The design of Bitcoin and the blockchain, its public transaction ledger, make it challenging to distinguish specific types of transactions. Nonetheless, researchers from the U.S. Federal Reserve determined in a recent analysis that the currency is “still barely used for payments for goods and services.” Last week, nearly 200,000 bitcoins changed hands each day, on average. But fewer than 5,000 bitcoins per day (worth roughly $1.2 million) are being used for retail transactions, according to estimates by Tim Swanson, head of business development at Melotic, a Hong Kong-based cryptocurrency technology company. After some growth in 2013, retail volume in 2014 was mostly flat, says Swanson.
“Some of the New York Bitcoin Center guys are pretty religious,” says Tim Swanson, who has written two e-books on cryptocurrencies in the past year, most recently The Anatomy of a Money-like Informational Commodity: A Study of Bitcoin. Before that, while living in China, he built his own graphics-chip miners. (Some of his miners have since been re-purposed as gaming systems.) Swanson has grown increasingly skeptical that Bitcoin will unsettle the existing finance megaliths. “You have centralization without the benefits of centralization,” he says. Bitcoin’s promise of frictionless finance is drowning in the ever more immense cost of mining, user-friendly infrastructure, and appeasing regulators.
“Being your own bank sounds cool in theory,” Swanson says, “but it’s a pain in reality.”
In this episode, Meher Roy does a fantastic job explaining what a neutral, agnostic protocol actually is and why the current allotment of cryptocurrency “protocols” are not real protocols. Many thanks to Arthur Falls for his time, patience and great questions. We will all miss the show.
At the end of the day, that is ultimately the question that the Bitcoin community is asking when it asks, “what is the non-currency ‘killer app’ for Bitcoin?” And this could be akin to asking, “what is the ‘killer app’ for the Chinese economy?”
Because as described in a number of other posts, “Bitcoinland” — a “virtual-state” — probably has more in common with the economic dynamics of a “nation-state” than say, agnostic, inflationary computer protocols like TCP/IP/HTTP.
So what is the “killer app” for a meat space economy like China? How, as measured in GDP, did China grow from 364 billion RMB ($58 billion USD) in 1978 to 58 trillion RMB ($9.4 trillion USD) in 2013? Was it solely the result of Deng Xiaopeng efforts of “reform and opening up?” The full answer to that involves surveying numerous books; the shorter answer involved a combination of liberalizing a nearly fully autarkic economy and improving the productivity levels of existing inputs.
In the physical world, one way to measure how an economy develops is by looking at something called total factor productivity (TFP). An increase in TFP is largely a result of technological improvements, inventions and innovations. That is to say, for the same quantity of inputs, more outputs are created.
We see this frequently occur in developing economies as subsistence farmers adopt mechanization to improve agricultural yields, sometimes by several orders of magnitude. For instance, the 2011 harvest yields in Heilongjiang province China, broke nation-wide records, rising 11% over the previous year due to ‘bigger and better machinery for threshing and plowing’ (for more specifics see also: Wage Growth, Landholding, and Mechanization in Chinese Agriculture).
Historically, as an economy develops, the inputs (such as land and labor) become more productive and therefore produce more outputs. Can the internal Bitcoin economy also see such productivity gains?
Maybe, but probably not securely.
Let’s rewind for a moment. Because there is no land per se, let us instead look at the labor component of Bitcoinland.
Unlike the labor market in the real world, this virtual-state has a marginal productivity of labor of zero. It is very unique in that manner. That means irrespective of the amount of hashing power (or laborers) added or removed from the network, the virtual country will always (and only) produce a fixed amount of output (block rewards). Both David Evans and Tadge Dryja independently discussed this observation last year.
Simultaneously, this virtual country’s economic output is secured through proportionalism: ceteris paribus, in the long-run it should take a bitcoin to make a bitcoin. Rational laborers (miners) will not spend more than a bitcoin to make one. Thus if a coin is worth $250, miners as an aggregate will not spend more than $37,500 per hour to secure the ledger.
Recall that maintaining a distributed consensus network is different from consensus on a centralized ledger. Bitcoin was purposefully designed so that it is artificially expensive for people to cast “votes” for a consensus. The necessity was to make casting “votes” in the consensus artificially high since we cannot know who is participating in the “vote” (because it operates on an untrusted network).
What is another way to look at this?
I spoke with Jonathan Levin, formerly of Coinometrics. In his view:
The security model of Bitcoin is how much it would cost a malicious attacker to gain a significant portion of the network. The security model of Bitcoin is therefore an anti-Sybil attack mechanism and not necessarily focused on securing financial transactions. This begs the question: Is any financial transaction secure if the cost of reversing it is less than the value of the transaction. Or would we need a system in which it would cost $1 million to undo $1 million of value?
This question is difficult to answer in the abstract. For different use cases, there might need less proof-of-work needed in order to secure the transaction. There could be a few reasons for this. In many cases the issuer of the goods may be able to monitor the network for an attack waiting for sufficient work to be done before issuing the goods, e.g. Warehousing and physical delivery. For account balances, the victim could alter the balance of the attacker. There are very few $1 million transactions that are consumed instantly. However it does throw high value escrow services based in Bitcoin into question.
In the original white paper, Satoshi, albeit incorrectly calculated the probability of successful block reversals by an adversary. From this a magic number of 6 confirmations was often deemed as secure. I think this security model should be framed as burying a transaction under some dollar equivalent value of proof-of-work. This might give businesses more accurate view of the security of bitcoin transactions.
One unfortunate reality for assessing the security of bitcoin transactions is that we still need to factor in market concentration due to the possibility of bribes and corruption. Where some of these pools would actually find it profitable to attempt block reversals, a la selfish mining, it is difficult to think of an economic model for bribery and corruption in the Bitcoin network. Furthermore, we have seen the discussion take place on gated entry where you can make the entry into the validating nodes set super secure but someone may be able to bribe that entity to reverse / block transactions.
What does Levin mean by the cost of reversing a transaction?
To successfully disrupt the country (the network), the maximum cost to do so is roughly 0.5 x MC, where MC is the marginal cost of production.
In today’s terms to brute force the network — to attack it head on through its hypothetical ‘Maginot Line‘ it would in theory cost half of $37,500 per hour (or rather, half of the aggregate of 6 blocks as Levin suggested above) to obtain the magical “51%” of the hashrate needed to continuously double-spend.
In reality, the actual cost is significantly less due to out-of-band / side-channel / rubber hose attacks. But that is a topic for another article.
A parasitic unit of account?
In May 2014, at the Bitcoin Foundation Amsterdam conference, Robert Sams brought up two interesting points that involve Bitcoin as a developing country, the first involved deflation:
There is a different reason for why we maybe should be concerned about the appreciation of the exchange rate because whenever you have an economy where the expected return on the medium of exchange is greater than the expected return of the underlying economy you get this scenario, kind of like what you have in Bitcoin. Where there is underinvestment in the actual trade in goods and services. For example, I don’t know exactly how much of bitcoin is being held as “savings” in cold storage wallets but the number is probably around $5 billion or more, many multiples greater than the amount of venture capital investment that has gone into the Bitcoin space. Wouldn’t it be a lot better if we had an economy, where instead of people hoarding the bitcoin, were buying bitshares and bitbonds. The savings were actually in investments that went into the economy to fund startups, to pay programmers, to build really cool stuff, instead of just sitting on coin.
I think one of the reasons why that organic endogenous growth and investment in the community isn’t there is because of this deflationary nature of bitcoin. And instead what we get is our investment coming from the traditional analogue economy, of venture capitalists. It’s like an economy where the investment is coming from some external country where Silicon Valley becomes like the Bitcoin equivalent of People’s Bank of China. And I would much prefer to see more organic investment within the cryptocurrency space. And I think the deflationary nature of bitcoin does discourage that.
As I noted in a previous article, the $500 million that VC’s have deployed to build Bitcoinland are effectively a foreign exchange currency play (because it is a virtual-only foreign country that can only be accessed with a pre-paid card, bitcoin). This money is being paid to effectively leverage one economy, or rather one unit-of-account (namely USD, EUR, RMB) to build a virtual unit-of-account called BTC.
But because of a number of factors, including volatility and lack of native on-protocol financial services (such as credit facilities), bitcoins are not typically used to fund internal improvements (such as building the actual country of Bitcoinland). Or as Sam aptly noted:
I think the issue if should you have more elastic supply or not it just really comes down to the fact that if you have a fixed supply of something, the only way that changes in demand can be expressed is through the change in price. And people have expectations of increased demand so that means those expectations, expectations of future demand get translated into present day prices.
And the inelastic supply creates volatility in the exchange rate which kind of undermines the long term objective of something like cryptocurrency ever becoming a unit of account. And forever it will be a medium of exchange that’s parasitic on the unit of account function of national currencies. So I do think the issue does need to be addressed.
What does this have to do with “growing” the GDP of Bitcoinland? And more to the point, how can Bitcoinland increase the amount of outputs?
If the labor force in Bitcoinland, miners, are continuously expanding and contracting the amount of capital they destroy to secure the network (in concert with the market price of the token), then the size of the Bitcoin economy is continuously shifting in size each hour, day, week and month.
Or in other words, as measured in terms of several foreign unit-of-accounts (because the physical land, electricity and hardware are paid for in foreign currency): the size of Bitcoinland is directly proportional to the amount of fixed outputs. Denominated in BTC, the economy grows at an incrementally fixed rate. It cannot, due to deterministic rules, be more productive in terms of outputs. It can only grow larger and/or faster than this fixed amount through what amounts to ‘secondary issuance’ of watermarked metacoins such as Counterparty, Mastercoin and colored coins.
As described below, while this is not an issue today, these hacked-in under-secured metacoins are a double-edged sword. Why? Because these metacoins create a disproportional rewards vulnerability discussed last year.
Recall that metaprotocols (or sometimes referred to as ’embedded consensus mechanisms’) that utilize and sit on top of Bitcoin blockchain provide disproportional rewards. For instance, while both Counterparty and Mastercoin require participants to pay some nominal transaction fee, the social value of the actual asset itself if effectively piggy backing and free-riding off seigniorage rewards (this also happens with colored coins and Dogeparty). Aside from mining pools that use Luke-Jr.’s software, miners in general currently have no way to distinguish between a watermarked transaction from any other transaction.
Consequently, they have no incentive to destroy more capital to protect these metacoins in part because they receive no additional revenue to do so… because the network and coinbase itself has no knowledge of the social value placed on these metacoins and therefore cannot distribute rewards in proportion to the actual value being protected. And the network then is effectively top-heavy.
For example, if for some reason Apple Inc. decided to issue all of its shares onto the Bitcoin network via a metacoin, this could create a top-heavy security vulnerability. Recall that the total market cap of Apple’s shares is ~$750 billion USD but the labor force of Bitcoinland is only destroying enough capital to secure ~$3.46 billion in bitcoins (at the time of this writing $250 x 13.85 million mined coins).
Thus in the long run, miners are probably not destroying enough capital to ultimately secure metacoin assets, making the network less secure.
Or in other words, Bitcoinland — as it is encoded today — probably cannot securely increase its productivity levels (as would be measured by TFP) without opening itself up to some kind of vulnerability.
What about merged mining?
Last year I wrote a short working paper discussing the potential of merged mining as a way of productively reusing the existing capital base. In theory it sounds like an easy home run but in practice, if it costs miners nothing to merge mine, then it also costs them nothing to attack the merged chain/coin. Relying on and trusting in goodwill or altruism of a labor force is the direct antithesis of the game theory baked into Bitcoin itself: where it is assumed that all parties can and will be adversaries.
Empirically we have seen Bitcoin pools attack chains that have attempted to merge mine (see Coiled Coin).
We have also seen (above) how Namecoin’s hashrate has diverged over this past year and how it now consistently represents less than half of Bitcoin’s (note: Namecoin began merged mining with Bitcoin in October 2011).
This is due to at least 2 reasons:
1) not all Bitcoin pools support AuxPOW (merged mining) with Namecoin
2) also due to a block reward halving that took place in mid-December 2014 (notice that in contrast to the popular narrative, there was in fact no doubling in namecoin value because the market had already priced the future block halving into present day prices)
Or in other words, if it depends on the growth of an underlying unit-of-account hoping for an unseen Bitcoin GDP multiplier (or in this case a non-currency ‘killer app’) probably is similar to wanting something for nothing.
That doesn’t mean it shouldn’t be tried or that all the startups in this space are for naught. In fact, it looks like there are any number of useful innovations with practical applications (such as hierarchical deterministic, multisig, keyless wallets, etc.), including the experiments coming out of the altchain/ledger community. Several investors and entrepreneurs willing to navigate the space could see a good return if some of these innovations become integrated within other industries (such as financial services).
Yet in practice, operating a distributed consensus network based on proof-of-work seems to require an always changing capital allocation structure that is fused to the market value of its internal unit-of-account relative to national currencies. And based on the current version of the program, Bitcoinland itself (and not the ecosystem on the edges) may likely remain a laboratory model of a marginally subsistence nation that (often) violently moves between contractionary and expansionary cycles.
Other open questions
Aside from currency conversion, can there be a stable, secure domestic economy within Bitcoin. If so, what is or could be another identifiable, exportable good or service?
As its labor force (miners) must continuously exchange the domestic currency (BTC) into a foreign currency (USD, EUR, RMB) to pay for bills — what is the recent historical precedence of economies that start off subsisting off of a foreign unit-of-account that later manage to move on to become an independent unit-of-account for economic calculation purposes?
Can other Bitcoin-like cryptocurrency economies actually grow, or are they all faced with similar constraints with respect to proportionalism?
Existing metacoins require their own consensus systems and as such, they don’t fully rely on Bitcoin. Can this be further enhanced?
Earlier this evening I gave a new presentation to the Sim Kee Boon Institute (SKBI) for Financial Economics at Singapore Management University (where I am a new research fellow).
Covered a lot of ground over 2 hours, I am not sure if there is a recording but will post it if one surfaces. Below is the deck that I used. Many thanks to David Lee, Ernie Teo, William Mougayar, Mikkel Larsen, Taulant Ramabaja, Taariq Lewis, Dan O’Prey, Bobby Ong, Meher Roy, Richard Brown, Sidney Zhang, Dave Hudson, Jonathan Levin and Robert Sams for their feedback.
For the past two years, many entrepreneurs, developers, investors and enthusiasts have promoted the view that blockchains and in particular, Bitcoin will eventually be adopted as a universal value transfer mechanism — a type of global payment rail fit for a cornucopia of use-cases. Empirically this does not seem to be the case as over the past year and specifically the past 6 months, multiple startups have been created that specialize in areas that Bitcoin is not particularly well suited for. Whether any of these succeed is another matter entirely, but it is not a foregone conclusion that any one blockchain will be the “one to rule them all” based on their competitive (dis)advantages. This presentation outlines a number of vendors that have either announced or are working on solutions for the broader “Fintech” space as well as incumbent institutions in the existing ecosystem.
Recently the Museum of American Finance hosted an event covering Bitcoin. One of the panelists allegedly said: “we don’t think about infrastructure cost of VOIP because it’s approaching zero.”
I haven’t seen a video, so it’s unclear if this is a summation of their thoughts. But in terms of the infrastructure costs of Bitcoin, this is probably not comparing apples to apples because the incentives and costs to successfully attack the Skype network are very different than a network such as Bitcoin.
If the cost to maintain Bitcoin’s infrastructure is zero, so too is the cost to successfully attack and fork it. In fact, just about anyone motivated to do so could have successfully “attacked” (e.g., double spent or do a block reorg) the Bitcoin network in its first 18 months because the hashrate was relatively low because the value of the token was negligible (e.g., miners weren’t consuming additional units of capital because there was no financial incentive to do so).
