As the business of blockchain has evolved into real use cases, it has become apparent that there are at least two paths for current cryptocurrencies:
1. Transactional unit of exchange (as in ETH and others)
2. Store of value (as in bitcoin (BTC))
In this three-part series, we address the requirements to be successful for each path and the potential for size of network and value proposition for them to be able to compete with incumbent systems such as gold (store of value) and payment systems (VISA, Union Pay, etc). In the third installment, we take a look at the public and soon to be public market mining companies and assess their chances for success.
Cryptocurrency as a replacement for fiat transactions
The use of public ledger blockchain solution to underpin global payments systems is predicated on three major requirements:
1. The public ledger can scale to manage the high transaction volumes required to compete with incumbent payment systems.
2. The public ledger can compete on costs with incumbent systems.
3. The public ledger provides or exceeds the security of incumbent systems.
Can the Public Ledger scale to meet transaction throughput requirements?
The first of the 3 requirements for the success of a public ledger blockchain is that the system can scale to match the transaction throughput requirements. Given the nature of Proof of Work systems, current throughput is in the range of 6–30 transactions per second whereas incumbent systems are orders of magnitude larger. It must be stated, the addition of more computing (hashing) power does not increase transaction processing speed. More computers only mean a higher number of entities chasing the block solution. Blocks will be solved more quickly with more computing (hashing power) but block production is controlled by difficulty. When block production deviates too much from the stated block production time (eg 10 minutes BTC, 14 seconds ETH), the difficulty is either increased or decreased to lengthen or extend block production time respectively. Given the desire to solve blocks over set time intervals, a very short time period for block production –say under 1 second becomes problematic as latency within the network to “catch all of the nodes up” becomes rate-limiting. Therefore transaction scaling cannot occur without off-chain or side-chain transactions. Ethereum moving to Proof of Stake (POS) versus Proof of Work (POW) is being done for broader business reasons (energy efficiency, others) but still requires the creation of an off-chain scaling solution. If POS cannot work for whatever reason, a POW system still could provide the underlying backbone for the ecosystem — read on to find out how!
So just how big is the transaction market?
Broadly speaking, physical cash transactions and non-cash transactions are both increasing but the rate of increase of non-cash transactions is significantly higher. The non-cash marketplace is likely to become dominant in most countries by 2026 (Khiaonarong and Humphrey, 2019). The required computing power by such systems can be estimated based upon the current transaction suppliers and their operating costs and the projected growth of the non-cash digital token/currency markets.
In 2016, CapGemini reported that the number of global non-cash transactions was 482.6 billion (CapGemini, 2018). North American markets provided 161.1 billion of the total. The IMF in April 2019 reported cash transactions to comprise 27 percent of US transactions in 2017 (Khiaonarong and Humphrey, 2019). This suggests that the move to a completely cashless transaction society in North America would provide electronic transaction growth potential of 30–40 percent (69–101 billion transactions).
CapGemini suggests non-cash transaction growth is expected to occur at the historical rate of growth for mature non-cash markets at 5–6 percent per year (2018). At a 6 percent growth rate, ignoring population growth and potential increasing cash use, it would take 6–8 years to fully transition to a cashless society.
For developing countries, non-cash transaction growth is more rapid but there is a large volume growth available as measured in transactions per capita. The United States, Finland and Sweden have the highest non-cash transaction per capita ranking at about 440 Tx/capita/annum while China, though growing rapidly, still has less than 50 Tx/capita/annum (CapGemini, 2018). In other words, there is a massive growth potential for non-cash transactions globally and cryptocurrencies as payment systems would like to capture new market share and/or cannibalize existing market share if they are able. Regulatory oversight, of course, has the potential to massively affect non-cash transaction growth rates both positively and negatively.
Putting together the above analysis, in North America, there is an existing market of 161 billion Tx and a theoretical market size of 230–270 billion Tx assuming a move to a completely non-cash market design for payment/value exchange transactions. CapGemini suggests the number of transactions globally to rise to 876 billion in 2021 with North America contributing 212 billion of the total. Unless physical cash is no longer supported for transactions, this appears to be nearing the practical limit of the number of non-cash transactions as cash use will persist for a certain percentage of all populations (unless cash is regulated out of existence!).
Assuming a reasonable growth rate in the non-cash transaction market, over time rising to perhaps an average of 550 non-cash Tx/capita/annum, the global non-cash payments over time should develop over time as follows in Figure 1.
Figure 1: Projected Global Non-Cash Transaction Growth
Because of its early adoption of non-cash payment systems, North America should reach its practical non-cash transaction limit over the next 6- 8 years and then grow only minimally. By 2025 the global non-cash transaction volume should be nearing 1.3 trillion Tx or 2.7 times the 2016 estimate. By 2035 the global non-cash transaction market could be as large as 3.3 trillion Tx/annum (a seven-fold growth).
Who are the current players in the non-cash transaction markets?
