX and USDC.
• Chainalysis will help Binance comply with anti-money laundering (AML) regulations around the globe, and
• Coinfloor becomes the first exchange to obtain a Gibraltar license.

Exchange Market Segmentation

Spot volumes constitute less than three quarters of total market volumes on average (less than 7 billion USD) compared to futures volumes (3.2 billion USD). BitMEX and BitflyerFX average more than one quarter of total volumes while traditional exchanges such as CME and CBOE constitute just under 1%.

Within total spot volumes, exchanges with taker fees represent approximately 90% of the exchange spot market volumes, while transaction-fee based and no-fee exchanges represent the remaining 10%.

Exchanges that offer fiat to crypto pairs constitute just under a quarter of spot market volumes on average (~2 billion USD) while exchanges that offer only crypto to crypto pairs constitute approximately three quarters (~4.7 billion USD). In terms of exchange count however, approximately half of all exchanges offer fiat to crypto pairs.

Transaction-Fee Mining Volumes

The top trans-fee mining exchange by average 24h volume was EXX (160 million USD), followed by Coinex (114 million USD) and Coinbene (113 million USD). The total average 24h-volume produced by trans-fee mining associated exchanges on CryptoCompare totals just over 550 million USD. This constitutes approximately 10% of total exchange volume over the last 30 days.

Decentralized Exchanges

The total average 24h-volume produced by the top 5 decentralized exchanges on CryptoCompare totals just under 2.4 million USD. This constitutes just 0.4% of total exchange volume. The top 3 on CryptoCompare by 24h volume include Waves Dex, IDEX and Dex.

Volume, Pairs and Coins

Binance remains the top exchange in terms of 24h volume with an average of 977 million USD. This is followed by OKEX (405 million USD) and Bitfinex (368 million USD). Yobit offers the highest number of pairs at 7,032, followed by Cryptopia (4,321) and CCEX (2,140).

Bitcoin to Fiat Volumes

The US Dollar represented half of BTC fiat trading on average over the past 30 days, followed by JPY (21%) and KRW (16%). Bitcoin trading to Korean Won (KRW) increased sharply after the 7th of October. The pair previously represented a tenth of bitcoin trading among the top 5 fiats on average. Between the 7th and 15th of October it represented a third on average, a 230% increase stemming from Korean exchange Bithumb’s spike in trading volumes.

Country Analysis

Maltese-registered exchanges produce the highest total daily volume at just under 1.4 billion USD, followed by those based legally in South-Korea (~840 million USD) and Hong Kong (~560 million USD). Among the top 10 volume-producing countries, the highest number of large exchanges (with significant volume) are based legally in the USA, the UK and Hong Kong. Binance and OKEX represent the vast majority of Malta’s volumes, while Bithumb and Upbit dominate in South Korea.

Trade Data Analysis

CoinEx, a well-known trans-fee mining exchange, has a significantly higher trade frequency and lower trade size than other exchanges in the top 25. This may point to algorithmic trading, given its almost 176 thousand trades a day at an average trade size of 125 USD. In contrast, Bithumb and HuobiPro had an average trade size of just under 3,000 and 1,500 USD respectively and significantly lower trades per day (12-18 thousand).

Web User Analysis

IDAX and CoinBene appear to have lower average daily visitors compared to similarly sized exchanges by daily volume. Binance has the highest average daily visitor count, in line with its high trading volumes. Meanwhile, exchanges such as Coinbase, Cex.io and Bittrex have significantly greater numbers of daily visitors than other exchanges with similar daily volumes. ZB and EXX attract significantly lower daily visitors than similarly-sized exchanges.

Order Book Analysis

ItBit, Kraken and Bitstamp have relatively more stable markets compared to exchanges such as CoinEx, ZB and Coinbene. These exchanges appear significantly less stable given their relatively low average order book depth values over the specified period of analysis.

