Here is our talk from the CryptoFin Conference from October 2019 in Tallinn about how to disintermediate the banks: Here is the short summary. We need: More tokenization Crypto credit-money...
Here is our talk from the CryptoFin Conference from October 2019 in Tallinn about how to disintermediate the banks:
Here is the short summary. We need:
We look in this article on the risk management of the custodial crypto lending platforms and of non-custodial crypto lending platforms. The aim is not to say what is right...
We look in this article on the risk management of the custodial crypto lending platforms and of non-custodial crypto lending platforms. The aim is not to say what is right or wrong, but to create transparency about both business models from the risk point of view.
Custodial crypto lending platforms
We look here on Nexo.io and on Celsius.network. Both systems represent custodial lending systems. Clients transfer their assets into platform wallets and platforms control their assets. Platforms then lend out the assets via marketplace or institutional channels. Platforms receive interest, they keep smaller parts of the interest and the clients receive the bigger part of the interest.
Nexo.io and Celsius.network have bought insurance policies to cover the client asset losses on their platforms. They pay a yearly fee but their coverage is capped at a fixed amount.
Everything sounds nice here, but where are the limitations?
We have two key sub-types of lending:
Lending via marketplace – platform’s offer to their borrowers their lender’s funds. The platform sets the collateral requirements, controls the margin and de-facto manages/controls the full process. That’s a lower risk than the second sub-type.
Lending to the institutional channels – platforms pool their client assets and slice them and lend them to their institutional partners. Platforms make the OTC deals with margin lending programs of crypto exchanges or hedge funds. Contract specific parameters like collateralization ratios and durations will be fixed and the crypto-assets will be transferred to the contracting party. While the contract for the marketplace lending is public, then these contracts are private.
From this moment we have to trust the contracting party and his lending/margin management processes. We have to trust as well, that the contracting party will not be hacked or the assets are not frozen because of regulatory issues (think Bitfinex and 850 mUSD) and many other risks. This lending sub-type has a higher risk than the first sub-type. The key difference between these sub-channels is the following – in case of the first subtype, the platform can manage the end-to-end process. In the case of the second subtype, the assets are under the legal control of someone else…
Of course, there are contracts in place, but let’s keep in mind two cases from not so distant traditional finance history:
Lehman Brothers are still notliquidated, but is still in the liquidation process. It just takes time to unwind all these OTC contracts.
MF Global bankruptcy, where client assets were placed as collateral against the MF Global proprietary trading desk trades. When these trades failed (yes, black swans come more often than one thinks), then the client assets of 600 mUSD moved over to the counterparty (JP Morgan), MF Global went bankrupt and clients lost their assets from one day to the next.
In traditional finance, we have a sector called “prime brokerage”, which is providing services, especially to the hedge funds. Investment banks pool their client assets, which are lent to hedge funds, which pay interest for them. Hedge funds borrow these assets for short selling (you borrow an asset, sell it and hope to buy it back at a lower price).
If the trade works, then you make a nice profit. If the trade is not working, then the margin calls are issued to the hedge funds. If the trade goes totally wrong, then the hedge fund is not losing only the collateral but has to put in additional money, to cover the losses. If they, don’t have this money, then they are bankrupt. The pooled and sliced client assets will be part of bankruptcy proceedings.
That’s why the “primer brokerage” the business has high-interest margins. It’s because of the high risk. That’s the same business that the crypto lending platforms are doing with their institutional clients.
Do we have some regulatory licensing here?
Yes, we have. The vision of the regulations is to create a fair marketplace for service providers. The reality of the regulations is that they create the entry barriers for the non-members of the club. It’s just because of the revolving-door-phenomena – the regulators hire their people from the private companies in the sector, which will by nature protect their sector. And the private companies hire as well people from regulators, let’s call it – for preferred information and access.
The current regulations state (de-facto in all countries) is following – if you control client assets, what the custodial platforms do, then you will need a financial intermediary license. You not only need to apply for this, but you also have to maintain it year by year.
Custodial platforms provide the services in “cross-border mode” to other jurisdictions as well. But that’s where it gets interesting – providing “cross-border service” to other jurisdictions is OK, but doing marketing for a platform is not OK, except when the platform has registered in the respective jurisdiction. In the case of the U.S., it’s even more complicated – it’s enough to have cross-border service clients from the U.S. and the platform will need U.S. licensing (think here on the NY Attorney General versus Bitfinex case because of presumably 1 NY client on Bitfinex platform).