For example, by the end of June 2010, the network strength (detailed here) was around 139 megahashes/second. To obtain half that hashrate, or 70 megahashes/second, an attacker would need to only spin up about 10 Xeon processors which could be obtained through AWS relatively cheaply (note: Satoshi probably used just onecomputer).
It was not until market participants increasingly valued the coin (vis-à-vis higher demand) which then in turn incentivized miners to destroy a corresponding amount of capital to protect the ledger. Or as one developer recently explained: the maximum cost to successfully attack Bitcoin’s network is directly proportional to the market value of the token. It is intentionally designed to be expensive to attack otherwise anyone could change the history. Or as Richard Brown has explained, proof of work as used in Bitcoin is “inefficient” on purpose.
The logistics of currency positions
In practice miners are taking one currency (USD, EUR, RMB), usually one denominated based on where the equipment is located, and through the process of destroying exergy (see Chapter 3), converting it into a foreign currency called bitcoin. Or in other words, miners are currency convertors. And irrespective of scale, “to mine” is effectively taking a long position on bitcoin versus a fiat currency (recall that the mining equipment and operating costs are paid for in foreign currency). For many actors, it is not just a forex bet but also a gamble on appreciation. As discussed in Chapter 3, there are at least two classes of actors willing and able to mine at losses, including some who hope that the token will appreciate in value.
I, along with several others, have written about this numerous times. In the long run, most miners, if not all, do not actually generate economic profit because of how the difficulty rating adjusts proportional to the amount of hashrate that is added to the network (e.g., the “Red Queen effect”). If it becomes cheaper to “mine” then the situation will simply incentivize more hashrate to be added resulting in a higher difficulty rating, negating the temporary advantage. In the short run, there are actual differences in margins due to differences in climate, electricity prices, administrative overhead, taxes, etc. Some, such as BitFury and a few in China, have better economies of scale and/or handsome land and energy deals due to guanxi (a few consequently have “cost of production” down to $80 per bitcoin and even lower as of this writing).
How the sausage is made
Unless you have mined some kind of coin before (see 12 Step Guide), in order to understand how mining actually works we must begin by noting that most miners are not actual miners, but rather hashers who effectively ‘rent’ their equipment to pools (pools charge a fee in exchange for this service). Miners, technically speaking, are the machines that actually select, process and validate a transaction. Hashing equipment does not do this.
For instance, CoinTelegraph recently ran a story on the new Raspberry Pi 2 Model B which costs $35.
This Pi computer (above) is effectively the only miner, the only “transaction processing” machine in an entire mining warehouse.
Since the entire Bitcoin blockchain can and is processed with something this cheap, why is mining so expensive then?
That is where Sybil protection and decentralization come into play. Recall that for the supply side of the equation, miners compete with one another to win the block reward (since it accounts for roughly 99.5% of their revenue, a figure which hasn’t changed much in a couple years, see below for more). Thus, rationally economic actors will strip a mining facility of anything that lacks utility (in some cases, even computer “cases” themselves). If it is not hashing, it is not helping to generate income. Thus in all warehouses today, they have row after row of specialized machines called ASICs to provide this spartan hashing function (recall this was all initially spurred on by ArtForz creativity). In practice, this hashing equipment actually just asks for a block header from the host node of a pool (such as the Pi Raspberry) and only “hashes” the “midstate” but that is another discussion entirely (see this excellent explanation from Vitalik Buterin). Thus, the only bona fide “mining” equipment in a facility is usually something akin to the Pi computer above.
[Sidebar: whenever someone claims that Bitcoin mining manufacturing pushed fabrication geometries to new limits, the reality is that designing a mining chip (or really, hashing chip) is actually, relatively simple: you only need a small handful of engineers to do it compared with say, a Xeon chip (which requires several hundred). In fact, most of the IP for SHA256 modules (or tiles) for “mining” equipment can be purchased from existing backend design companies.]
So what utility do those rows of ASICs provide then?
As shown in the video (above), the sole job of those single-use ASIC machines are to provide “proof of work” hashing power which thereupon provides Sybil protection for the blockchain. The video above was filmed in Liaoning province in China last fall by Vice magazine. Be sure to also read more details from Jake Smith’s article covering the same facility (he was also the laowai translating in the video).
The bigger picture
Recall that the estimated total deployed capital from VC firms over the past 18 months in the Bitcoin space is roughly $500 million into over 100 startups. And the direct financial rewards to miners over the same time frame has been roughly $780 million (3,600 bitcoins x 540 days x $400 weighted token price). This wealth transfer represents a large opportunity cost to the emerging economy that is Bitcoinland (one notable exception is BitFury, which invested in BitGo). Because instead of being able to hire software developers with that $780 million, it was used to fund exergy dissipation through:
Semiconductor firms such as TSMC
Utility companies (coal power plants in China, facilities in Washington, Finland and Ukraine)
Property and real estate agencies
Or in short, in an alternate universe in which Satoshi had created a different distributed yet secure consensus protocol (onethatmayor may not exist) in which the infrastructure costs did not directly scale in proportion to the value of the token, $780 million could have been instead used to hire 7,800 full-time developers (based on SF Bay wages).
But the Bitcoin network doesn’t need those developers, the current network can do everything the incumbents provide right?
Based on at least one post, Satoshi may have hoped to compete with Visa but he/she could turn out to be empirically wrong, there are real costs to maintaining a decentralized network. As it stands today, the Bitcoin protocol does not offer any of the actual banking and credit services of existing financial institutions. Consequently, recall that the expenditure and threat models on ‘trusted’ centralized networks are different than ‘untrusted’ decentralized networks. As I and others have described elsewhere, Sybil protection and decentralization add costs to operating a network — they do not in fact, make it cheaper. There is no free lunch or “free energy” in the mining process, anyone claiming that proof-of-work-based “mining” will somehow become ‘cheaper’ in the future is in the same class as the perpetual motion salesman.
Why is this important?
Another way to think about it: the $500 million that VC’s have deployed to build Bitcoinland are effectively a foreign exchange currency play (because it is a virtual-only foreign country that can only be accessed with a pre-paid card, bitcoin). This money is being paid to effectively leverage one economy, or rather one unit-of-account (namely USD, EUR, RMB) to build a virtual unit-of-account called BTC (see more from Robert Sams). But, and this is important for international adoption: there are no real corresponding exports from that economy (yet). Furthermore, there are several reasons why the narrative of social media enthusiasts will likely not go according to plan.
Bitcoinland – a large, virtual retirement facility
From a network sustainability perspective, Bitcoinland is a senior citizen and its trust fund (revenue base) is no longer in the “early days.”
Investor and entrepreneur interest may still be in the “early days,” but the asymptotical reward structure rapidly aged this economy into its twilight years much like early stars.
As of this writing, approximately 13.8 million bitcoins have been divvied out to miners over the past 6 years. This represents roughly 2/3 of the internal income the Bitcoin trust fund had at the beginning. More than half of the remaining will be apportioned in the next five and half years.
One common refrain is that at some unknown date and time, transaction fees will somehow increase and/or more users will collectively pay more fees. This is a possibility but is unlikely for the reasons discussed on numerous occasions for reasons described in this working paper (it is a type of collective action problem).
In fact, the biggest counterpoint to this is that we have direct evidence to the contrary.
The chart (above) illustrates the total transaction fees to miners (denominated in USD) over the past 2 years. Denominated in BTC, the 2 year chart shows the same trend line.
Fees to miners is actually at a 2 year low (in BTC) and not increasing despite the fact that there are now more than 100,000 merchants that accept bitcoin for payments (up from 20,000 last year).
Why is merchant adoption far outpacing consumer adoption? Well there are multiple reasons which I and others have discussed before. More on that later.
Perhaps there is another way to visualize this historically, from the beginning?
The chart (above) is from Organ of Corti and illustrates what I mentioned at the start of this post: that roughly 0.5% of a miner’s revenue comes from transactions (effectively, user donations), the vast majority still comes from the block reward.
But isn’t the retail economy booming and will balance this out? No.
As shown from Jorge Stolfi (and Coinbase’s own chart), on-chain retail growth is stagnant (in fact, it is one of the glaring omissions in Bitpay’s new infographic).
Why? Because most consumers are, in practice, not incentivized or otherwise interested in converting their local currency into a foreign currency for goods or services they can already buy with their existing currency. Endless threads on social media have proposed solutions to this inertia, but the fact of the matter is in practice, consumers are only willing to change if and when the alternative is not just as useful, but significantly so (there is an entire segment of economics that studies consumer choice and indifference curves). And they are only going to use something if it provides them more utility. Thus to them, entering Bitcoinland (and current cryptocurrencies in general) is a friction they have preferred to avoid. Perhaps that will change, but then again, maybe not.
Again, recall that the primary utility provided by the Bitcoin blockchain was to circumvent trusted third parties (TTP), which in practice, the average consumer are okay with having to deal with (the tradeoff between less privacy for more insurance, etc.). For instance, in terms of demographics, the vast majority of gamblers that use bitcoin are based in the US because online gambling is illegal here. European gamblers typically use bank transfers. When SatoshiDice blocked US-based IPs, gambling volume dropped significantly for them (and flowed to other similar sites). Maybe there will be another “killer app” but then again, maybe blockchains in general attract illicit activities because their decentralized nature enables routing around TTP, which some bitcoin holders find useful and attractive.
Circular flow of income
One last issue that intersects with miners and the Bitcoinland consumer economy is that of volatility. This is a topic that generates enormous reaction and I am aware of companies such as Bitwage, Hedgy, Teraexchange that are attempting to create either hedging mechanisms against volatility and/or bridges between two different unit-of-accounts.
Ignoring the impact of the Poisson process, there is never a dull moment for being a cryptocurrency miner (professional or otherwise) as you never have a really good idea of how much capital to deploy in the future due largely to the continuous uncertainty over what the future market price of a coin is and what the difficulty rating may adjust to. Or as Robert Sams aptly noted:
It is the nature of markets to push expectations about the future into current prices. Deterministic money supply combined with uncertain future money demand conspire to make the market price of a coin a sort of prediction market on its own future adoption. Since rates of future adoption are highly uncertain, high volatility is inevitable, as expectations wax and wane with coin-related news, and the coin market rationalises high expected returns with high volatility (no free lunch).
Yanis Varoufakis, the new finance minister for Greece, has written about the monetary supply schedule challenges within Bitcoin severaltimes. One notable quote he had last year involved how speculative demand for bitcoin outstrips transactional demand:
“By a long mile. Bitcoin transactions don’t go beyond the first transaction. The people who have accepted bitcoins don’t use them to buy something else. It gets back to the circular flow of income. When Starbucks not only accepts bitcoins but pays their workers in bitcoins and pays their suppliers in bitcoins, when you go back four of five stages of productions using bitcoin, then bitcoin will have made it. But that isn’t happening now and I don’t think that will happen.” Because it isn’t happening now, he continues, and because so many more people are speculating on bitcoin rather than transacting with it, “Volatility will remain huge and will deter those who might have wanted to enter the bitcoin economy as users, as opposed to speculators. Thus, just as bad money drives out good money, Gresham’s famous law, speculative demand for bitcoins drives out transactional demand for it.”
What this has looked like in practice is that miners themselves are creating a currency with which they are not necessarily able to pay their electricity bills or leases with. They have to convert it. Perhaps this will change, but since the bulk of this virtual currency has to be converted into a foreign currency (USD, EUR, RMB), it creates continuous sell-side pressure on the market (see How do Bitcoin payment processors work?). And without a corresponding increase in demand from those holding foreign currency, the market price declines.
Hedging may help mitigate some losses for a few of the merchants that choose to keep and not convert bitcoin payments they receive, but again, hedging isn’t free. It also costs someone something to do — hedging can be expensive, this is why corporates do not typically hedge against ongoing foreign revenue but they only hedge against large one-off items (such as acquisitions, or large shipments / purchases). Just ask the airline industry about its fuel hedging strategies. Recall again that consumers in general prefer stable purchasing power for medium’s-of-exchange (no one is trying to directly use petroleum as a currency).
Without a circular flow of income, this is unlikely to change and this is something that requires years, perhaps even decades to build even with dynamically adjusted, elastic money supplies. For instance, recall even with its $9.5 trillion economy and its $2 trillion in exports, the RMB only represents 2.17% of all international trade settlements (for comparison, the Greeks exported €27 billion in goods and services in 2013). Perhaps indeed, Bitcoinland is still in the “early days” — or maybe its fixed monetary supply has inflicted it with incurable progeria (i.e., few want to spend it, so not enough fees to replace the block reward). And thus its main exports will continue to be ways to distribute exergy via currency conversion processes and illicit trade.
Is all lost?
Earlier this week William Mougayar encouraged advocates in this nascent space to basically chill out with the moon rhetoric. Again, it is impossible to know what consumers will eventually adopt. Anyone claiming that there will just be “one winner” that encompasses all use-cases is probably wrong in the short run (note that Richard Brown and Meher Roy have suggested that there may be some kind of “Grand Unified Theory” of cryptofinance but that is a topic for another post).
Every business, institution and customer has different wants and needs that will dictate actual adoption of technology and not the other way around. Entrepreneurs, developers and investors cannot assume a market will adopt their own narrative any more than shipwreck survivors can “assume a boat” — thus as Mougayar has touched on: blockchains and consensus ledgers may find traction outside of niches only if they satiate mass consumer appeal, not just hobbyist interest.
To the chagrin of the heavily invested, Bitcoin may prove to be the vehicle that will spawn a variety of useful mainstream tech but that will never actually go mainstream itself. In that respect, perhaps Bitcoinland is essentially a huge R&D program. Perhaps this is a modern facsimile of The Rise of ‘Worse Is Better.’ Bitcoin enthusiasts believe that they are the “New Jersey” crowd in this particular story but in truth they may be taking the “MIT” approach, where they are seeking to build a perfect new financial platform. The lesson of the story is that the MIT approach almost always fails because it is incredibly hard to do and relies on perfect up-front understanding, while the New Jersey approach favors incremental discovery and evolving things towards something that works well enough.
Or maybe, conversely, some black swan event such as a large hedge fund publicly announces major buys or an ETF is approved or large-scale regulatory clarity occurs (see also: the Bitcoin Bingo card); we can only know in retrospect.
In the meantime, other mental models are being discussed including a separation of specialized distributed ledger systems (via consensus-as-a-service) from the current crop of cryptocurrency systems as well as proposed a dual-currency solution (such as Seigniorage Shares) that could end up implemented in other projects such as Augur’s prediction market: it could also be used for CFDs, it does no one any good if the underlying currency is too volatile to price contracts in — even if you “win” you could still lose due to currency depreciation (this is not an endorsement).
Other ideas such as the new replace-by-fee patch targeted at providing a mechanism for miners to prioritize transactions or metacoin censoring tools to allow mining pools to filter out watermarked coins (colored coins, Counterparty, etc.), will undoubtedly provide empirical feedback to future ledger designers on what to do and not to do.
Welcome to Bitcoinland, a virtual world whose artificial age is more akin to Sumter County than Madison County and whose primary export is currency conversion via exergetic displacement. On-chain population: roughly 380,000.
Over the past couple of months there has been a number of discussions revolving around increasing the Bitcoin block size from its current 1 MB limit to 20 MB. One such plan is Gavin Andresen’s proposal (this is not to single him out as there are others with similar proposals). The code change itself is trivial, as it can simply be changed to any arbitrary number in a couple of keystrokes (for instance, see Vitalik Buterin discuss this at 14:15).
However, getting the majority of validating nodes, miners and the rest of the ecosystem on-board in a timely fashion is a very non-trivial matter.