The current incumbents in the non-cash payment world are dominated by 3 major platforms and 3 minor platforms that provided approximately 368.8 billion of the 482.6 billion transactions in 2018 with the balance of transactions split through a large variety of smaller entities. The businesses enjoy extremely robust operating margins and that is why new entrants are using cryptocurrencies as an entry point into this lucrative market (Facebook, Apple, many others!). The end result will be that new competition will erode margins and the cost structure will change.
Table 1: Largest Incumbent non-cash transaction entities and their estimated revenues and operating costs
Based upon data published by MasterCard for 2018 and assuming similar costs for both smaller and larger companies, the total data processing costs for the six largest non-cash entities in 2018 are estimated at 2.43 B USD and the total operating expenses are estimated at 27.5 B USD.
Assuming a fight for transaction market share between incumbents and cryptocurrencies, there is a bounded range of potential outcomes:
At the high end, cryptocurrencies could capture similar revenues per transaction as the incumbents in a growing market
At the mid-point, cryptocurrencies drive operating margins for incumbents to zero and match the overall operating expenses of the incumbents (these operating expenses include a lot more than data processing!).
At the low end, the incumbents are forced to reduce their operating costs to just above their data center costs, in which case cryptocurrencies would need to match data center costs of the incumbents.
The most likely outcome, with a still-growing transaction volume and increasing competition, is somewhere between the low and mid-point whereby incumbents are forced to reduce their operating costs to compete and margins remain at or just above data center costs. Cryptocurrencies ultimately must provide a competitive cost solution to capture market share — either from the existing market or to capture new market growth. Downward pressure on transaction margins is expected to occur rapidly even though the market is growing due to the number of new competitors entering the market.
Can a POW based Public Ledger compete on costs?
As shown in Table 1, transaction costs are bound on the upper end by the revenues earned by incumbent payment systems. Therefore, a scaled global POW ecosystem, assuming no profit margin, matching incumbent provider data center costs, would support 2.43 B dollars of hashing costs for the existing market size. If the global POW systems could achieve similar revenues as the incumbent systems then there is 60.9 B dollars at a maximum of available market revenues, all else being equal. Accordingly, with a potential revenue range of 2.43 B dollars to 60.9 B dollars, the range of global POW systems based upon a 0.05 USD/kWh cost of electricity would range from 7,900 MW to 198 GW.
Using Bitcoin as an example token, if one looks at the amount of tokens mined daily (approx 1800), one quickly sees that the value of Bitcoin to support 198 GW of miners is 92,694 $/BTC. Unless there is dramatic increase in the price of BTC this is not supportable. It is even less supportable once the halving occurs in May 2020. It also suggests that the current cost structure for transaction payment processing will not be eroded by competition. Fat chance!
What is shown in Table 2 is that a POW based system of 7,900 MW could conceivably compete on operating costs assuming, of course, that they could process the same number of transactions.
Table 2: Size of POW mining ecosystem based upon the incumbent cost structure
In reality a cryptocurrency mining operation needs about 2–3 times the annual electricity costs in mining revenues to pay for return on capital invested, capital replacement and other operating costs (we can share our analysis for those that are interested email or PM us). This adjustment is shown in the Table 3.
Table 3: Required BTC price to support required mining revenue
So, all things being equal, at a 10,000 USD/BTC price, a global POW mining community of about 7,900 MW could theoretically be supported at the current BTC issuance rate. The challenge is that the global average of 368.8 billion transactions (Tx) per year is an average of 11,695 Tx/s. The BTC network can manage only 6 Tx/s so it would need to scale approximately 2,000 times. Scaling therefore must occur above chain via vastly different software protocols and/or via above chain layers, not via a vastly larger network of POW miners, as more miners does not mean more transaction throughput.
It’s not the megawatts, it’s the number of unique and individual participants that matters
The most important facet to be addressed in a POW based distributed ledger is the true level of distribution among market mining participants.
Are five large mining pools controlled by major market participants adequate to ensure transaction validity? Are ten? What about 20? The ideal system would have no controlling market participants and there would no joint venturing by participants to increase their chances of success. This unfortunately is a denial of human behavior. We touch upon the nature of distribution challenges in our discussion further on under the POS ecosystem.
The transaction market is expected to grow………………..
If one believes, and we do, that public ledger-based cryptocurrencies will find software solutions to scale¹ and therefore provide competitive services sometime over the next 5 years then public ledger cryptocurrencies have a larger future (some might argue they already have in some systems shown this ability!). Until that time, it is unlikely that cryptocurrencies will capture significant market share of the global transaction market. POW miners may continue to enter the market with new mining equipment and bright hopes and dreams but any forecast of a growing market for miners needs to be balanced against the reality of the underlying ecosystem capability.
It is reasonable to assume that if over next 10+ years cryptocurrencies can capture a significant (say 20–25 percent) market share of transactions, that would support a transaction volume of 700–800 million Tx/annum. Given the costs for incumbents to currently supply an approximately 500 million Tx market, that suggests that if scaling occurs, there is room for up to 13 GW (90 TWh/y) of POW mining capacity using current state of the art mining equipment. Given that POW mining can compete at the current transaction level, it is then reasonable to assume that POW miners will continue to maintain some level of market share. Whether this is 50 percent or 10 percent with the balance held by POS type ecosystems remains to be seen.