Let’s summarize the business models of custodial crypto lending platforms:
Someone else has the private keys to your assets and controls them, till you withdraw your assets. But you receive interest for depositing your assets.
Platforms have contracts with the liability insurance providers, these contracts are usually capped at a certain amount to protect the insurance providers.
Lending via the institutional channels can be quite risky, the asset pooling, slicing and transferring works in most of the cases fine, till it doesn’t (black swans come more often than anticipated)
Financial intermediary licenses would be required because these platforms control the client assets
Non-custodial crypto lending platforms
We look here on MakerDAO and Compound.finance as examples. We look only at their AS-IS business model. Their model is simple:
The platforms do not have access to the client assets, so they will not need regulatory financial intermediary licenses
There are no assets transfers to the institutional borrowers, there are no OTC contracts with the margin lending programs of central crypto exchanges
There is no insurance with insurance providers
The loans are protected with collateral, usually with pretty high collateralization ratio (300% +)
But what can be the failure points?
The main failure points are the respective smart contracts, but as these contracts are open source and they have been audited, then the probability is low.
Failures in the smart contracts of other platforms, for example, 0x decentral exchange, which are used for the collateral liquidation
External price feeds into the smart contracts
About the black-swans
Black swans are defined as 3-sigma (standard deviation) events and they should be very seldom events. Funnily there are more black swan events than the statistical theory allows. Are the statistics wrong?
No, it’s just the wrong statistics which are used – the financial markets are modeled based on the random-walk-hypothesis (which has never been scientifically proved, it’s just as the name says – “hypothesis”) and this hypothesis implies using of the standard distribution (as everything is random, then this would be logical conclusion).
But the financial markets act based on the power-law distribution, as most of the things in nature. And by this distribution we have a much higher frequency of the black swans, meaning there are many more risk events than anticipated.
Summary
We looked at the risks in two different crypto lending business models – custodial and non-custodial. The custodial business model is rather similar to traditional financial intermediaries. The non-custodial business models are new innovative business models.
Regarding the platform risks – we will not say which platform has fewer risks.
However, we refer to the common-sense hypothesis – if comparing two different models, then:
We have to look at the number of potential failure points in the model
The model with fewer failure points will be more resilient
There are the custodian and non-custodian crypto lending platforms. The key difference between them is who controls the assets - the first ones control your crypto assets, by the second...
There are the custodian and non-custodian crypto lending platforms. The key difference between them is who controls the assets – the first ones control your crypto assets, by the second ones it’s you who is controlling your assets.
Both of them propagate the interest rates on their platform, as the key benefit for the borrowers and lenders on their platforms. But is the interest rate really all and everything, what should be followed?
Our answer is – actually not. While interest rates and risk management are the key drivers for the lenders, there is one more parameter to be followed – the capability to borrow for the borrowers.
Crypto interest rates
Here are current interest rates for DAI (they are pretty similar to the USDC)
Borrowing rates DeFi DAI
Source: https://loanscan.io/borrow/historical?interval=3m
The interest rates between custodial and non-custodial platforms are more or less the same. Non-custodial platforms are saying that custodial interest rates should be higher because of more risks (hacks, loss of assets, etc). Custodial platforms are saying the non-custodial interest rate should be higher because of potential mistakes in smart contracts.
Therefore, let’s use the https://loanscan.io data as a basis.
Crypto collateral rates
Here are for example current DeFi (Decentral Finance) collateral rates:
Let’s imagine two scenarios for the borrower: Scenario A
Loan amount: 100 units
Collateral: 300 units
Interest: 10%
Scenario B
Loan amount: 100 units
Collateral: 150 units
Interest: 10%
The interest rates in both scenarios are the same, but the Loan To Value (LTV) is different:
In Scenario A: 100 / 300 = 33%.
In Scenario B: 100 / 150 = 66%, which is twice as much as in Scenario A.
Capability to borrow shows, how much can borrower borrow on his given asset basis. If the borrower would have two similar offers with different LTV’s, then the borrower should choose the one with higher LTV. What does it mean?