Recall that, as illustrated by Organ of Corti and Dave Hudson, the average block size has increased over the past year to the point where we will likely max out at around 3 transactions per second with the current 1 MB limit. Since many of the investors, developers and entrepreneurs in this space would like to make Bitcoin ‘competitive’ to other payment platforms such as Visa, according to their view, this number eventually needs to increase by several orders of magnitude.
Fundamentally there are two trade-offs in block size economics:
Keeping a 1 MB block size requires higher fees to end-users but results in a more decentralized network
With a larger, 20 MB block size, fees are (temporarily) subsidized to end-users but with fewer validating nodes on the network
A quick explanation of both:
Retaining a 1 MB block size ultimately results in higher transaction fees because block space is scarce and miners will only process and include transactions based on market-based prioritization rates (e.g., pay higher to be included faster). While this would likely mean the end of certain types of transactions (such as “long chain” transactions) as well as fee-less transactions which have disproportionally increased the size of the blockchain over the past six months relative to actual commerce, simultaneously this design decision would have the effect of retaining some nominal decentralization as the increase in blockchain size would remain relatively linear and thus the blockchain could be validated by several thousand nodes as it is done today without (much) additional cost.
In early March 2014, there were approximately 10,000 nodes however over the past year there has been a decline by roughly 1/3. What does this distribution of roughly 6,400 current nodes look like?
Recall that the original value proposition of the Bitcoin blockchain was its decentralized characteristic, thus the more miners and validation nodes that are geographically distributed, the less prone the network is to single-points of failure. Furthermore, while many people call the various artifacts that have increased the blockchain size “bloat,” because this is a public good and no one owns it, it is imprecise to do so (e.g., one man’s 80 byte “trash” OP_RETURN is another man’s data storing “treasure“).
Whether consumers are sensitive to this change in fees is another matter due to elastic demand, they may simply switch over substitute goods (e.g., competing chains and ledgers). What does this mean exactly?
An increase to a 20 MB block size would likely continue the same “low” fee (donation) structure practiced and promoted today as there is purportedly more room for non-priority transactions. The known challenge however is that if 20 MB blocks became “filled,” this would require a corresponding increase in bandwidth and disk space which would require more costs to be borne by the validating nodes which are already operating as public goods. That is to say, a blockchain that increased in size by 20 MB every 10 minutes would fill over 1 terabyte a year which would create additional costs for participants and likely reduce the amount of verification nodes and therefore reduce the decentralization of the network.
The other challenge to Andresen’s plan is, that because the prioritization of transactions would still not be adjusting towards via fees to miners, this would in turn continue the status quo in which miners continue to largely rely on seigniorage to operate. This is an unhealthy trend as it stalls the transition from block rewards to fees which was the narrative stated since day one on October 31, 2008 (see section 6).
What will happen?
It is difficult to predict what exactly will happen as the key actors in this space are still deciding what to use social capital on.
Gavin Andresen, as recently as two weeks ago, stated that most of the large payment processors, exchanges and other service companies are on-board with his plan (see also David Davout’s recent dialogue with Andresen). Furthermore, others in the community have (likely erroneously) found correlation between market cap and transaction volume yet as we know, correlation does not actually imply causation. Similarly, ‘Death and Taxes’ recently presented a narrative reinforcing Andresen’s view yet for some reason glossed over the all-important miners perspective. Others, such as in the ideological wing personified by Mircea Popescu claim that they will fight this effort with an actual attack.
Irrespective as to what size a block is increased to, it will likely create at least a temporary fork as validating nodes need to upgrade and they are not being compensated for storage and traffic (Andresen’s plan is to “future proof” the protocol such that the 20 MB change is included in a patch this year but isn’t “turned on” until needed later on). There is at least one open question: what is the minimal amount of full nodes that are required for network to operate within current trust/security model? Unlike miners, their value to the system is hard to measure.
What the experts say
While the field is young, one expert in this space is Jonathan Levin who modeled network propagation in his masters thesis. I reached out to him and in his view:
I think that the 20mb proposal is untenable given the current way that blocks are propagated around the Bitcoin network. The Bitcoin network and specifically the Bitcoin miners use a gossip network to relay blocks to each other. That means that as the size of the block increases, the time that it takes to spread around the network also increases linearly. We have seen this first in the work of Decker and Wattenhofer as well as my own work.
The problem is that the increased time that blocks take to propagate around the network increase the probability of orphan races between different mining pools. If you create blocks that are 20mb and a competing pool is creating blocks under 1mb or even empty ones, they have a higher expected return per hash. This is because you would expect your blocks to lose out to smaller blocks in an orphan race if both are found in quick succession. Now we can argue that miners will continue to create large blocks out of altruism but if we continue to increase the size of the blocks without greater utilisation of better block relaying protocols we risk breaking this equilibrium and miners resorting to nasty strategies like creating empty blocks which suit no one.
I also spoke with several other professionals in this space.
On the one hand, increasing block sizes, as you say, may result in lower transaction fee requirements. However, if the transaction fees actually are lowered by, say, 1000x what they are now (0.00001 is the minimum accepted by the reference client), this will lower the cost of “institutional attacks” on the Bitcoin infrastructure, where an attacker can push 1000 transactions for an erstwhile cost of 1. The attack will basically be “make infrastructure expensive to run for the average joe, drive them towards centralized infrastructure services that run APIs, Blockchain Explorers, etc.” It is good for business, bad for the decentralization of the network in the near term.
We’ve seen something like this occur on the Dogecoin Network in the past few months, where one user or a group of individuals were pushing transactions with 0 transaction fees. These transactions were accepted as valid by the Dogecoin reference clients, and as a result, caused bandwidth consumption hikes for the dorm-room nodes, which populate most of the current network(s). The resulting change by the Dogecoin Core team was to add a fee of 1.0 DOGE for every transaction, which isn’t yet mandatory, but is on its way there. The dorm-room nodes, however, are already on the decline in both Bitcoin and Dogecoin due to the increasing size of the Blockchain, and the bandwidth consumed by them.
Increasing the Block sizes sounds like a good idea for the number of transactions flowing on the network, but in the near term it will drive a lot of the nodes out of the system because of CPU/bandwidth/disk IO hikes. Increasing the Block sizes will definitely increase infrastructure costs, driving more users towards centralized places that can afford to host API services for the Blockchain. However, given this crunch on the average joe Bitcoin nodes, this will lead to a more concentrated effort towards “pick what you need” style nodes (say, SPV). Again, in the near term, the number of “full nodes” on the network will dwindle, but as more companies come into the ecosystem, this number will inevitably rise.
Bitcoin as a whole is headed towards a network where most nodes don’t actually host the entire Blockchain — increasing the block size will only accelerate this change. This will lead to more innovative solutions, and who knows, we might find a way for nodes to communicate cost-effectively rather than the current “gossip”-style protocol we use, where you inform all your peers when you hear about a new transaction. The community can very dynamic, and I think the longer term outlook for the network looks good regardless. Bitcoin is powered by nerds like you and I, and we tend to find solutions where others walk away.
Nazir raises an interesting point in terms of a hypothetical time horizon for when a transition (between short term and long term) could take place.
Another individual who has done a lot of modeling of incentives, mining and block sizes is Dave Hudson, a software developer who also writes at HashingIt. According to him:
Changes to the distributed consensus software within Bitcoin raise really interesting questions about the evolution of cryptocurrencies and how truly decentralised they really are. With each change we’re actually seeing something interesting happen where the ongoing participants in the system all effectively agree to move to a new system: BTC becomes BTC’ becomes BTC”, etc. We might be calling BTC” Bitcoin but any legacy nodes running BTC’ or BTC also think they’re Bitcoin too. At some point in time something happens and the various systems start to disagree about what is or isn’t valid and those could be very subtle. Imagine for example that BTC” introduced a subtle change that inadvertently made some of Satoshi’s coins unspendable; nobody might ever know until someone with Satoshi’s keys tries to spend their Bitcoins. Arguably it might already have happened as the result of some random compiler bug (not a fault in the Bitcoin-core code, but a bug in the way that’s transformed into something that runs on the node CPUs).
Clearly the Bitcoin-core developers try very hard to ensure that this sort of thing doesn’t happen by accident, but in order to sustain all participants holdings within the system they really do have to try to ensure that every node moves from BTC to BTC’ to BTC”, etc. In order to do this they essentially have to persuade everyone to migrate to each new version within some specific time window.
Now let’s imagine for a moment that instead of miners all tending to mine through centralised infrastructure (mining pools), that we really did have true decentralisation and had hundreds of thousands, or millions, of nodes that all did their own transaction selection and mining. Perhaps they’re even embedded into things that their users didn’t even realise were contributing to mining. At this scale it would probably be almost impossible to get them all to move to adopt a planned fork. We would either see the protocol totally stagnate or else we would see potentially very significant forks occurring.
In practice the system holds together in a cohesive way because, in the absence of a precise protocol spec, the core devs try to ensure that everyone uses the same consensus-critical software, runs it on the same sorts of hardware that all do things the same way and with some reasonably consistent set of capabilities.
It’s seems a slight irony that one of the key factors in the successful maintaining and sustaining of the Bitcoin network is continual centralised actions, and that things aren’t actually massively decentralised.
This last point is intriguing in that a lot of the software in this space is still relatively homogeneous and that if a network were to scale to become as distributed (or decentralized) as is hoped while simultaneously incorporating many nodes and clients, then it is likely that a diverse set (or lackthereof) of developer tools could prevent or perhaps even incentivize attacks (e.g., if every actor in the ecosystem uses the same client then that could create a vulnerability to the network).
In an exchange with Peter Todd, a contributor and developer on Bitcoin core and other related protocols (such as ClearingHouse), he framed the issue:
At the recent O’Reilly Media conference basically I pointed out that because this is an externality / tragedy-of-the-commons problem we may have to see Bitcoin fail due to a blocksize increase first before the community actually groks the issue. Personally I’m inclined to not oppose a blocksize increase on this grounds – Bitcoin failing cleanly is probably good for my interests.
In terms of “getting people on board” – to a degree you inherently can’t do this, because a blocksize increase will inherently exclude people from the system. See for example the discussion between Greg Maxwell and Gavin Andresen several weeks ago on the #bitcoin-dev IRC channel.
I spoke with Robert Sams, co-founder of a fintech startup who has previously written analysis covering the marginal costs of Bitcoin-like systems. In his view:
Levin’s point about network propagation is key: mining a larger block has a lower expected return because of the increased probability of losing out to a smaller block in an orphan race.
Now all of what you argue is a totally sound economic conjecture based on the assumption of distributed mining economics. Miners include tx until the marginal cost of tx inclusion (opportunity cost of including a different tx when up against the block limit + block propagation effect) equals marginal revenue (the fee).
However, for me the crucial economic force here is what happens to fees under concentrated mining. The logic changes from the marginal costs equals the marginal revenue logic in the above distributed case to a more strategic, oligopolistic pricing dynamic. What I mean is this. In the distributed case, whether or not a given miner includes a given tx has no material effect on the expected confirmation time for the tx sender. But in the concentrated mining scenario it does. If some pool is 35% of the network, the decision by that pool to not include the tx will materially increase the confirmation time of that transaction. So miners can extract more of the value that a tx senders place on fast confirmation times by setting their own minimum fee threshold, knowing that this threshold will over time effect the fees that tx senders include. What that optimal threshold is depends upon how much senders are willing to pay for faster tx confirmation times. Who knows what that is, but the implication is clear: under concentrated mining, fees levels will start to reflect more what tx senders are willing to pay rather than the cost to miners of including them.
So when you cast the blocksize issue in this concentrated mining context, it’s really not clear what will happen. My bets are that fees will go up and we won’t have to worry about blocksizes because higher fees will act as a break on adoption.
If block sizes are increased we will learn a lot about the dynamics of the community, the interplay between incentives such as fees and seigniorage have for on-boarding (and off-boarding) miners as well as how price sensitive users are in this space.
In theory, fee rewards should incentivize miners to include as many transactions as possible. In reality though fee rewards are a tiny percentage of block rewards and the risk-rewards ratio simply doesn’t add up at the moment (risking a (almost) sure 25 BTC payoff to get a potential say 25.1 BTC). What are the rational incentives for miners to upgrade and actually fill 20mb blocks? At the moment there are none that I am aware of. If there are no incentives for miners then this is not going to happen. Period. There is no altruism when it comes mining and anyone who bets on it is in for a rude awakening.
But this crosses over into the new field of cryptoeconomics which is a topic for another day.
[Thanks to Anton Bolotinksy for his thoughts on measuring the value of nodes within the system.]
I would add that there is a downward pressure on block size for block makers. I’ve done some research with Nadi Sarrer that proves the larger the block, the longer propagation takes. Even if a pool uses the relay network, increased latency also increases the chance of a pool losing an orphan race.
So block makers have to decide how to maximise fees while at the same time minimising block size. Some, like Discus Fish (f2pool) have tested both minimum block size (only including coinbase tx) and maximum block size, and lately seem comfortable producing maximum sized block each time. (They also seem to have a ‘pay for tx inclusion’ scheme here, but I don’t know much about it)
I think eventually pools will aim to use a decision making algorithm to:
a) Pick a block size they think will make losing an orphan race less likely.
b) Include all available high fee density (fee/kb) transactions in the block
c) then include high fee transactions
d) any left over space can be given to low and zero fee txs
With more data, this sort of process could be optimised to calculate the expected value of a block including the probability of losing orphan races. This would only lead to larger blocks when the value of the included txs outweighed the losses due to orphan races in the long term.
Of course, if all block makers had the same sized blocks, this would not be an issue. But if a block maker can win an orphan race by the expedient of having a smaller block, then they will.
Some open questions for the community: How will fewer network nodes affect orphan races? If the blocks are solved many seconds apart, I would think that fewer network nodes will mean fewer orphan races since the time for a block to propagate to most of the network will reduce significantly. However, if the blocks are solved at the same time, an orphan race might be more likely since the paths taken by the blocks propagating will have less affect on the overall propagation time. Which do you think is more likely?
In summary: If block makers are rational actors and the risk of losing orphan races is a significant downward pressure on block size, I don’t think increasing the available block space will have a significant effect on actual block size. There’s a lot of room for improvement in the tx inclusion algorithms used by most pools, and if I was a block maker I would increase the fee density of blocks and include far fewer low-fee and fee-free txs.
This episode also spawned a number of comments over at Reddit this past week, where I responded to a couple of people.
One clarification I would like to make regarding a specific comment I made on the show. At around the 53 minute mark I discuss something called “trusted transparency.” Guy Corem, CEO of Spondoolies Tech (an Israeli-based mining company) reached out to me this morning and explained that there is a misunderstanding and the area he is working on is more akin to an odometer. I’ll probably write something up later next month as more information becomes public.
Also, the usual caveats: these alone are my opinions and I could be incorrect.
This past week Koinify and the Cryptocurrency Research Group (CCRG), a new academic organization, held a 3-day event — the first of its kind called Cryptoeconomicon, an interdisciplinary private event that included a cross section of developers, entrepreneurs, academics and a few investors. It was purposefully scheduled to coincide with O’Reilly Media’s own “Bitcoin and the Blockchain” conference which took place in the middle of it.
I attended what amounted to four days of seminars, brainstorming and networking sessions. Below are my summarized thoughts. Note: these are my opinions alone and do not reflect those of other participants or the companies I work with. You can view pictures/info of the event: #cryptoecon and @cryptoecon
Rather than going through each session, I will just highlight a few areas that stood out to me and include outside relevant content.
What is cryptoeconomics?
According to Vlad Zamfir, of the Ethereum project, cryptoeconomics as a field might be defined as:
A formal discipline that studies protocols that govern the production, distribution and consumption of goods and services in a decentralized digital economy. Cryptoeconomics is a practical science that focuses on the design and characterization of these protocols.