The profitable portion of the POW market size, therefore, is currently approximately 5–6 GW (35 TWh) assuming the entire market uses current state-of-the-art miners and could rise to much as 13 GW (90 TWh) within the next 10+ years with minimal growth over the next 5 years as cryptocurrency ecosystems develop the ability to scale to compete with incumbent systems. The 13 GW estimate is affected by the assumed market share captured by cryptocurrencies as well as the mining/validation model assumed. This amount of energy is hardly country swallowing volumes and its environmental impact, if supplied by renewable energy, will be small relative to global energy use.
Can public ledgers match the security of incumbent systems?
A novel rivaling Tolstoy’s War and Peace could be drafted to address this aspect of the pros and cons of public ledger cryptocurrencies vs incumbent payments systems. It would be safe to say that both systems have their merits and demerits when it comes to security risks for the network. No system is completely infallible and it can only be plainly stated that a distributed public ledger faces different risks than a single point transaction ledger and therefore requires different solutions to ensure network security.
POS vs POW — the why and the why not?
Etheruem has already made a concerted move from a Proof of Work ecosystem towards a Proof of Stake ecosystem that will be implemented sometime over the next year if completed on schedule. There are numerous descriptions of how the two approaches work available in the public domain and therefore a description of their workings will not be addressed here. What we do address are the three or four primary drivers for this change and the potential challenges facing Ethereum as it moves to the POS ecosystem.
1. To reduce the energy footprint (costs and environmental impact)of the network
2. To reduce the ecosystem latency to allow faster transaction throughput
3. To keep validators on the system by offering more rewards to those that have remained on the ecosystem for a longer period of time
4. Maintain or at least attempt to maintain a very broad distributed ledger with a high number of node participants
The most basic reason to move towards a POS model is the cost of operating the underlying computing network (also its potential environmental impact of the electricity is generated by non-renewable technologies). Per its’ 2017/18 Annual sustainability report, VISA states that it uses approximately 17 MW of energy to run its network. On the most basic level, a public ledger system must be able to compete with that.
Although we demonstrated earlier in this paper that a POW network of reasonable scale appears to be able to compete with the single point networks, it does have a larger environmental footprint. The use of renewable energy to supply the POW mining network can alleviate most but not all of these concerns.
The second advantage point of the POS system is driven by the fact that the structure selects via lottery a single validator (“miner”) to create a block which is then confirmed by other validators so the system latency is reduced along with energy use.
The third advantage is that miners choose to mine the coins/tokens that will earn them the most rewards. By rewarding longer-term validators with improved probability of success regarding the chance of being selected as block validator (and therefore higher chance of rewards) as well as interest on posted performance collateral is a strong solution to keep validators on the network.
The primary challenge we see with the Ethereum POS approach is maintaining the balance for a widely distributed/decentralized ledger with the nothing at stake problem. The posting of 32 ETH as “ staking collateral” for good performance as a node/validator on the network does promote a broader distribution of the ledger but it remains open as to whether the potential of loss of 32 ETH is adequate to deter/prevent “bad behavior” and how much of the network will actually participate.
Based upon the December 12, 2019 USD/ETH conversion rate of 143.23 USD/ETH and 108,552,553 issued ETH, the Market Cap of Ethereum 15.548 B$. A single stake of 32Eth is the equivalent of 4,583 USD based upon the 12–11–2019 exchange rate. What percentage of the market will be staked is a question. Table 4 shows the number of potential individual validators for the ecosystem, assuming single-stake validators and 10% of the total issued and outstanding ETH being staked.
Table 4: Number of Validators per Size of Stake
The case that best matches the individual stake size is the last one in the table that suggests that 350,000 individual stakers are possible at 32 ETH staked. It is unlikely that 350,000 stakers will participate and if only larger parties participate, say staking the equivalent of 1.5 million $, then only 1,000 stakers would be supporting the network. Outstanding questions certainly remain — will more or less than 10% of the total amount of ETH be staked and how many individual/unique stakers will participate? Will the network remain secure without larger securities being posted?
If for some reason a POS system is not stable, all is not lost as our work seems to suggest that a POW ecosystem likely can compete on cost with incumbents.
Hear that BTC developers — get to work on your off-chain and side-chain overlays!
For more information see our website: www.biresearch.ca
Note: this article was previously posted to medium here.
Next in the series: Bitcoins role within the next global monetary system
¹ Non-public ledgers (effectively private ledgers such as Ripple, NEM, NANO ) have already shown that can scale to competitive transaction rates
CapGemini. BNP Paribas. (2018). World Payments Report 2018. P. 56.
Khiaonarong, T., and D., Humphrey. (2019) IMF Working Paper. Cash Use Across Countries and the Demand for Central Bank Digital Currency WP/19/46. Monetary and Capital Markets Department. P. 43.