The capability to borrow does not matter to the lenders. Lenders are interested in:
Risk management (which is done fully with the collateral)
Liquidity after lending out their funds (capability to call in the loans or tokenize the loans)
But the capability to borrow matter’s very much to the borrowers:
It’s not only the interest payable, which is relevant
It’s relevant, how much can the borrower borrow on given asset basis
Capability to borrow with different interest rates
Let’s imagine further two scenarios for the borrower: Scenario C (the same as Scenario A)
Loan amount: 100 units
Collateral: 300 units
Interest: 10%
Scenario D
Loan amount: 100 units
Collateral: 150 units
Interest: 15%
The Loan to Collateral Value’s (LTV’s) are different. The interest rates are different too. The loan amounts are the same. But which option is better for the borrower? Scenario C: LTV: 33%; Interest 10% Scenario D: LTV: 66%; Interest 15%
The borrower will pay in Scenario C for this 50% more interest for 100% higher LTV – the borrower will have higher leverage on his assets. If the borrower needs leverage, then Scenario D is preferable for the borrower – he would pay a little bit more interest for a much bigger loan
Reflection
Current DeFi and custodial platforms are using very high collateralization ratios. This is protecting the lenders.
However, the borrowers would be interested not only about the interest payable but about lower collateralization ratios, which would lead to the higher capability to borrow.
We analyzed the reasons for high collateralization ratio’s in another blog article. Here is the summary.
The risk management methods are rather one-dimensional, which translates into high collateralization ratios
The other risk management methods like credit-risk ratings or loss provisions funds or fixed-term loans are rather seldom used
SmartCredit.io approach
SmartCredit.io is funded from 2 CFA’s and ex-Bankers. The risk management is never a one-dimensional approach of over collateralizing the loans, but it’s a network of different measures, which on the end translates into usability:
The collateralization ratios are driven by the market dynamic (they are not something hardcoded in the smart contracts)
Credit risk ratings for the borrowers are used and allow to separate good risks from less good risks
Loss provision fund is there for the eventualities when the markets are moving too fast
Enforceable legal contracts are created in the background – a defaulted loan will stay a defaulted loan, till all the obligations are fulfilled
This results in the least factor 2 – 2.5 smaller collateral requirements as the current standard in the industry. Which results in a higher capability to borrow.
The current collateralization ratios are ca 300% + for the DeFi borrowing/lending protocols. These ratios benefit the lenders on these platforms because over-collateralization protects their loans. However, these ratios reduce...
The current collateralization ratios are ca 300% + for the DeFi borrowing/lending protocols. These ratios benefit the lenders on these platforms because over-collateralization protects their loans. However, these ratios reduce borrower’s capability to borrow and therefore the usability of the system.
This article analyses:
What are the current collateralization ratios in DeFi protocols and
What would be the means to reduce the collateralization ratio
Here are the current collateral ratios in key DeFi platforms:
The collateralization approach is directly linked to the risk management framework. The key here is to combine multiple risk management elements, which then leads from one side to the smaller collateralization ratio and from the other side to better risk management.
Here is the list of measures for collateralization reduction:
Loan Maturity
On Maker and Compound platforms the borrowers do have unlimited maturities.
The platforms protect themselves with the collateral liquidation, if for example, the collateral value sinks to 135% of the loan, then the Maker will liquidate the collateral. The same with Compound (the ratios might be different).
If we would have fixed maturity loan, then we could calculate via standard deviations and loan maturity, how much collateral we should have, so that by given probability we will not hit the liquidation threshold.
Step 1: Calculate 30-day standard deviation of the underlying collateral
Step 2: For calibrating standard deviation to loan maturity we have to multiply standard deviation with the square root of “loan maturity / 30”.
By doing this we can set the amount of collateral so that the liquidation probability will be low.
But Maker and Compound do not have fixed maturities, therefore it’s not possible to calibrate loan collateral to the loan maturity. This results in very high collateral requirements, which then reduces borrower’s capability to borrow. Could Maker use fixed maturities?
Maker DAO uses Collateral Debt Positions to create the DAI’s – borrower puts Ether into the Smart Contract (CDP) and receives the DAI’s. Having fixed maturities would imply fixed maturity CDP’s – borrowers would need to close these CDP’s before the maturity with paying in DAI’s into the CDP’s and receiving back the collateral. If the borrower forgets to pay in DAI at the right time, then the CDP would go into automated liquidation, independently from the collateral ratio. Could Compound use fixed maturities?
Compound could introduce fixed maturities exactly in the same way as Maker. As maturities have to match on borrowing and lending side, then lenders should make fixed maturity loans as well (otherwise we get into the maturity mismatch and “bank run” risk on the platform).
Having fixed maturities would imply moving away from the “money market fund with variable interest” rate, which would be quite a change into the Compound’s business model and smart contracts.
On-demand collateral requirements calculation
Some assets have lower standard deviation and their collateral requirements will be smaller. Other assets have a higher standard deviation, which leads to higher collateral requirements.