Zamfir discussed this at length (slides) (video) and rather than going too in-depth with what he said I wanted to reiterate his main points he gave:
Cryptoeconomic security as information security
Mechanisms are really programs
They can distribute payoffs
The programs have a certain behaviour in the Nash equilibrium case
The NE has a cryptoeconomic security
We can be assured that a program will run a particular way
He also argues that “cryptoeconomics” should be see as more economics for cryptography rather than cryptography for economics:
Economic mechanisms can give guarantees that a program will run in a particular way that cryptography alone can’t provide.
Incentives are forward facing, cryptography is a function of already-existing information
How do we provide custom cryptoeconomic guarantees?
The last part in relation to his talk that really stuck out to me was on the final day. In his view (slides) the technical term that should be applied is, “distributed cryptoeconomic consensus” which would assuage concerns from the academic “distributed consensus” community that uses different terminology. Under this definition, this means:
A cryptoeconomic mechanism with the Nash equilibrium of assuring distributed byzantine fault tolerant consensus
We should be able to assert and prove the cryptoeconomic assurances of any consensus mechanism
Distributed consensus mechanisms can create a pure cryptoeconomy. Even the execution of the mechanisms is has a measurable assurance.
Most interesting comment of the event
I think the most apt comment from the economics discussion came from Steve Waldman, a software developer and trader over at Interfluidity on the first day of the event.
While there will likely be a recording posted on Youtube (video), in essence what he said was that in the blockchain space — and specifically the developers in the room — they are creating an enormous amount of supply without looking to see what the corresponding demand is. That is to say, there is effectively a supply glut of “blockchain tech” in part because few people are asking whether or not this tech actually has any practical consumer demand. Where are the on-the-ground consumer behavior surveys and reports?
Again, if Bitcoin (the overall concept) is viewed as an economy, country or even a startup, it is imperative that the first question is resolved: what is the market need? Who are the intended consumers? So far, despite lots of attention and interest, there has been very little adoption related to blockchains in general. Perhaps this will change, maybe it is only a temporary mismatch. Maybe it these are the chicken-egg equivalent to computing languages like Ruby or PHP and eventually supply somehow creates the demand? Or maybe it suffers from the Kevin Costner platform trap (e.g,. if you build it, will they come?).
To illustrate this contrarian view:
Source: David Norris https://twitter.com/norrisnode/status/561262588466839553
Maybe there is no real market need for these first generation concepts? Perhaps the network will run out of block rewards (cash incentives) to the miners before these blockchains can gain mainstream traction? Maybe the current developers are not quite right for the job?
Or maybe, blockchains such as Bitcoin simply get outcompeted in the overall marketplace. For instance, there are currently 1,586 Payment startups listed on AngelList and 106 P2P Money Transfer startups listed on AngelList. Most of these will likely burn out of capital and cease to exist, but there are probably at least a dozen or so of each that will (and have) gained traction and are direct competitors to these first generation blockchains.
Perhaps this will change, but then again, maybe the market is more interested in what William Mougayar (who unfortunately was not part of the event) pointed out a few days ago. Simply put, maybe there is more room to grow in the “Blockchain Neutral Smart Services” and “Non-Blockchain Consensus” quadrants:
We cannot know for certain a priori what market participants will decide. Perhaps Bitcoin is good enough to do everything its enthusiastic supporter claim it can.
Or maybe, as Patrick Collison, CEO of Stripe, wittily stated in Technology Review:
“Bitcoin is kind of a financial Rorschach test; everyone projects their desired monetary future onto it.”
Now, to be fair, Collison (who was not part of the event) has a horse in the race with Stellar. Fortunately there was not much emphasis on token prices going to the moon at the Cryptoecon event. When incentives did come up, it was largely related to how a consensus mechanism can be secure through a self-reinforcing Nash equilibrium.
Perhaps a future event could discuss what Meher Roy (who unfortunately was not in attendance either) adroitly summarized and modeled in relation to how actors are betting on crypto-finance platforms:
There were a number of startups at the event, probably around a dozen or so. In my view, the most concise overview was from Sergey Nazarov co-founder of SmartContract. The interface was clean, the message was clear and “issuance” can be done today. I’m not necessarily endorsing the stack he’s using, but I think he has clearly talked to end-users for ease of use feedback (note: be sure to consult a lawyer before using any ‘smart contracting’ system, perhaps they are not recognized as actual “contracts” in your jurisdiction). Also, drones.
It would have been nice to see a little longer debate between StorJ, Maidsafe and Filecoin groups. I think there was probably a little too much “it just works” handwaving but thought that Juan Binet-Betez from IPFS/Filecoin gave the most thorough blueprint of how his system worked (he also showed a small working demo).
It was not recorded but I think messaging for Augur (a variation of Truthcoin) was pretty poor. Again, just my opinion but I was vocal about the particular use-case (gambling) proposed as it would simply bring more negative PR to a space smashed with bad PR. The following day other members of the team discussed other uses including prediction markets for political events (similar to what Intrade did). I am skeptical that in its current form it will become widely adopted because futures markets, like the CME, already do a relatively competitive job at providing this service for many industries and these decentralized markets could likely just attract marginal, illicit activities as has been the trend so far. I could be wrong and perhaps they will flourish in emerging markets for those without access to the CME-like institutions.
Things that look less skeptical
There were about 10-12 people affiliated with Ethereum at the event, all of them were developers and none of them seemed to push their product as “the one chain to rule them all” (in fact, there was a healthy debate about proof-of-stake / proof-of-work within their contingent). I’ve been fairly skeptical since last summer when their team looked gigantically bloated (too many cooks in the kitchen) but they seem to have since slimmed down, removing some of the pumpers and focusing on the core tech. This is not to say they will succeed, but I am slightly less skeptical than I was 3-4 months ago.
I also had a chance to sit down with a couple members of the IBM ADEPT ‘Internet of Things’ team. They held a ~3 hour workshop which was attended by around 20 people. The session was led by Henning Diedrich (IBM), David Kravitz (IBM) and Patrick Deegan (Open Mustard Seed Project). Again, even though I’ve paged through the ADEPT whitepaper, I was hesitant to believe that this was little more than marketing on the part of IBM. But by the time the session was over, I was a little less skeptical. Perhaps in the future, when more appliances and devices have secure proplets, they could use a method — such as a blockchain/cryptoledger — to securely bid/ask on resources like electricity. B2B and machine-to-machine ideas were discussed and piggybacked on. Obviously there are all sorts of funny and sad ways this could end but that is up for Michael Bay to visualize next year.
This also intersects with another good comment from Stefan Thomas (CTO of Ripple Labs). In a nutshell, on a panel during the first day, he thinks there is some confusion and conflation of the terms “automation,” “decentralization,” “smart contracts” and “blockchains.” That is to say, while blockchains are automated, that is not to mean that it is the only means to achieve automation. Nor is decentralization necessary for automation to be achieved in every use-case. Nor are smart contracts the only way to control automated devices. When the video is posted I’ll be sure to link it (video).
Ethan Buchman, lead dev for Eris, was both witty and on top of his form, noting that in practice users don’t need a new browser every time they go to a new site, so they shouldn’t need a new client to view a different blockchain. Let’s keep our eye on Decerver to see how this germinates.
Lastly, the two investors that attended the VC panel on Wednesday included Shahin Farshchi from Lux Capital and Pearl Chan of Omidyar Network. What I liked about them is they weren’t pushing a certain binary viewpoint. They were both upfront and honest: neither had invested in this space, not because they hated it, but because they were taking their time to see what opportunities actually fit within their mandate. Perhaps they will at some point. One joke that Farshchi mentioned was that back when cellular telephony was growing, “everyone and their mom” was selling base station equipment and chips. Similarly there were over 300 companies creating thin film solar cells before bankruptcies and mergers. So the type of euphoria we see in the Bitcoin-space is not necessarily unique.
Room for improvement
Perhaps if there is a next event it could include representatives from Blockstream, Bitfury and other Bitcoin-centered projects. It would be nice to have some perspective from those deeply concerned about with maintaining secure consensus and the Blockstream team has some of the most experienced engineers in this space. Hearing their views next to what Peter Todd (who attended and had some interesting calculations for the estimated costs to attack a network), could help developers build better tools. Similarly, developers from Peernova, Square, Stripe, M-Pesa and Western Union would also likely be good resources to provide empirical feedback.
Additional clarity for what a decentralized autonomous organization (DAO) actually is and is not could be spelled out as well. And how do these intersect with existing legal jurisprudence (can they? as Brett Scott might ask). For anyone who has read “The Cookie Monster” by Vernor Vinge, both Matt Liston and Vitalik Buterin made some not-entirely-unreasonable points about machine-rights and whether or not machines should trust humans (e.g., humans expect bots to provide truthful information, but can the reverse be expected? And what happens if a bot, like a DAO, is deemed too successful or broke a law in some jurisdiction — does it get “carted” away in a truck?).
Lastly, I think by the time there is another event, there will hopefully be more clarity for what a “smart contract” is. One panel I moderated, I tried to get the participants to use the word “banana” instead because the term “banana” is overused and often conflated to mean many things it is legally not. Primavera De Filippi from the Cryptolaw panel made some good comments too about whether or not “bananas” are actual legally binding contracts; she previously did a workshop with Aaron Wright (also in attendance) at the recent Distributed Networks and the Law event held at Harvard/MIT. Steve Omohundro also spoke realistically about these scenarios on the final day, where does liability start and stop for developers of DAOs?
[Note: I would like to thank Kieren James-Lubin, Vitalik Buterin, Tom Ding, Sri Sriram for organizing the event, Robert Schwentker for acting as emcee/photographer, and CFLD and Omidyar Network for sponsoring the event including the delicious food.]
Over the past month we have seen nominal transaction volume on the Bitcoin network reach several all-time highs. Enthusiasts on social media have proposed any number of theories including a rise in retail payments or commercial volume.
Yet upon further inspection, there does not appear to be a silver bullet answer.
We know, for example, that these transactions can originate or be comprised of faucet outputs, mining rewards, coin mixing, gambling, movement to ‘change’ addresses and simple wallet shuffling. 1 So with this type of identification problem, how can analysts distinguish the signal from the noise? Or as Peter Todd and others explained last month, for a few hundred dollars a day, it is possible to inflate the transaction volume by an entire order of magnitude.2
For instance, questions have arisen over a series of what some call “long chains.” Last month several commentators on a popular thread on Hacker News identified thousands of small transactions originating from a single source.3 The source was continually sending transactions and paid transaction fees for each of them. The reason this struck many as odd as a rational actor would simply bundle the transactions together to save on transaction fees.
While there are likely different motivations for doing so, one reason for why this was occurring was that the originating source was attempting to delink or otherwise mix and tumble coins to make it difficult to “dox” or identify the originating source. But it could also be a faucet and at one point even pools paid out miners using chained transactions, perhaps some still do.
What does this look like? Below is a chart created by user “FatalLogic” in that thread:
Source: Hacker News
The green line identifies the overall transaction volume on the Bitcoin blockchain, whereas the red line follows the rule, the heuristic that removes these “long chains.”
Is there a definition of long chains?
Two weeks ago Blockchain.info published several similar charts excluding “Long Chains.”
According to Jonathan Levin, formerly of Coinometrics:4
Blockchain.info have implemented a heuristic to identify high velocity activity that is probably unrelated to real world commerce. Every day the internal counter resets and counts how many times transaction outputs were spent on the same day. So if a wallet paid someone 1 btc in one transaction output and they then transferred that to cold storage that would be a chain of two. However there are some chains where the chain of spent outputs of a given day exceeds 1000. Each day, on average, the sample size is 144 blocks. Therefore, for chains of more than 144, the chain of transactions involve zero confirmation transactions (i.e., are not relying on the blockchain for their security). In other words, it is a measure of velocity.
These long chains show that there are some parts of the economy that are flipping outputs almost 10 times a block with chains of over 1000 in a day. This may not relate to real world commerce or security processes, probably more likely to be gambling or mixing. In Satoshi Dice often the bettor just takes their winnings and gambles again with everything being done with 0 confirmations. Likewise with mixing there is little need to wait for confirmations and the priority is obscuring the origin of the transaction outputs. Finally this is unlikely to capture a lot of activity run by the centralised services since their objective is fee minimisation.
Furthermore, according to the description on Blockchain.info’s site, “A chart showing the total number of bitcoin transactions per day excluding those part of long chain transaction chains. There are many legitimate reasons to create long transaction chains however they may also be caused by coin mixing or possible attempts to manipulate transaction volume.”
The first chart below is the original unmodified chart of total transactions on the Bitcoin blockchain:5
Using the same Y-o-Y time frame, below is the newly modified chart, using the Blockchain.info heuristic that removes these “chains” longer than 10:6
As we can tell above, by removing these “long chains” the volume decreases by 3x, yet there does appear to be an upward trend over the past several months.
I spoke with Atif Nazir, the CEO and co-founder of Block.io. In his view:7
The term “longest chain” is vague – it would be misleading to say it is just coin mixing. The volume could be a series of transactions where the user cannot spend to the desired destinations in the same transaction. This could be a limitation of their wallet software’s user interface, or the backend of the software itself.
For instance, if a faucet is built on Block.io, the owner spends coins rapidly, sometimes breaking them into a couple transactions if they are efficient, and at other times into hundreds of transactions that spend unconfirmed change in rapid succession. We have seen chains of unconfirmed spends as long as 1,000 transactions, and they could be longer if blocks are not found.
In general, achieving provable privacy through coin mixing and coin shuffling is hard as long as you stay on the same Blockchain. With the current methods, you can look at a destination address and say, with some certainty, “hey, this guy is the one who stole the Bitstamp coins.”8
In the absence of a definite, no-non-sense way to look at “long chains” of transactions, the safest assumption would be to consider them as unconfirmed chain spends, where the user wants to spend transactions very quickly deliberately or due to their software’s limitation.
Another potential source is even smaller.
For instance, Sidney Zhang, co-founder of HelloBlock has noticed that:9
Another interesting thing is people are sending dust transactions on the network as advertisements for high-yield investment program (HYIP).10
This transaction, 92aa, is an example of an ad (and the message was removed by blockchain.info).11
What they do is they will look for transactions happening on the blockchain, pick a collection of addresses and then send 1 satoshi to them and then they will attach a “public note” on blockchain.info. The message is normally like earn 7% per day at xyz.com. The public note in this case was removed, probably reported as spam
The second, 1cca, is an example of a faucet. If you look at the tag “win free bitcoins every hour!” it is the address for freebitco.in.12
It is unlikely the long chains come directly from consumers because consumers don’t spend money rapidly.
A more likely scenario is it is a ‘shared’ hot wallet operated by a service (e.g., Coinbase, Circle). A possible explanation then emerges – off-chain gambling sites such as Primedice / Moneypot / Betcoin casino and others operate hot wallets.
In terms of scale, very small casinos may receive approximately 30+ deposits a day. A larger casino easily operate with 1000s of deposits a day and hundreds of withdrawals.
One interesting behavior is that, bitcoin gamblers never keep funds in a casino. They tend to deposit, play and then immediately withdraw without leaving funds there overnight. That could create a huge amount of activities from the same hot wallet. Thus creating a large chain.
Last year Ken Shirriff also pointed out a few of the notable pieces of “spam” that permanently reside on the blockchain including images.13
What does this look like altogether?
For additional analysis I reached out to Organ of Corti who plotted out these differences onto two different charts.14
As shown above, these match up with the heuristic used by the original Hacker News post as well as that of Blockchain.info. In Organ’s view:
If long chains of transactions are used by entities of a very different nature to single transactions or short chains of transactions, then we might expect to see differences in transaction rates and transaction rate cycles between the short and long chain groups.