Exchange Security

Out of the top 100 exchanges by 24h volume, only 86% have both a public privacy policy and a terms & conditions page. A third of top exchanges store the vast majority of users’ funds in cold wallets. Exchanges itBit, Coinfloor, Bitfinex and Coinbase are among those that store the highest proportion of users’ funds offline. As a proportion of the top 100 exchanges, 11% have been hacked in the past.

KYC

Just under half of top exchanges impose strict KYC requirements, while more than a quarter do not require KYC.

Total Exchange Volumes and Market Segmentation

This section aims to provide a macro view of the cryptocurrency exchange market as a whole. An area of interest is the proportion of spot trading vs futures trading historically. We will also assess the relative proportion of exchange volumes that represent exchanges that charge fees, as well as those that implement models with no-fees or trans-fee mining. Finally, we will take a look at exchange volumes that represent crypto-crypto exchanges versus those that represent fiat-crypto exchanges.

Historical Spot vs Futures Volumes

Spot volumes constitute three quarters of total market volumes on average.

Total spot volume averaged less than 7 billion USD, while futures volume averaged over 3.2 billion USD over the period of analysis.

Futures exchanges such as BitMEX (XBT to USD perpetual futures) and BitflyerFX (BTC to JPY futures) average just under a quarter of total cryptocurrency market volumes. Traditional exchanges such as CME and CBOE trading bitcoin futures, only constitute a very small proportion of the total market at just under 1% on average.

Historical BTC to USD Futures Volumes

BitMEX’s Perpetual Bitcoin to USD Futures volumes continue to dominate the Bitcoin to USD futures market

When compared to CME’s and CBOE’s futures volumes, BitMEX has represented an average of just over 90% of the market over the last month.

Historical Spot Volumes Segmented by Predominant Fee Type

Exchanges with taker fees represent approximately 90% of the exchange spot market volumes.

On the other hand, exchanges that implement transaction-fee mining represent just over 9% of the total spot market, while those that offer no-fee spot trading represent just under 1% of the market.

Historical Crypto to Crypto versus Fiat to Crypto Exchange Spot Volumes

Exchanges that offer fiat to crypto pairs constitute just under a quarter of spot market volumes on average.

Adjusted Historical Spot Volumes

The cryptocurrency exchange market trades an average of 5.26 billion USD in adjusted volumes over the period of analysis.

Adjusted spot volumes exclude all exchanges that operate trans-fee mining or no-fee trading models.

Historical BTC to Fiat Spot Volumes – Top 5 Fiat Currencies

Bitcoin trading to Korean Wan (KRW) increased sharply from the 7th of October.

BTC to KRW previously represented a tenth of bitcoin trading among the top 5 fiats on average. Between the 7th and 15th of October it represented a third on average, a 230% increase. This increase stems from Korean exchange Bithumb’s spike in volumes.

Proportion BTC Trading to Various Fiat Currencies

The US Dollar represented half of BTC fiat trading on average over the past 30 days, followed by JPY (21%) and KRW (16%).

Summary of Volumes, Coins and Pairs

Top Exchanges by Average 24H Volume in USD

Top Exchanges by Number of Pairs

Historical 24h Volume – Top 8 Exchanges

The top exchange by 24h spot trading volume was Binance with an average of just under 980 million USD.

By average 24h volumes, Binance was followed by OKEX and Bitfinex with volumes of 405 million and 368 million respectively.

Bithumb saw a 356% spike in trading volumes from an average of 140 million USD to an average of 640 million USD after the 7th of October. This follows after Singapore-based BK Global Consortium bought a controlling share in the exchange.

Bitfinex saw a spike in volumes towards the 15th of October as the Bitcoin premium on Bitfinex vs Coinbase reached an all-time high of 11.28% according to CrypoGlobe.

Month on Month Average 24H Trading Volume – Top Exchanges

Average Bithumb volumes increased 187%, while those for Binance and OKEX dropped by 8% and 35% respectively

Korean exchange Bithumb saw a significant increase in average trading volumes from 96 million USD between August/September to 276 million between September/October. Meanwhile, Binance’s volumes over the same time period dropped from 974 million USD to 893 million USD. Finally, the 2nd largest exchange by 24h volumes, OKEX, saw trading volumes drop 655 million USD to 423 million USD.