Starting with a visual comparison of the two groups, the most significant difference between the longer and shorter chain groups is variance. This is to be expected since one long chain of transactions increases transactions rates more than a single, unchained transaction.
Does the yellow line at the bottom represent the actual “real” volume? Perhaps, but maybe not.
In addition, Organ put together a spectrogram to analyze this weekly cycle that is visually apparent in all the charts:
Another way to look at it is through a spectral density chart, according to him:
Perhaps a more useful test is to check for periodicity in the data. We know from previous work that currently transactions show a daily and a weekly cycle. I’m using Blockchain.info’s data which is daily, so a spectrogram will only reveal a weekly cycle.
The last plot shows the spectrograms for chains longer and shorter than 10, 100, 1000, or 10000. These show a periodicity similar to that for all transactions of one cycle per week.
We can also compare transaction of chains longer and shorter than 10, 100, 1000, or 10000 by calculating the cross correlation function. In each case the maximum correlation is at lag 0 and is much higher than the upper bound of the 99.9 confidence interval, so the periodicity of the transaction rates of each group (chains longer and shorter than 10, 100, 1000, or 10000) are similar to, also suggesting that time of use for shorter and longer chain transactions are similar.
Further, time series decomposition showed the same starting and finishing days of each weekly cycle.
I think that a working week cycle implies that the larger number uses of longer chain transactions are from businesses with a normal working week, and the correlation in the periodicity of the shorter and longer chains of transactions suggests the largest use of both longer and shorter chains of transactions are by entities with a work days and weekends.
Is there anything that explains the increase then?
Earlier this month a new game called SaruTobi was approved for inclusion into the iOS store.15 The game tips its users bitcoin on the blockchain (in contrast, ChangeTip does so off-chain). During its debut week, before running out of coins, according to its first public address, SaruTobi sent out more than 5,000 transactions most of which during an 11-hour time period.16Within its first two weeks it paid out roughly 6.4 bitcoins with more than 50,000 transactions.17
Another continual source of on-chain usage comes from Counterparty, a “2.0” platform that effectively sits on top of the Bitcoin blockchain and uses bitcoins for each counterparty transaction (e.g., it is an embedded consensus mechanism). Below is a visual of the daily transaction volume over the past year:18
The variation follows some of the daily (and weekend) patterns we have observed with Bitcoin in general (e.g., less activity on “Sundays”) but at certain days and times there are peak usages of up to 3% of the Bitcoin network.19 One explanation is that Counterparty is a popular platform for issuing tokens during crowdsales. For instance, the double peaks in December are most likely related to the Gems crowdsale, in which 2,633 BTC were exchanged for 38 million “GEMZ” (the native coin of the Gems system).20
As I briefly described last month, over the past year, a BitcoinTalk user, “dexX7” has been parsing other data, usually related to alt platforms such as Counterparty, Mastercoin, Colored coins and proof of existence.21 Recall that these ‘altcoins’ are actually in practice, just watermarked bitcoin transactions. In order to use these platforms, a user has to interact with the Bitcoin network (e.g., they are embedded consensus mechanisms). Below is a chart he recently sent me that dissects this composed parts:22
Data captured at block height 340,018
There were at least 184,155 identifiable meta-transactions
There were 57,489,982 transactions in total
There were 16,511,696 unspent outputs
This only includes the transactions dexX7 was able to identify. Counterparty, Mastercoin and Chancecoin use almost entirely “bare multisig” scripts as medium to embed and transport data. In contrast, Proof of Existence, Open Assets, Coinspark and Block Sign use OP_RETURN (note: there is still an active discussion between using 40 bytes and 80 bytes).23 Open Assets and Coinspark are a type of colored coin implementation and both Proof of Existence and Block Sign are a type of notary service (previous charts are available in an album view).24
Some other analysis from dexX7:
Almost all Counterparty transactions carry data via bare multisig and there are about 5000 non-multisig Mastercoin transactions. There are furthermore 17620 unclassified, unspent multisig outputs and 6286 unclassified, spent multisig outputs.
Almost all of those unclassified multisig outputs were created by Wikileaks and actually carry some data too.25
Proof of Existence, Open Assets, Coin Spark and Block Sign account for 7363 OP_RETURN transactions. The total number of all OP_RETURN outputs, according to webbtc.com, is close to 11960, so more than 60 % can be mapped to those four.
Another slice of daily and weekly transactional volume comes from pay-to-script-hash, better known as P2SH. This was originally BIP 16 proposed by Gavin Andresen and incorporated into the protocol in 2012 to “let a spender create a pubkey script containing a hash of a second script, the redeem script.”26
This has replaced ‘bare’ multisig as a means for securing bitcoins. While its use and adoption started off very slow, more than 6% of all bitcoins are now stored in this manner including Bitstamp via its recent integration with BitGo:27
What about retail volume?
As has become apparent, it cannot be said that an increase in transaction volume is (probably) due to any one specific variable. Yet, according to a popular narrative, the quadrupling of acceptance by merchants this past year (from ~20,000 to 82,000), may have led to increased spending by consumers and therefore account for the increase.28
Last month, Jorge Stolfi a computer science professor in Brazil analyzed the BitPay addresses (BitPay reuses addresses) based on the Walletexplorer dataset.29 Below is a visual of what BitPay has received over the past two years.
According to Stolfi:
The green line on this graph shows the number of BTC deposited each day into that wallet.30 This graph is rather strange since the number is practically constant since January 2013, about 500–1000 BTC/day, and shows no weekly pattern. And no Black Friday spike either.
In his analysis Stolfi also noticed two different types of orders processed by BitPay, what he labels “wholesale” versus “retail.” The “wholesale” coins are likely miners selling their block rewards in bulk whereas “retail” is consumer behavior (e.g., buying coffee, food, tickets).
Furthermore, if this wallet heuristic is valid, according to Stolfi:
BitPay now processes about 1000-1500 “retail” payments per day, averaging less than 1 BTC each;
The number of retail transactions processed by BitPay has grown 3x since mid-2013, and has been flat through most of 2014;
The amount of BTC processed by BitPay (including “retail” and “wholesale” payments) has been quite constant since Jan/2013, about 500-1000 BTC/day
In terms of dollar value, the amount processed by BitPay (including “retail” and “wholesale” payments) has increased a lot from 2013 to 2014, but has fallen 50% or more since February, as the BTC price fell.
Black Friday had a modest effect (2x to 3x) on the number of “retail” payments, but had no effect on the total BTC/day (which is dominated by the “wholesale” payments).
And what about off-chain retail transactions?
Below is a public chart from Coinbase that visualizes the off-chain activity that takes place on Coinbase’s platform.31
The noticeable pattern of higher activity on weekdays versus the weekend is apparent irrespective of holidays. Consequently, on most days these self-reported numbers comprise between 3-5% of the total transactions on the Bitcoin blockchain. However, as Jonathan Levin, has pointed out, it is not clear from these numbers alone are or what they refer to: Coinbase user to user, user to merchant, and possible user wallet to user vault?
Another way of looking at whether or not transaction volume is increasing is through the “fees” to miner metric (recall that these are not real “fees” as they are not mandatory yet and may be more akin to “donations”).32 Maybe transaction volume based on the methods above does not fully capture hypothesized growth.
Above is a new chart from Organ of Corti which visualizes the transaction fees included with each block over the past 6 years.33 If on-chain retail commerce was increasing, it would likely in turn be paid for via some fee mechanism yet this is not apparent. This is not to say that utility has not increased for certain participants. Volume as a whole has clearly increased as shown by the second image – yet these are users who likely opt to send a fee-less transaction to the mempool (these transactions typically take several hours or perhaps a day to be included within a block).
What is another explanation?
It does illustrate that the other narrative – that fees replacing block rewards – has not yet begun to occur. Maybe it will not.
For instance, last year Robert Sams and Vitalik Buterin highlighted the economic costs that are being overlooked to maintain the infrastructure, that fees would unlikely be able to adequately compensate miners.34 And Dave Hudson independently explored what has actually occurred in practice, providing visualizations of the empirical data that highlights and reinforces their marginalized viewpoint.35
To put it another way, if more users were actively using the blockchain to transmit value, then it would likely be apparent via an aggregate increase in fees.
As shown above during a four year time span, miners, the actual labor force of the network, are not seeing the narrative play out as it is supposed to (block reward plus fees to miner). Denominated in bitcoin (the blue line), miners have not seen the increase in fees or revenue that many of the same social media promoters claim will happen. Whether this changes is unknown.
Again, recall the current narrative that in the end, transaction fees will purportedly replace the block reward.36 But the causality is the opposite direction than assumed by most: fees people are willing to pay determine the number of miners. Not the other way around. The takeaway is that simply put, fees may not rise to cover the current block reward amounts. It may be that the block reward falls and miners just drop out and net transaction fees never increase reducing the security of the network but this is a topic for another article.
What does this all mean?
For perspective I spoke with Ernie Teo, a research fellow at the Sim Kee Boon Institute for Financial Economics (which hosted a cryptocurrency conference in November).37According to his team:
We observe similar trends to what has been mentioned in your article. We see a large increase in the one satoshi (or less) addresses over time. This could also be due to the long chain “spammer” you have described above. A few more things we can note from our upcoming analysis on the distribution of bitcoins over time:
50 coin addresses, these are the only addresses in the very beginning due there being only miners on the network. However we see that this does not fluctuate a lot overtime and it indicates that most miners tend to cash out once they mined.
Large increase in number of addresses with less than 1 bitcoin. This indicates more “retail” type buyers.
Not much change or fluctuations to the large addresses.
I think it is probably true that not a very large proportion of the transactions are retail transactions. In the long run, it doesn’t help the network. We can only wait for the next big innovative app that can boost retail-type usage.
How else can this be visualized?
John Ratcliff recently published several new charts describing “the State of the Blockchain Address(es)“ in which he delves into token movements and in particular “zombie” addresses (addresses that have not been active in 3 or more years).38 They are illuminating and we both disagree on conclusions that can be drawn from them.
For instance, he updated one chart that I previously described as showing more than 70% of coins have not moved in more than 6 months:39
Source: John Ratcliff
What does the chart above illustrate? If it is velocity then what the color bands reinforce my explanation from two months ago: that the majority of coin holders that were purchased in the November / December 2013 bubble are now underwater.40 We see the transition over the year, in which these coin holders, rather than spending and realizing a loss, hold on to them throughout the months. Hence, why we likely see another uptick to an “older” band starting in mid-November 2014 – the anniversary of the beginning of the most recent bubble.
This explanation is further reinforced by the demographics of bitcoin holders: mostly middle to upper-middle class residents of developed countries – most of whom have “low time preference” (e.g., speculators) and therefore do not need or want to spend bitcoins immediately because they have other means of payment (e.g., credit cards) and can therefore hold onto their coins longer than someone with “higher time preference” (e.g., less affluent individuals living paycheck to paycheck who in theory would have to continually, immediately spend bitcoins). Another potential explanation is the disposition effect, but this is also a topic for a different article.41
The chart above (originally Figure 15) was published this past month by two researchers at the Federal Reserve.42 They independently used a similar methodology that Ratcliff has undertaken. In their view:
Figure 15 examines the degree of activity for the addresses in the network. For each date we partition the volume of addresses with positive balances according to their last activity. For example, the addresses that have transacted in the last week are likely to be frequently used (shown with the strip in the bottom). On the other hand, some of the addresses have not been active in the past 52 weeks. Those are likely to serve saving or investment purposes and much less so for transacting. From Figure 15 we can see that the volume of “investment” addresses (not used in the last year) has been steadily decreasing. Still, however, around 75 percent of the addresses in operation with positive balances have not been used in a transaction in the last four months.
While the rest of their report is illuminating, in their concluding remarks, they also do not see retail transactions as comprising more than a marginal amount of volume:
Broadly speaking, our empirical exercise documents general patterns of Bitcoin usage, and examines the use of Bitcoin for investment and payment purposes. We find that while the number of daily users may have doubled every eight months, the transaction volume is negligible compared to the domestic volume of U.S. payment systems. Our analysis of data from the Bitcoin system further suggests that Bitcoin is still barely used for payments for goods and services. In addition, the patterns of circulations of bitcoins and the dynamics of the bitcoin exchange rate are consistent with low usage of Bitcoin for retail payment transactions. Finally, we provide evidence that the exchange rates between bitcoin and other currencies are not well aligned, which we interpret as a lack of depth of the exchange markets and as costly exchange rather than unexploited arbitrage opportunities.
Perhaps these trends will change. Maybe, as some claim, retail volume will increase. But as shown above and through Total Output Volume we know what the maximum “purchasing power volume” of transactions is, this has not been a mystery.43
While merchant adoption continues to increase, consumer adoption for retail purchases appears to be flat (as shown by both BitPay and Coinbase numbers). Future analysis may need to look at correlating these trends for brick and mortar merchants. Without regular use at the register and point-of-sale, there are a number of anecdotal stories of retraining and fumbling that will go on with floor employees with respect to accepting bitcoin.44
Perhaps again, this will change in the future (e.g. Impulse),45 but going forward a full traffic analysis such as the type created by Sarah Meiklejohn et al. two years ago would help the industry as a whole determine what consumer behavior looks like with greater accuracy.46 And this is important for a project whose white paper promotes itself as a payment network for online commerce (see section 1).
So what conclusions can be drawn from this?
As noted at the beginning, there does not appear to be one specific variable that explains the recent increases over the past several months. For example, most tipping from services like Bitui in China and ChangeTip internationally, is already done off-chain (e.g., the independent site ‘ChangeTip stats’ describes activity on the company database).47SaruTobi is too new to account for all but the last few weeks of growth and DarkWallet activity will likely be “long chain” related. Perhaps offline P2P transactions from OpenBazaar should be identified, aggregated and brought into future analysis.48
Future analysis should also look to factor in or filter out activity related to “change” addresses. For instance, the short-term ‘velocity’ seen in the daily and weekly bands of Ratcliff and Badev & Chen’s charts could be overstated due to coins which do not actually swap hands but are rather “spent” to themselves due to how “change” is handled by the protocol. Furthermore, as has been described in Dave Hudson’s modeling of block sizes, it cannot be said that an increase in on-chain volume is axiomatically “good.”49
All we can say for now is that there is an increase in usage from multiple sources, but not likely from on-chain retail commerce which has remained flat for about a year.
This is still a dynamic space and perhaps it may be months or even years before we will be able to fully identify all the major contributors to volume changes.
Special thanks to dexX7, Raffael Danielli, Michael Dann, Dave Hudson, David Lancashire, TM Lee, Jonathan Levin, Atif Nazir, Organ of Corti, Jorge Stolfi, Ernie Teo and Sidney Zhang for their constructive feedback and time.
I have a new O’Reilly Media presentation up online called: “Moving Beyond Bitcoin (BINO) Beta:Transitioning mindshare from Bitcoin-for-everything monopoly to a competitive consensus-as-a-service marketplace.”
It is largely based on an earlier presentation (older slides) I gave in Singapore in November plus a few more updated slides from my R3 talk last month (slides).
Note: in order to listen and view you need to register (for free).
Yesterday there was a discussion on a listserve about Brian Kelly’s hypothesis’ regarding bitcoin exchange rates and below is an answer I used to discuss where payment processors fit into the ecosystem.
At their core BitPay is basically a forex company, a broker that matches merchants with liquidity providers. Microsoft and some 44,000 merchants can convert bitcoins into fiat through them (and/or hold portions or all of the coins they receive too). Some miners also use them to process BTC to USD.
To do this, they have built an exchange (you can also call a few of their team members to place block orders with), which effectively sorts the bid/asks among other exchanges and OTC providers (such as Buttercoin, Mirror, Xapo, Sator Square Partners, Bitfinex, Coinbase, etc.). I tried describing some of how this plumbing system works in a article a couple months ago.
While I do not have the full details of other payment processors (like Coinsimple or Bitnet), they likely try to build similar relationships with liquidity providers. And this is important because all payment processors — or really, forex brokers — are faced with the following three situations during an arbitrary 15 minute window:
1) order from merchant is canceled by payment processor
2) order from merchant is accepted and then sold to inventory partner (such as Buttercoin)
3) order from merchant is accepted but the coin is put on payment processor’s books
Payment processors ultimately want commerce to flow so they do their best to match up partners; so in practice there has to be partner on the other end with the same or greater demand for the coins being sold by the consumer/merchant.
I do not have exact numbers for how often #1 happens though I do understand it happens on a daily basis (again, the 15 minute window is to help lock in a price and the OTC demand from partners such as Coinbase may not be fast enough at times) or how often #3 happens (my understanding is US payment processors typically used to hold coins on their own books prior to the IRS ruling last year but have sold their inventory for tax purposes). Obviously during a heavily volatile period like yesterday (or even today on the upside), there is a possibility that the coins could get placed on the payment processors’s books due to a lack of bids on the OTC partners side, but none of that is really public knowledge.
The point is however, that there has to be a demand side to absorb the sales of coins coming from merchants and payment processors have built some pretty good systems to handle that (incentivized in large part to limit their exposure to exchange rate volatility). If these partners were to disappear or the coins they decide to purchase declines in aggregate, payment processors are then left with having to choose #1 or #3. This doesn’t seem to be the case the last few days, the behavior seems to be on the exchanges themselves and not from merchants.
What does this mean in practice?
The current supply pressure on a daily basis: aside from a couple firms such as BitFury (which according to some sources has around a ~$180 total cost of production), miners as a whole end up having to sell the majority of coins each day (~2,000 – 3,000+ coins) and as a whole, merchants process about 5,000 – 6,000 coins a day. So this means 10,000 coins x 365 days or 3,650,000 coins. Thus, to maintain a $300 price with that sell pressure the market needs to have ~$1 billion a year in capital come into this space. And to maintain a $1,200 price with the same merchant/miner behavior the market would need to have ~$4.4 billion. Therefore it is likely that payment processors try to reduce the amount of exposure to #3, otherwise the coins would eat up the internal budget and increase the burn rate at these startups.
Note: what BitPay’s volume looks like in practice was recently summarized by analysis from Jorge Stolfi.
A couple days ago I noted that because Bitpay reuses its addresses, it is possible to monitor them and that there hasn’t been much of a growth since May (the last time they announced numbers).
Today a redditor posted some visual analysis and explanation of these same Bitpay addresses. [Note: I’ve reached out to the user and will update this post if they provide any other information.] Below is their analysis:
The green line on this graph shows the number of payments per day into the presumed (see below) receiving address of BitPay, from 2013-01-01 to 2014-11-3. Note that the vertical axis uses log scale. The number was about 1000–1500 per day through most of 2014, with a strong weekly pattern. The spike at the right end is Black Friday; there were about 3200 inputs, i.e. about 2x to 3x as many as in a typical day.
The green line on this graph shows the number of BTC deposited each day into that wallet. This graph is rather strange since the number is practically constant since January 2013, about 500–1000 BTC/day, and shows no weekly pattern. And no Black Friday spike either.
What happens is that there are two kinds of inputs to that wallet, which I will call “retail” and “wholesale” (although I have no idea what the latter are, really). The wholesale inputs are large (often hundreds of BTC) and have been regular in amount since 2013-01. The “retail” ones are much smaller (mostly under 10 BTC, many under 1 BTC), much more numerous, and have increased about 3x from mid-2013 to mid-2014. Hence the first graph above is dominated by the retail inputs, while the second graph basically shows the wholesale ones.
The data for these plots comes from these pages that are claimed to show all transactions into the BitPay receiving wallet since it was created. However, the addresses that make up that “wallet” were inferred from the blockchain by an undisclosed heuristic that is supposed to identify addresses belonging to the same owner.
My guess is that the heuristic simply assumes that two addresses that are inputs to the same transaction must belong to the same owner (since one needs both private keys to sign the transaction) and assigns them to the same “wallet”. If my guess is correct, the heuristic may fail to include in the “Bitpay.com wallet” some addresses that belong to BitPay but were never used together with the identified ones.
However, the volume of BTC that went into that heuristic “wallet” during May/2014 seems to match what BitPay said to process per day in that month (assuming that they picked the best day of May); so it seems that the heuristic wallet is fairly close to the real one.
BitPay now processes about 1000-1500 “retail” payments per day, averaging less than 1 BTC each;
The number of retail transactions processed by BitPay has grown 3x since mid-2013, and has been flat through most of 2014;
The amount of BTC processed by BitPay (including “retail” and “wholesale” payments) has been quite constant since Jan/2013, about 500-1000 BTC/day
In terms of dollar value, the amount processed by BitPay (including “retail” and “wholesale” payments) has increased a lot from 2013 to 2014, but has fallen 50% or more since February, as the BTC price fell.
Black Friday had a modest effect (2x to 3x) on the number of “retail” payments, but had no effect on the total BTC/day (which is dominated by the “wholesale” payments).
Last year Peter Coy illustrated what a deflationary economy looks like (such as the Bitcoin economy) and explained how this impacts consumer spending (and lending).
Depending on what peak someone may have bought at, the very reverse happened this year, with prices denominated in bitcoin rising by perhaps as much as 65% (a full analysis should probably also adjust a couple percent to include CPI).
Though, to my knowledge there are no products actually denominated in bitcoin (yet).
So then, did spending habits change over the course of the year?
Not really, users as a whole still preferred to simply hold onto coins either because they had low time preferences with future expectations of large price appreciation and/or they were ‘underwater’ in coin (e.g., they bought at a peak). Off-chain transactions on Coinbase did not see much of a difference (yet) either.
Economic theory suggests that consumers prefer a medium of exchange with stable purchasing power and in practice that seems to be the case.
For instance, on January 9, 2014 online retailer Overstock.com began accepting bitcoin as payment. In the first two months it generated $1 million in bitcoin payments and through May the tally had grown to $1.6 million in bitcoin payments.
According to a new story yesterday, Overstock announced it would likely generate $3 million in bitcoin payments this year (though they do not specify how many bitcoins that is altogether). This is in contrast to the estimates at the beginning of the year:
The figures are notable given that the e-commerce company had issued a wide range of potential estimates for its first-year bitcoin sales over the course of the year. In March, CEO Patrick Byrne suggested Overstock was on pace to achieve $10m–$15m, or even $20m, in bitcoin sales.
Such estimates were also below the $5m Byrne said Overstock originally anticipated, though on par with those suggested by Overstock chairman of the board Jonathan Johnson in interviews.
Altogether approximately 11,100 customers paid with bitcoin this past year at Overstock — these customers spent an average of $273 in bitcoins. That means that after the initial power law from the first couple months, roughly $200,000 in bitcoin sales occurred from March onwards, or roughly $6,700 per day.
If bitcoin denominated prices had stayed the same, would that have increased the amount purchased? Perhaps, but as articulated by both Robert Sams and Yanis Varoufakis, bitcoin stability is perpetually ephemeral and perhaps the only solution is to switch the monocoin ledger and adopt a dual currency ledger design instead (a topic for another day).
Besides a decline in purchasing power, is there anything else that may have caused this?
In chapter 11, pages 181-182 I explored another reason (see this image): demographics. Most (60%) of the customer base of Overstock are female and as we know empirically, there are very few females that inhabit the Bitcoin ecosystem. Perhaps this will change in time, so what are other datum in this exhibit?
Specifically, what does Overstock do with these coins? One redditor looked through the most recent 10-Q filing and found:
At present we do not accept bitcoin payments directly, but use a third party vendor to accept bitcoin payments on our behalf. That third party vendor then immediately converts the bitcoin payments into U.S. dollars so that we receive payment for the product sold at the sales price in U.S. dollars.
We have also begun accumulating bitcoin in an amount of approximately 10% of the amount of our bitcoin-denominated sales as well as other cryptocurrency.
We hold cryptocurrency denominated assets such as bitcoin. We currently consider these holdings to be investments and include them with other long-term assets in our Consolidated Balance Sheets. Cryptocurrency denominated assets were $346,000 and zero at September 30, 2014 and December 31, 2013, respectively … Losses on cryptocurrency holdings were $50,000 during the three and nine months ended September 30, 2014. There were no losses on cryptocurrency holdings for the three and nine months ended September 30, 2013.
Or in other words, Overstock.com sells all but 90% of the coins it receives and puts the remaining portion onto its books as an investment, which saw a loss of $50,000 through Q3. Perhaps this reverses next year if there is another run up in prices.
In addition, the coin sales created (a marginal) sell side pressure on the market through the intermediary, Bitpay, the largest payment processor in this space.
What changes did Bitpay see this year? In a recent profile they noted that:
BitPay, the largest and oldest bitcoin payment processor with a daily volume of $1 million bitcoin transactions supporting more than 44,000 merchants, stated in an email exchange to CCN that more than 4,400 of their merchants keep all of their settlement in bitcoin, almost 18,000 keep some of their settlement in bitcoin while the remaining 22,000 convert it all to fiat.
While the amount of merchants accepting bitcoin more than quadrupled this year, the amount of retail commercial transactions did not. Because Bitpay re-uses the addresses for purchases, it is possible to monitor them for inflows. And over the past 6 months, there has not been a significant change: roughly 2,000 bitcoins in aggregate (+/- 200) are received by Bitpay each day. In fact, they have been receiving approximately the same $1 million in bitcoin transactions since May. [Note: at current market prices, even 2,200 bitcoins does not equal to $1 million thus a contradiction, which can only be cleared if/when Bitpay releases its methodology]
Because of the ecosystem still lacks a ‘circular flow of income,’ in return Bitpay sells these coins to other inventory providers such as financial institutions, family offices and exchanges (detailed here). This further creates sell side price pressure and if there is not a corresponding increase in speculative or transactional demand in bitcoins, effectively lowers the purchasing power of a coin.
For instance, last Wednesday, December 10th, Microsoft announced that it had added bitcoin as a payment vehicle for games and apps. The price rallied 10% in the course of an hour yet subsequently declined to pre-rally prices. Why?
As analyst Raffael Danielli explained to me, on the one hand, Microsoft under the new CEO — Satya Nadella — seems to push deliberately into areas at the forefront of the tech sector. Accepting bitcoin is an item on their list that can easily be implemented and subsequently crossed off (e.g., a cheap point in terms of risk / reward due to the usage of an intermediary).
On the other hand, if people are less willing to spend Bitcoin while ‘underwater’ this can lead to more ‘bad’ news regarding a lack of consumer adoption. For example, one could see a correlation between Xbox One’s less-than-stellar sales and losses against the Playstation 4 (PS4 is outselling 2:1), versus the need to get some kind of PR spark before the Christmas shopping spree. Similarly Time magazine’s announcement today probably will only produce a temporary marginal increase in bitcoin activity and was likely done with similar motivations (positive PR before holidays) because Time been hit hardest (it’s 2012 sales of single-issue copies declined 27%, the most across the entire industry and it laid off 5% of its workforce in early 2013).
Yet most bitcoin holders are probably not the usual demographic of paper magazine subscribers. Or as one droll redditor explained:
Venn diagram of people who use bitcoin and people who subscribe to print magazines: OO
Perhaps market participants as a whole see this too or perhaps they recognize that even if there was an upsurge in bitcoin usage to Microsoft product lines (which we can monitor as Microsoft is using Bitpay), those coins will ultimately put sell side pressure because there is no circular flow of income. And again, without a corresponding amount of speculative or transactional demand, the price of a bitcoin could decline as would its purchasing power.
There is never a dull moment in this space, perhaps 2015 will create new patterns to analyze.
[Special thanks to Jop Hartog and Jonathan Levin for their feedback and information this past month]
Earlier today I gave the following presenation at the R3 Cryptocurrency Round Table in Palo Alto. It covers “Bitcoin 2.0” ideas including alternative consensus mechanisms, costs of operating decentralized ledgers, use-cases for these new ledgers within existing financial institutions and potential hurdles including disproportional rewards.
[Note: citations and references can be found in the notes of each slide]
Why spend time writing about this? Because it is increasingly clear that keynote speakers in this industry are factually wrong about many things, including the various margins that money service organizations (MSO) like WU have. For instance, yesterday there was a really good thread on reddit that broke down the erroneous claims from Andreas Antonopoulos regarding the margins that WU and others have, it is wrong by an entire order of magnitude.
Over the past year as I conducted interviews for my research I would often hear stories of how such and such owned X amount of bitcoins. In just a six month period it became pretty clear that someone somewhere was embellishing because there just aren’t that many bitcoins around. This was especially true once you start hearing rumors of the amount of bitcoins that large holders in China claim to have. Which side of the Pacific is exaggerating more?
A few things were cut in the 2nd article to slim it down a bit and also because it meandered a little. Here are a few of the items:
While an imperfect facsimile a UTXO (unspent transaction output) or bitcoin, is not equivalent to equity.
Remember, pre-Artforz, miners and hashers were one and the same, so a DMMS was not a farm or pool back then as it is today.
Some of these exchanges started within a niche such as futures speculation. For example, Bitfinex originally shared (mirrored) the Bitstamp order book and later, after growth, established their own thereby allowing their customers to partake in price discovery through the spot market (e.g., providing bids and asks). Others such as Coinbase effectively operate what Coindesk calls “a Universal” — that is as a hosted wallet, merchant processor and exchange — albeit without a users ability to speculate on the bid/ask of a token (in most cases Bitstamp acts as their liquidity provider who in turn receives coins from miners and so on).
This year alone, several exchanges have been hacked and/or customer funds were stolen by insiders, including Mintpal, BTER, CoinEx, Coinmarket.io, Neo & Bee (it wasn’t an exchange per se, it collapsed too soon to figure out what they meant, if at all, to do) and most prominently, Mt. Gox. Despite a spectrum of counterparty risks and the advent of decentralized and multisig trading (eg the Counterparty DEx and Coinffeine), traders, on the whole, still prefer to use centralized exchanges due to their trading speeds (milliseconds instead of 10+ minutes).
Lastly, a friend of mine, Anton Bolotinsky sent me some additional feedback that may be of interest to some readers:
The statement: “Also, withdrawal time from an exchange is not necessarily related to the price of bitcoin.” Seem to be out of context.
I’d assume it’s about market phenomena – which will move price if people withdraw both btc and fiat positions from exchange. They would either have some very fast cash deposit/withdrawal mechanism to be able to do it daily. Alternatively, at the end of the day, they would convert fiat to btc, and withdraw btc. This would move the price.
If fiat positions are not liquidated, withdrawing only btc, will reduce risk exposure to 50% on average. And will create evening & morning blockchain transactions spike – btc from exchange to wallet, and back. I can’t see anything like this happening.
Another thing that somebody will probably comment: btc exchanges, unlike NYSE, work 24/7, nothing besides trading volumes (maybe) changes. So notion of doing something for night might be archaic:)
Based on comments from both reddit and Coindesk, the number one question today seems to be related to off-chain transactions. Why aren’t these being factored in to the equation? [Note: it bears mentioning that I did discuss this on p. 84, Chapter 4]
There are multiple problems with this perspective, however before delving into that I should point out that in the previous article, I did in fact link to Coinbase’s self-reported off-chain transaction numbers. They are relatively marginal, on most days comprising less than 5% of the total transactional numbers. But it is not clear from these numbers alone are or what they refer to: Coinbase user to user, user to merchant, and possible user wallet to user vault?