Country Analysis

Exchanges maintain operations in a variety of countries, in order to serve the wider global community of cryptocurrency traders. They often change legal jurisdiction to avoid regulation in countries that might restrict their abilities to conduct business as they wish. The following country analysis aims to highlight the top 10 legal jurisdictions by the total 24h volume produced by the top exchanges legally based in each jurisdiction.

Top 10 Exchange Legal Jurisdictions – 24h Volume vs Exchange Count

Maltese-based exchanges produced the highest total daily volumes, while the highest quantity of top exchanges are based in the USA and the UK.

Maltese exchanges produce the highest total daily volume at just under 1.4 billion USD, followed by those based legally in South-Korea (~840 million USD) and Hong Kong (~560 million USD). Among the top 10 volume-producing countries, the highest number of exchanges (with significant volume) are based legally in the USA, the UK and Hong Kong.

Top 10 Exchange Legal Jurisdictions – Constituent Exchanges by Impact on Volume

Binance and OKEX represent the vast majority of Malta’s volumes, while Bithumb and Upbit dominate in South Korea.

Top 10 Exchange Legal Jurisdictions – Constituent Exchanges and Count

Well-known USA-based exchanges include Coinbase, Poloniex, and itBit, while those in South Korea include Upbit, Bithumb and Coinone.

Hong Kong exchanges include HitBTC, CoinEx and Bit-Z, while those in more remote jurisdictions include HuobiPro in the Seychelles, ZB in Samoa and Coinbene in Vanuatu.

Pair Offering Analysis

The following analysis aims to highlight both the total volumes produced by crypto-crypto vs fiat-crypto exchanges as well as the total number of exchanges that fall within each category.

Crypto to Crypto vs Fiat to Crypto – Average 24H Volume and Exchange Count

On average, exchanges that offer only crypto-crypto pairs constitute approximately three quarters of the total spot trading market (~4.7 billion USD)

Those that that offer fiat-crypto pairs constitute only a quarter of the total exchange market (~2 billion USD) on average. In terms of exchange count, approximately half of all exchanges offer crypto-crypto.

Trade Data Analysis

This analysis aims to shed light on the trading characteristics of given exchange. It helps to answer whether an exchange’s volumes might be the product of consistently large trades, or the product of many small trades which may suggest the use of algorithmic trading or bots.

Average 24H Trade Frequency vs Average Trade Size – Top 25 Exchanges

CoinEx, a well-known trans-fee mining exchange, has a significantly higher trade frequency and lower trade size than other exchanges in the top 25.

This may point to algorithmic trading, given its almost 176 thousand daily trades at an average trade size of 125 USD. In contrast, Bithumb and HuobiPro had an average trade size of just under 3,000 and 1,500 USD respectively.

Average 24H Trade Frequency vs Average Trade Size – Top Exchanges

Web Traffic Analysis

This analysis examines the web traffic stats of the top exchanges within CryptoCompare’s total pool of exchanges. It is based on similar studies that have attempted to make a connection between the number of unique web users per domain and the subsequent 24h trading volume for that specific domain. This analysis assumes that the more unique visitors an exchange attracts, the higher its trading volume.

Average Daily Visitors versus 24H Volume – Alexa Rankings Above 100,000

IDAX and CoinBene appear to have lower average daily visitors compared to similarly sized exchanges by daily volume.

The figure above represents the top exchanges by volume that have an Alexa ranking above 100,000. The reason for this is that according to Alexa, any ranking below this may not be statistically significant.

What we can see that exchanges such as IDAX and CoinBene have lower Average Daily Unique Visitor numbers than other exchanges with similar volumes such as Kraken, Bitstamp, and CoinEx.