It actually makes the network insecure in two ways:
1) Users become increasingly dependent on trusted third parties (TTP) on the edges, which defeats the purpose of having a blockchain in the first place (recall that “trusted” appears 11 times in the white paper). This also opens both consumers and entrepreneurs up to a host of vulnerabilities and abuses that the industry is continually plagued by.
2) As more users leave the actual blockchain and move off onto TTP, less funds (or “fees”) are going to pay miners for actual security, making the entire network more reliant on seigniorage (block rewards) which in the long-run has empirically been a losing battle.
Below is a chart from Blockchain.info that illustrates fees to miners:
Another chart illustrating this data was compiled from data by Jonathan Levin (formerly of Coinometrics) over the same time period:
Notice how fees have actually decreased and are now at a two year low. This is actually the opposite trend we would want to see and potentially troubling. In fact, contrary to prudence, instead of floating fees the core developers have “slashed” fees (more accurately called “donations“) by tenfold this past year. From an economic sustainability point-of-view, this is the diametrically opposite action that should be taking place. It will make the adjustment period at the next block halving much more painful to consumers as fees have to go up to incentivize miners to stay.
The race to build more hashing power (by developing ASICs for instance) means that the cost to pull off a 51% attack on the network increases. In this respect, the network is more secure. Note however that the amount of money spent on mining and mining equipment must be approximately equal, in the long run, to the amount of bitcoin paid in transaction fees or created through mining. Given off chain transactions, this could dwindle to very low levels in the future.
As Dave Hudson and others have pointed out (see Chapter 3), this fee has to increase because transactional volume simply is not increasing to the level it needs to in order to replace the block reward.
Meher Roy succinctly summed up this conundrum in a comment earlier today:
The question is how will the low-fee high volume work when off-chain is / will prove to be more convenient? Any on-chain fee will be out-competed by speed, lower fees and convenience of off-chain transactions. Why exactly are we sure on – chain transactions will rise 10000 fold that it needs to? How exactly does Bitcoin solve this collective action problem?
These are important questions that thus far, everyone seems to punt on.
What about off-chain data from exchanges? Surely they should be factored into this?
Unless exchanges are willing to publicly share that data, it is difficult to surmise what is taking place in their black boxes (we can have some idea based on public addresses).
But again, this is not a particularly good metric for those who believe lots of commercial trade is taking place. Off-chain transactions on an exchange are equivalent to forex. Value transfer, possibly. Retail commerce, no.
We do in fact know how much Bitpay and other payment processors do in business each day, we know this through the bitcoins they sell each day to liquidity providers. And altogether this amounts to around 5,000 – 6,000 bitcoins per day. Although there are some merchants that keep part or all of their bitcoins, the liquidity sales is the most accurate version of retail commerce we can estimate with today. And that has not changed much over the past six months.
[Special thanks to Dave Babbitt and Jonathan Levin for their constructive feedback]
Back in May I published a blockchain analysis piece on Coindesk that utilized graphs created by John Ratcliff. Ratcliff published several new charts yesterday that provide a fuller picture of this overall movement.
The chart above visualizes nearly 6 years of token movements.
Is there a way to isolate the past year and if so, what does the past year look like? That’s what the next chart illustrates:
What conclusions can be drawn from these charts?
1) that token movement (velocity) strongly correlates with a rapid increase in market prices (e.g., more velocity during the bull runs, less during price decreases); you can see that in the first chart with large bumps in April 2013 and then again in November 2013
2) because of the large dip in prices over the past year, most tokens are inactive in part because the owners are still “underwater”
3) that monthly liquidity is still only around 10% (more on consumption below)
4) the “tx volume” chart on Blockchain.info is no longer entirely valid due to a combination of the usual mixing and mining rewards but also because of increased advertisement spam (e.g., metadata within OP_RETURN), increase in P2SH and Counterparty tx’s. Only a full traffic analysis can provide a more accurate breakdown.
What is especially interesting is to see the “overhang” or rather the “underwater” coins that are moving from the 3 months to the 6-12 month band. What this effectively shows is that owners of those UTXOs purchased them during the bubble of November-December 2013 and are still willing to wait and hold onto these coins until the price rebounds. If there is no upward change in prices then some (or all) of these coins will eventually move into the next band sometime in the spring of 2015.
What other conclusions can be made?
This is a sobering chart for advocates or entrepreneurs within the merchant payment processing vertical. What this shows is that despite the near quadrupling of merchants that now accept bitcoin as payments (this past year increased from ~20k in January to ~76k through September), on-chain activity has not seen a corresponding increase by consumers. They are all effectively fighting for the same thin slice of liquid coins, a segment which empirically has not grown. This does not mean that there are no consumers, only that when paired with data from Bitcoin Day’s Destroyed, there probably hasn’t been any real on-chain growth beyond the exceptions in #4 above. Thus on any given day, payment processors (collectively) likely only process 5,000-6,000 bitcoins still. Other additional activity could be taking place off-chain in trusted third parties (like hosted wallets and exchanges such as Coinbase).
Too reuse an analogy from Chapter 14 (p. 224 and 230), that also means that since 3,600 bitcoins are created each day to pay for security, that with this ratio (3,600 : 6,000) every other mall patron is effectively being guarded by a mall cop which in laymens terms means there is massive security overkill still taking place. This is not a big deal today but when coupled with analysis from Dave Hudson, network transaction fees will have to increase by several orders of magnitude to replace the seigniorage that currently incentivizes miners. This is best illustrated in the cost per transaction metric on Blockchain.info.
On Tuesday I was a panelist on a new segment from Follow The Coin, hosted by Tina Hui. The other panelist was the creator of Dogecoin (among other projects), Jackson Palmer.
Below are transcribed comments I made throughout the recorded portion with the approximate time they were said.
Ditto. When I first got involved with Bitcoin a few years ago, I was really excited, I did some mining. I built some machines in China and slowly but surely I kind of became more of a skeptic. I guess that’s what people know me for. I wouldn’t say I’m anti-Bitcoin, I think there is a lot of Koolaid that is continually circulated. I think Jonestown would be very jealous of the Koolaid in this space. Right now, the phrase I was talking to Jackson earlier was, you know how people are saying “Be your own bank”? I’m not saying you can’t be your own bank but what happens in reality is, like “Be your own textile factory” or “be your own data center” — for whatever reason that just doesn’t work out in reality. I’m not saying it can’t work out in this space but it looks like people prefer to be nannied, prefer to have costumer assurance. I probably just lost a few friends and followers but that’s how I kind of look at things. It’s become BINO: Bitcoin in name only. I have a whole talk on that otherwise.
I’d have to agree for the most part. For listeners, the use cases I think are interesting with the actual technology are pretty mundane. I was talking to Everett from Bloomberg, there is this thing called Consolidated Audit Trail. Back two years ago, the SEC put together something called Rule 613. The idea was to get all these institutions together in the financial industry to actually track every single transaction. That seems like a mundane, unsexy thing but at the same time this might be something that a blockchain may be able to do in some capacity because you have people who do not necessarily trust each another, you have a lot of them. Maybe you don’t need Bitcoin’s blockchain, maybe you can use some kind of other ledger, a proof-of-stake based ledger. I do think the technology does have some interesting potential but probably not for a lot of the things that are being funded.
Sure, so I’ll be mean, I’ll say something not nice. Tipping is a neat idea but in practice what ends up happening a lot and we see this on reddit and LTBCoin and stuff like that, is it incentivizes begging. So we end up having this magnet to rewarding behavior that you really don’t want to have. Obviously there are people who do take tipping seriously and put together some good comments and stuff like that. For example, with LTBCoin. If you are not familiar with it, Adam Levine had this really cool idea: “hey, how about we reward people who make comments.” That sounds great, you are part of the message, part of the community. What ended up happening is that attracted just tons of bots basically, people just spamming. We see this with reddit too with the different tippers. Some guy the other day, 2 or 3 days ago said, “hey, I literally made sock puppets to collect as many tips as I could.” And he collected something like 50,000 satoshi worth, which is not a whole lot but that’s a lot just spending time spamming around to try and get. It has some interesting ideas, the question is, how do you filter out the froth from legitimate players in this. And I’m not sure there is a real silver bullet to that. Maybe it just has to be part of the ecosystem, we’ve lived with it this far maybe it is something we have to soldier on with.
So I’ll be mean again. There really is no correlation between tipping and then encouraging that behavior in a restaurant. Most of the literature doesn’t point to the reason why China is stagnating for example isn’t because a lack of tipping in the country. It’s a cultural thing here in the US, I’m not anti-tipping. My wife and I tip, maybe on the lower side of scale of things. I think it is a funny activity that people do and I’m not against it, but I’m not sure it’s providing a good marketing signal to the participants or the people who receive it.
I don’t put tipping addresses for two reasons. The first one is, actually I talked with Victoria van Eyk at Changetip yesterday, and she said, “Tim, you shouldn’t use this reason.” But I’ll tell you the first reason why, I don’t want to accept candy from strangers. I’m not sure where that coin came from, maybe it is a Silk Road coin. Obviously that is something way down the line, I don’t think anyone is going to bust me for accepting some tip that way. But I do think we should be judicious against who we receive money from, especially in this era of Alex Green and just the amount of scammers and bad apples in this space you don’t know where that money comes from. The other, and this is nothing against Changetip, it’s just how it is efficient: it’s all off-blockchain. The whole purpose of this blockchain space is to provide decentralization, if we’re accepting tips from centralized silos it just reinforces that. So again, I’m not anti their service, but it kind of defeats the purpose if you have to rely on a centralized service to do all that.
Just like you said, it’s unsexy to build these vigilante services because they become centralized and who are you to decide who is the bad guy and stuff like that. So you end up recreating the system that we’re in right now, for better and for worse. There are some tools, if you guys are interested, there is a company called Bitreserve. They just released their transparency initiative called Reservechain and Reserveledger. The idea is you use the Merkle root to trace back to make sure all the tx’s are accounted for. Obviously multisig is one of the few areas I’m not bearish on, it’s legit. Whether or not you can build an entire company around just multisig, I don’t know, we’ll find out. Taking that internally for financial controls, segregating. Even hardware wallets, actually I just tweeted about that the other day. Hardware wallets seem like they have, I hate to say it, maybe they do have some potential — that’s not sexy again, who wants to carry around a wallet, a smartphone and then a hardware wallet with your private keys. Maybe that’s something that user behavior will end up changing or maybe it’s not.
So there is this thing called “affinity fraud.” And just like the name affinity, when you were in school you had affiliations, it’s kind of the same idea. It happens a lot in Bitcoin because there are so many self-identified libertarians essentially. So if you pretend to be a libertarian you can — no offense to anyone here — I’m about to lose some more friends here. They are identifiable targets, it happens in religions, it happens in just about any ‘affinity’ essentially. It’s not something that can be stopped immediately, there’s going to be bad actors that know they can take advantage of this. You have to be judicious. Again, I’m not sure if there is a way you can build a startup, fund it somehow and then go after these guys. It becomes this public goods issue. Again, I’m not saying the only solution is a government, but it seems like there is a perverse incentive to not get rid of these actors. Because what happens is, is especially with thefts and scams is these people need to launder the money and move their money – exit somehow. And to do so, they end up having to use — it creates demand for these other services. So in a way, there is a perverse incentive to not get rid of these actors because creates more demand for the underlying currency. Again, I’m not saying that it is going to stay the way it is, I’m sure I’m going to get a lot of emails saying, “no Tim you are wrong.” But so far no body has done much to get rid of these guys and maybe there is a reason why, maybe everyone is sort of benefiting from this underlying demand.
I will argue that Satoshi pre-mined. And I’m not saying that because I hate Satoshi. Is Satoshi here? Does anyone know Satoshi? You can prove it either way by signing. The reason I argue that is the biggest complaint with pre-mining is you have this allocation that took place before anyone else could particpate, that’s the bottom line. Satoshi only advertised Bitcoin on one obscure mailing list and then preceded to mine basically for an entire year without advertising it again and without doing any effort at all to do PR. He could have run a testnet. He could have done mulligan, “hey, we have these people, it’s been a year now, we’re going to reset it.” And if you add up all the coins that were basically coinbase free, that were just the coinbase transaction or plus one tx, that is about 4.8 million bitcoins (see p. 163) that were basically handed out for free. Without any merit. Again, I’m not saying that you need to confiscate those guys. But what we’re having today is capacity issues with blocks right now: about 30% to 40% of capacity on any given day. Dave Hudson has been doing a lot of good research on this. And so these miners are essentially doing more work today than they were at the beginning. And they’re not being rewarded any more than they were then. That’s an issue with the static rewards. So I would argue that it is essentially a pre-mine, he could have said testnet for the first year and didn’t.
Mine what, Bitcoin? So home mining, industrial mining? The only way most people are making money off of Bitcoin is price appreciation. You mine, you hope that it will increase in value. But you might as well just buy coins at this point. The only people who are really making money are Bitfury, a few places in China (see Chapter 5) and this is because they’re able to scale it and benefit off the energy. This is not to say you can’t possibly do it in maybe certain locations here in the US, like Washington I believe has 3 cents a kilowatt hour. And they were in thenews for setting up some certain sites. But in general in this day in era, with ASICs it’s very difficult to actually have any margin. The argument is, ceteris paribus, it should take one bitcoin to actually make one bitcoin just because of the way the difficulty is auto-adjusted every two weeks. So on the margins there really is no profit except maybe a few different entities that can scale, like Bitfury.
So many questions. So to give you an idea, the Gini coefficient in Bitcoin is 0.88 (see p. 129), perfect number 1.0 is unequal. I’m not some kind of egalitarian marching in the street. But a 0.00 is just the opposite, basically it’s perfectly even distribution. Bitcoin basically has a Gini coefficient higher than North Korea. I’m not saying that’s a good thing or bad thing, it kind of disincentivizes some people to join because they think they can no longer participate in the “get rich quick.” The whole asymptote itself was just one “get rich quick” idea. Again, I’m not saying it was a scam, I’m not saying that at all. As far as the hording versus the savings. So people get this often confused: the protocol itself does not have any mechanism to actually save. It is simply a lockbox. So it is essentially a digital mattress. There is nothing wrong with that. If you just want to hold onto it. But there is no mechanism to take that money within the protocol and lend it out. And what we’re seeing is we can build out lending platform, through like BTCJam. So as a result you have, if you actually look at liquidity, on any given month you have about 10% of all mined tokens ever are actually liquid (see Chapter 12). You have about 90% of tokens that haven’t moved for over a month and about 50% that haven’t moved in more than 6 months. And this is because there is nothing built into the protocol to actually put these into active, lending purposes or any of these other financial instruments. So that kind of creates a stagnant economy. Well you wouldn’t call it a currency. Like you’d call that some kind of commodity. There is no velocity of gold even though it’s legal. You just kind of bury it. Again, I’m not against if you guys want to hold coin. That’s the rational thing to do. The rational thing is, if you believe it is going to appreciate in value you hold onto it. Everyone thinks it’s going to go to the moon. Everyone is actually [acting] rational. So it’s not actually being used as a currency, it’s being used as a commodity and that makes sense because everyone thinks it’s going to raise and appreciate.
It’s hard to know how much money laundering has occurred. I mean unless you can identify ever single transaction and know what the intent was, you don’t know how much. Again, I’m not saying that this doesn’t take place with fiat. Everyone’s always saying fiat is number 1. We have the ability with a blockchain to actually monitor this stuff. And actually it defeats the whole purpose if you have to identify everybody along the way because then it adds all this costs and stuff like that. So it’s this weird paradox. [Question: So you’re actually pro-bitcoin?] I’m on the fence with the technology.
“One of the discussions throughout the conference was related to bitcoin as a commodity, currency and potentially emerging asset class. While this is ultimately an empirical issue, the market so far — based on blockchain behavior — suggests that it could be some form of commodity. As to whether or not it can go the distance and become an entrenched asset class is another issue altogether largely due to the tendency for all proof-of-work based blockchains to ultimately “self–destruct” due to block rewards. Perhaps this will change and bitcoin will somehow be the exception to Ray Dillinger’s rules but it may be the case that its monetary policy cannot incentivize the labor force to stick around long enough to make bitcoin a viable asset class.”
“The Singapore conference was unique in that it provided a well-balanced cross-section of academics, business professionals, decision makers at governmental organizations and entrepreneurs within the industry. As a result, the sobering conversations that took place focused more around actual opportunities and challenges in the community today rather than the typical scifi cheerleading that is divorced from the reality that companies in this space face.”
Videos and other media should be up in the next week or so.
Below are the slides of the presentation I did at a closed-door session on November 5th. Citations and references can be found in the notes of each slide.
With nearly six years of empirical data and use-cases behind the Nakamoto consensus method the community has observed that a cryptocurrency economy behaves differently than originally envisioned and intended. What has arisen from these half-a-decade of physical interactions is a nearly complete rollback of the primary attributes embodied within the first of these Nakamoto consensus protocols, Bitcoin – to the point where it may best to refer to it as Bitcoin-in-name-only (BINO). Consequently there are two other challenges within this existing BINO framework: (1) the diametrically opposed forces of speculative demand versus transactional demand; (2) decoupling coins from the ledger altogether. This presentation discusses several proposed solutions to the challenges currently being devised by a multitude of teams.
I just finished reading through the new sidechains paper (pdf). The team has clearly been thinking of clever solutions to a multitude of challenges.
Below are my first thoughts which could change as more information is released and/or code is implemented.
The biggest issue they did not address (so far) is how to incentivize mining after block reward halvings, though that probably was not their intent. Also, and again this is just day one, but it is also unclear if the IP will be released as open source and if someone could use that code to create Blockstream 2, 3, etc.?
My comments below each block quote:
Because the miners do not form an identifiable set, they cannot have discretion over the rules determining transaction validity. Therefore, Bitcoin’s rules must be determined at the start of its history, and new valid transaction forms cannot be added except with the agreement of every network participant.
Even with such an agreement, changes are difficult to deploy because they
require all participants to implement and execute the new rules in exactly the same way, including edge cases and unexpected interactions with other features.
How can this be done in a trustless manner? Mining was supposed to be anonymous. If they are identifiable by good actors, then they’re also identifiable by bad actors and not-so-good actors.
One problem is infrastructure fragmentation: because each altchain uses its own technology stack, effort is frequently duplicated and lost. Because of this, and because implementers of altchains may fail to clear the very high barrier of security-specific domain knowledge in Bitcoin[Poe14c], security problems are often duplicated across altchains while their fixes are not. Substantial resources must be spent finding or building the expertise to review novel distributed cryptosystems, but when they are not, security weaknesses are often invisible until they are exploited. As a result, we have seen a volatile, unnavigable environment develop, where the most visible projects may be the least technically sound. As an analogy, imagine an Internet where every website used its own TCP implementation, advertising its customised checksum and packet splicing algorithms to end users. This would not be a viable environment, and neither is the current environment of altchains.
Non sequitur. The same complaint could be leveled at German carmakers versus American carmakers with the fragmentation in something like unit of measurement (meters vs Imperial). The auto industry did not collapse because of fragmentation.
In addition, there is fragmentation within Bitcoin itself, with different pools relaying different types of transactions (or censoring others). A couple days ago Dominic Williams pointed this out (in a different email), that there are different payment processors and different wallets that are incompatible (you can send money between them, but you can’t open one wallet with another).
A second problem is that such altchains, like Bitcoin, typically have their own native cryptocurrency, or altcoin, with a floating price. To access the altchain, users must use a market to obtain this currency, exposing them to the high risk and volatility associated with new currencies. Further, the requirement to independently solve the problems of initial distribution and valuation, while at the same time contending with adverse network effects and a crowded market, discourages technical innovation while at the same time encouraging market games. This is dangerous not only
to those directly participating in these systems, but also to the cryptocurrency industry as a whole. If the field is seen as too risky by the public, adoption may be hampered, or cryptocurrencies might be deserted entirely (voluntarily or legislatively).
Why are floating prices considered a bad thing? Besides, the issues in this paragraph are exactly the same problem bitcoin faces each day and a solution to risks/volatility is not addressed in this white paper. See Ferdinando Ametrano’s paper as well as Robert Sams’ upcoming draft on Seigniorage Shares.
Our proposed solution is to transfer assets by providing proofs of possession in the transferring transactions themselves, avoiding the need for nodes to track the sending chain. On a high level, when moving assets from one blockchain to another, we create a transaction on the first blockchain locking the assets, then create a transaction on the second blockchain whose inputs contain a cryptographic proof that the lock was done correctly. These inputs are tagged with an asset type, e.g. the genesis hash of its originating blockchain.
This has me thinking about token history and fungibility. Perhaps it could be argued that moving these coins to a sidechain is an act of “mixing.” Are atomic swaps a form of mixing?
This is true for almost all aspects of Bitcoin: a user running a full node will never accept a transaction that is directly or indirectly the result of counterfeiting or spending without proving possession. However, trustless operation is not possible for preventing double spending, as there is no way to distinguish between two conflicting but otherwise valid transactions. Instead of relying on a centralised trusted party or parties to take on this arbitration function like Bitcoin’s predecessors, Bitcoin reduces the trust required — but does not remove it — by using a DMMS and economic incentives.
It is still unclear what the additional economic incentives will be in the Blockstream/sidechains model. Is it just the fees in section 6.1, such as the clever time-shifting mentioned later on?
This gives a boost in security, since now even a 51% attacker cannot falsely move coins from the parent chain to the sidechain. However, it comes at the expense of forcing sidechain validators to track the parent chain, and also implies that reorganisations on the parent chain may cause reorganisations on the sidechain. We do not explore this possibility in detail here, as issues surrounding reorganisations result in a significant expansion in complexity.
What are the costs of running and maintaining this validator?
No reaction. The result is that the sidechain is a “fractional reserve” of the assets it is storing from other chains. This may be acceptable for tiny amounts which are believed to be less than the number of lost sidechain coins, or if an insurer promises to make good on missing assets. However, beyond some threshold, a “bank run” of withdrawals from the sidechain is likely, which would leave somebody holding the bag in the end. Indirect damage could include widespread loss of faith in sidechains, and the expense to the parent chain to process a sudden rush of transactions.
Who determines insurance of a blockchain? Will FDIC or similar bodies have jurisdictional grounds as described in the above USC citation (not a joke, Blockstream founders are not anonymous nor most large farm & pool operators)?
As miners provide work for more blockchains, more resources are needed to track and validate them all. Miners that provide work for a subset of blockchains are compensated less than those which provide work for every possible blockchain. Smaller-scale miners may be unable to afford the full costs to mine every blockchain, and could thus be put at a disadvantage compared to larger, established miners who are able to claim greater compensation from a larger set of blockchains.
We note however that it is possible for miners to delegate validation and transaction selection of any subset of the blockchains that they provide work for. Choosing to delegate authority enables miners to avoid almost all of the additional resource requirements, or provide work for blockchains that they are still in the process of validating. However such delegation comes at the cost of centralising validation and transaction selection for the blockchain, even if the work generation itself remains distributed. Miners might also choose instead to not provide work for blockchains that they are still in the process of validating, thus voluntarily giving up some compensation in 360 exchange for increased validation decentralisation.
How can that be done trustlessly? How does that deal with the issues Dave Hudson talked about with respect to IHPP in general? Until IHPP is changed or modified, Hudson’s models will remain valid.
By using a sidechain which carries bitcoins rather than a completely new currency, one can avoid the thorny problems of initial distribution and market vulnerability, as well as barriers to adoption for new users, who no longer need to locate a trustworthy marketplace or invest in mining hardware to obtain altcoin assets.
This doesn’t seem to be addressing several other reasons for why alts exist: who will pay independent developers wanting to build on sidechains? What about non-SHA-based hardware (like scrypt or X11)? What is to prevent someone from forking “sidechains” code and creating a similar business?
An alternate mechanism for achieving block rewards on the sidechain is demurrage, an idea pioneered for digital currency by Freicoin (http://freico.in). In a demurring cryptocurrency, all unspent outputs lose value over time, with the lost value being recollected by miners. This keeps the currency supply stable while still rewarding miners. It may be better aligned with user interests than inflation because loss to demurrage is enacted uniformly everywhere and instantaneously, unlike inflation; it also mitigates the possibility of long-unspent “lost” coins being reanimated at their current valuation and shocking the economy, which is a perceived risk in Bitcoin. Demurrage creates incentives to increase monetary velocity and lower interest rates, which are considered (e.g. by Freicoin advocates and other supporters of Silvio Gesell’s theory of interest[Ges16]) to be socially beneficial. In pegged sidechains, demurrage allows miners to be paid in existing already valued currency.
I am not sure Freicoin is a particularly good example here because in practice few participants want an asset to always lose value (what investors actively demand demurrage?). Maybe this is reflected in its lack of adoption (thus far). Perhaps that will change, perhaps Freicoin will grow over the course of the next few years. But this also touches on the issue of whether or not these “coins” are commodities or a currency in the first place (I have argued they are informational commodities).
The point about reanimation is an interesting one (and good) because of the uncertainties of “zombie” coins (as John Ratcliff calls them) that jump back onto the market.
Also, while the experimentation use-cases in section 5.1.1 seem to have some active demand (as measured by crowdsales and hype this past year) they could also (IANAL) lead to legal issues that these 2.0 projects are having with respect to unregistered securities (see the SEC with its Howey test). This is a legally risky area as discussed by these lawyers. Also, if users can create digital tokens pegged to real world assets — if these are non-deliverable, does this turn that chain into a large “bucket shop“?
Co-signed SPV proofs. Introducing signers who must sign off on valid SPV proofs, watching for false proofs. This results in a direct tradeoff between centralisation and security against a high-hashpower attack. There is a wide spectrum of trade-offs available in this area: signers may be required only for high-value transfers; they may be required only when sidechain hashpower is too small a percentage of Bitcoin’s; etc. Further discussion about the usefulness of this kind of trade-off is covered in Appendix A.
Readers may be interested in a few more of my thoughts below. [Disclosure: I am an advisor for Hyperledger and head of business development at Melotic.]
As of today, Koinify is probably the only serious venture-backed startup that solely focuses on building decentralized applications and decentralized autonomous corporations (DACs). It is also setting some ‘best-practices’ in transparency that has been largely missing in this community. You will see that soon with Koinify’s following announcements.
The biggest problem in the altcoin/decentralize app space is that virtually all of them lack any original utility, are blatant scams or simply cannot fulfill the paper-based promises of their vocal promoters. In short, virtually all digital asset projects have thus far been overpromised and underdelivered, including, arguably Bitcoin itself and we see that with a dearth of mainstream end user adoption for any of them. What I’d like to help provide Koinify is the knowledge of the past, to avoid the pitfalls of other projects. To accomplish this, Melotic is looking to provide liquidity to unique curated assets, potentially those incubated at Koinify. Thus, this is a mutually beneficial partnership.
I have been following the growing list of distributed computing and computational consensus proposals. Beyond the annual academic Dijkstra Prize, the nascent digital currency space has been fast in proposals but slow in actual production-level roll-outs. To be frank, I have been fairly disappointed with both the quality of product and traction of 2.0 projects in general, especially given the community euphoria in the first quarter when I did research for Great Chain of Numbers. However, with that said, if something like Bitcoin is allowed to be given a 5-6 year “grace period” I think it is only fair for a similar runway to be given to other proposals as well. Furthermore, there are economic trade offs depending on the level of trust and consensus required, but shoving everything onto one ledger, some kind of jack-of-all-trades Houdini ledger, is a bit like the clown car at a circus. It can be filled with a cornucopia of clowns and coins (and clowncoins) but the economic incentives might not align with the duct tape holding it together. Consequently, the community has evolved and created several new potential methods for untrusted nodes on a public network to arrive at consensus, to the point where consensus-as-a-service is becoming its own commoditized subindustry. In the future, this will likely be abstracted away and developers will be able to fine tune and granularize the level of centralization and trust they want to expose their users to. Another big development that I am increasingly paying attention to is the regulatory and compliance arena, which many people seem to want to ignore and handwave away. It is not going to disappear and structuring your project, company and even ledger in a way that reduces your personal liabilities will be an ongoing concern from now on. There is no point in being a martyr when there are many other areas to push the envelope on in this expanding space.
A few weeks ago I gave a presentation covering a number of factors as to why Bitcoin protocol development has plateaued in the past year and as a result how most of the innovation has effectively been outsourced to the altledger ecosystem. Here a steady stream of both old and new entrepreneurs and developers are toying with variables that cannot be touched with Bitcoin itself due to its current development cycle. A friend compared the speed at which this industry moved with dog years and this is particularly true in the altledger space. As a result, a new ledger can be forked, tweaked and spun up that incorporates the latest ideas in this space. Most do fail and will likely fail in the future, but that’s the nature of iteration in technology. The biggest challenges for Koinify is on boarding high quality decentralized apps that bring the utility and value that is now expected by the community. On the one hand creating a platform that allows access to something like cryptosecurities such as Overstock.com sounds neat, yet it is a hundred year old idea (equity) married to a different type of database (a blockchain). On the other hand, the decentralized app economy that Koinify is attempting to create is in fact has a different form, yet still pragmatic enough given existing technology. Market participants want to experiment, poke, prod and have choices — this effervescent vitality is attractive and I am excited to try and help out.
Turns out about 15 months ago, someone had already figured out how the mining costs of hash-based proof of work moved relative to the market prices of tokens, see “Why Bitcoin will never be a good store of value” by Stefan Loesch. One common retort to Loesch’s argument is that at some point in the future, for some reason, users will one day start paying higher tx fees. This is unlikely because it is a collective action problem. Why would people pay several orders of magnitude more to have the same exact service?
A new feature/dashboard that I came across is CoinGecko — has some interesting metrics to look at.
Other links related to digital currencies and China (linking is not an endorsement of service, coin, chain, etc.):
Readers may also be interested in a few other comments I provided them, a few of which are slightly edited (removed some names and numbers):
I should preface this by saying that the OTC/off-chain liquidity/inventory is something that is not being factored into most of the overall discussion on trade volume. I know that all the mining farms in China have liquidity partners (usually with the big three exchanges) and I could introduce you to one in particular who might be willing to talk on the record, or at least give you color. The reason I mention this is because if you can some how dig up the OTC/dark inventory numbers, the aggregate volume might actually be larger in USD than RMB (at least, that would be my guess).
To answer your first two questions I think it bears mentioning that there really hasn’t been any new VC-backed exchange that has setup in the US in the past 6 months or so (itBit moved its SG operations to NYC). Perhaps once the legal issues are more defined this can change.
In addition to having no fees on trades, I think this short comment on reddit describes some of the internal structural differences at the Chinese exchanges for question #3.
They’re busily trying to answer question #4 with a variety of value-added services like margin trading and issuing of derivative products as well as integrating with API services and even building out support for mining contracts (BTCChina apparently just acquired a mining pool/farm to do just that).
As far as your last question, I think it would be fair to say that public/open consumer-based exchanges are centered in China, but based on the OTC numbers that I hear throughout each month, USD is still probably bigger. For instance, BitPay sells around XXXX BTC a day to its liquidity partners. That’s usually more than ______ does (at least this past summer). Their daily sales are chopped/sliced up and sold to liquidity partners. Charlie Shrem briefly touched on this a week or so ago.