Binance has the highest average daily visitor count, in line with its high trading volumes. Meanwhile, exchanges such as Coinbase, Cex.io and Bittrex have significantly greater numbers of daily visitors than other exchanges with similar daily volumes. In Coinbase’s case, this can be attributed to the exchange’s reputation and age.

Average Daily Visitors versus 24H Volume – All Alexa Rankings

ZB and EXX attract significantly lower daily visitors than similarly-sized exchanges.

The above figure represents the top 20 exchanges by 24h volume regardless of whether their Alexa rankings are below 100,000. Noticeably, unique visitor counts for exchanges ZB and EXX are significantly lower than other exchanges within a similar 24h volume band.

These exchanges maintain average daily trading volumes of 248 million and 160 million USD
respectively. Despite this, their daily unique visitor counts amount to no more than 700 visitors per day.

Although there is a chance that these web statistics may present errors given Alexa rankings below 100,000, in the interests of mitigating any potential risks, these exchanges will be flagged until clarification is provided.

Order Book Analysis

The following order book analysis investigates the relative stability of various cryptocurrency exchanges based on snapshots of the average order book depth for the top markets on each exchange in 10-minute intervals over a period of 10 days. In the context of this analysis, average depth down is defined as the cumulative volume required (in USD) to reduce the price of a given market by 10%. This is compared to the average daily volume for the top 5 pairs. The result of this analysis is that we are able estimate the relative stability of a given exchange based on the ratio of depth down to average daily pair volume.

Average Order Book Depth Down vs Average Daily Exchange Pair Volume

In relative terms, CoinBene, ZB and CoinEx have the thinnest markets.

Despite relatively large average volumes per top pair (~12 million USD), CoinBene’s average order book cumulative depth down (order book buy side) totals only 33 thousand USD. In other words, to move the price 10% downwards, a trader would need to sell 33 thousand USD worth of currency.

In contrast, Kraken which has similar average daily pair volumes (~13.5 million USD), has an average order book cumulative depth of 4.2 million USD. This is almost 130 times larger than that of CoinBene’s and therefore suggests a much more stable exchange.

Average Depth Down to Average 24H Pair Volume Ratio

ItBit, Kraken and Bitstamp have relatively more stable markets compared to exchanges such as CoinEx, ZB and Coinbene.

In the case of ZB for instance, its depth to volume ratio was just 0.4%. I.e. in order to move the price down 10%, a trader would only need to sell 0.4% of average daily pair volume. These ratios are similarly low in the case of CoinEx (0.7%) and CoinBene (0.3%).

Meanwhile other exchanges such as Bitstamp and ItBit, had ratios of 30% and 40% respectively. This is a factor of 100 times greater than those of CoinBene’s for instance.

Transaction-Fee Mining Exchanges

Average 24H Trans-Fee Mining Volumes

The total average 24h-volume produced by trans-fee mining associated exchanges on CryptoCompare totals more than 550 million USD. This constitutes approximately 10% of total exchange volume over the last 30 days.

Decentralized Exchanges

Average 24H DEX Volumes

The total average 24h-volume produced by the top 5 decentralized exchanges on CryptoCompare totals just less than 2.4 million USD. This constitutes just 0.4% of total exchange volume.

Security Analysis – Top 100 Exchanges by 24H Volume

This security analysis aims to evaluate a pool of the top 100 exchanges by 24h volume considering the proportion of exchanges with both a public privacy and a terms & conditions page. In addition, we analyse the proportion of exchanges that have been hacked in the past as well as the publicly stated proportion of cold wallet vs hot wallet storage for users’ funds. In theory, the higher the amount of funds stored in “cold storage” (i.e. offline), the less exposed the funds held by a centralized exchange will be to hackers.

Proportion of Exchanges with both a Public T&C and Privacy Policy Page

Out of the top 100 exchanges by 24h volume, only 86% have both a public privacy policy and terms & conditions page.

Proportion of Users’ Funds Held by Exchanges in Cold Storage

A third of top exchanges store the vast majority of users’ funds in cold wallets.

Proportion of Users’ Funds in Cold Storage by Exchange

Exchanges itBit, Coinfloor, Bitfinex and Coinbase are among those that store the highest proportion of users’ funds offline.

Proportion of Exchanges Hacked in the Past

11% of top exchanges have been hacked in the past.

KYC Requirements Among the Top 100 Exchanges

Just under half of top exchanges impose strict KYC requirements, while more than a quarter do not require KYC.

Those that impose partial requirements (25%) require KYC verification in order to conduct certain activities such as to withdraw fiat, to trade fiat pairs, or to increase maximum trading amounts.

Trade Data Assessment of New Exchanges

A visual inspection of the trades on the new exchanges is now carried out. Snapshot data cannot capture volatility, so these trade graphs allow the characteristic trading to be assessed in light of its effect on the CCCAGG. Graphs were produced of all trades vs the CCCAGG for the top 5 trading pairs for each new exchange over the last month.

BCEX

BCEX displays high volatility on both of the pairs that it trades. Buying of large amounts of the order book is visible, suggesting a very thin market. The price on this exchange will accordingly not reflect the price of the cryptocurrency well, so it will not be included.

CoinTiger

Top trading pairs on CoinTiger display agreement with the CCCAGG, but due to anomalous volumes further monitoring will be carried out before considering inclusion into the CCCAGG.

iCoinBay

Pairs on ICoinBay show agreement with the CCCAGG. This exchange is a possible inclusion to the CCCAGG.

Iqfinex

A flash crash on the largest trading pair elicits a longer period of assessment before consideration for inclusion into the CCCAGG.

Liqnet

Pairs on Liqnet show agreement with the CCCAGG. However, large amounts of API downtime can be observed. The quality of the exchange API will be monitored and the exchange will be considered for inclusion in the event of an improvement in API provision.

P2PB2B

Poor agreement with the CCCAGG gives grounds to exclude P2PB2B.

StocksExchange

StocksExchange displays some unusual trading activity and a flash crash. The exchange will not be included due to trading behaviour.

Example Assessment of BTC to USD and Future Exchange Methodology Additions

This section provides a quantitative analysis of trade data received from exchanges. The purpose is to provide an understanding of what the exchange trading ecosystem looks like, and to allow for selection of exchanges that best represent the price of a cryptocurrency.

In order to make comparisons across exchanges, an estimate of the trading price of the cryptocurrency needs to be ascertained. For the BTC-USD pair, all trades over a 30-day period were collated and plotted. In this time period, there were around 6.5 million unique trades. The trades are plotted such that colour indicates the density of points in the area.

All BTC to USD trades over 30 days

This graph represents the entire ecosystem of the price of BTC-USD trading over a 30-day period. This is now used to generate a representative price for BTC. The median was selected to calculate a trading price for the cryptocurrency. The motivating factor behind this measure being used was the large number of outliers in the trade data set. To keep the computation tractable, trades were grouped into 1-hour long time bins, and the median for each of these bins was computed.

For the purposes of this investigation, volume weighting was not used. This was due to high volume buying up of order books being observed when looking at individual exchange trade data. It was hypothesised that the arithmetic median would better reflect the mid-price of the order books of the exchanges, as the majority of trades take place at the mid-price. The median should therefore reflect the price that the average trade was carried out at.

The 1-hour median line was then plotted on the trade data, and a visual inspection of a section of the above graph shows that the line follows the highest trade density, which is indicative that it is a good estimate of the trading price of the cryptocurrency.

BTC to USD trades over 30 days with hourly median price line

CryptoCompare’s CCCAGG is an aggregation of trade prices, and aims to reflect the current trading price of an asset. It is possible to validate the CCCAGG price by comparing it to the median trade price. It can be seen that there is agreement between the two measures, suggesting that the CCCAGG is accurately capturing the trading price.

CCCAGG Price vs Median Trade Price for BTC to USD