Collateralization parameters cannot be something static, which is fixed in the smart contracts, but need to be continuously re-calculated. If this is not the case, then the mitigation is to increase the collateral for any eventuality.
Loss provisions funds
Compounds and Maker’s approach is to over-collateralize for avoiding the worst market dynamics. But the other approach would be to use Loss Provision Funds to protect against adverse market dynamics.
If one can use only over-collateralization, then one has to prepare for the worst-case for every loan – i.e. for the non-paying borrower and for the collateral value flash crash for every loan.
If one would use over-collateralization plus loss provision funds, then the over-collateralization could cover till 2-sigma events and after that, the loss provision fund would take over. The result would be increasing the borrower’s capability to borrow.
Credit risk ratings
Current DeFi systems are not using credit risk ratings for the borrowers. From one side there are no systems available, which would provide this information, from the other side the DeFi systems are avoiding collecting any user data.
However, having credit risk ratings would allow us to separate good risks from less good risks. Good risks would get better collateral requirements and vice versa. Credit risk ratings would be the approach for the users to monetize their data – having good credit risk (and opening up his data) rating would result in better borrowing conditions.
Credit risk ratings would allow as well-diversified approach with the collateral handling. In case of good credit risks, one doesn’t need to rush into the collateral liquidation in flash crashes. However, in case of not good credit risk ratings or not opening up his data, one would need to liquidate the collateral during flash crashes.
Legal contracts and the NPL process
In traditional finance we have legal contracts. If the debtor is failing to meet his obligations, then the NPL (Non-Performing Loan process) will be started. Usually, the debt will be sold to the debt collection agencies, which are paying 5% – 20% from the amount owed. Debt collection agencies continue then with the NPL process against the borrowers.
Using the NPL process would require KYC. Many DeFi products see KYC as something that should not be followed. However, as KYC is the law in practically all countries, then we can just forecast that most of DeFi products start to use KYC as well.
Reflection
Current high collateralization ratios are driven by the respective business models. If we adjust business models, then we will adjust as well the collateralization ratios and increase the usability for the borrowers via increased capability to borrow.
SmartCredit.io approach
SmartCredit.io collateral requirements are by factor 2 – 2.5 lower than the MakerDAO or Compound requirements.
SmartCredit.io approach
It’s achieved via:
Fixed loan maturities
On-demand collateral requirements calculation
Loss provision funds
Credit Risk ratings
Legally enforceable contracts
This results in a higher capability to borrow with equal interest rates to other platforms.
Capability to Borrow
The lenders have unique features as well – the tokenization and transferability of their credit, which enables immediate liquidity to the lenders. And they have as well capability to define private fixed-income funds:
Some readers may remember the NASDAQ Dot-com bubble of 2000, but most readers will remember the Crypto bubble of 2018. In this article, we ask if we can leverage our...
Some readers may remember the NASDAQ Dot-com bubble of 2000, but most readers will remember the Crypto bubble of 2018. In this article, we ask if we can leverage our knowledge of NASDAQ’s 2000 bubble in forecasting future crypto trends? What are their commonalities? And what will happen next?
The NASDAQ Composite Bubble
NASDAQ composite is a stock market index of securities listed on the NASDAQ stock market. It is heavily tilted toward information technology companies. NASDAQ composite was launched in 1971 with a starting value of 100 and it peaked at 5132 in March 2000. After that, it fell to 1108 in October 2002, a — 78% decline. This was the dot-com bubble.
NASDAQ has recovered from these lows and the current price is around 7400 (in Feb 2019).
The Crypto Bubble
Here, we use Bitcoin as a proxy for the crypto markets. It reached a top price of 19500 in Dec 2017, and the current low, 3250, in Dec 2018. This represents an 84% decline.
Many believed, like in the NASDAQ 2000, that “this time it is different” or that it’s “the new economy”. It wasn’t so.
Analysis of the NASDAQ bubble
The dot-com bubble was driven by the belief in new technology — the Internet. The NASDAQ Composite was full of stocks which lacked real business potential.
The initial focus was on broadband cable companies, which were seen as a new infrastructure which would eventually generate huge revenues. However, this resulted in the oversupply of broadband infrastructure, internet connectivity prices collapsed and with them the stocks of the respective broadband companies as well. The positive outcome was that Internet broadband became a commodity and became available for most of the population.
The real business models of the Internet were not present before the dot-com bubble. These new, so-called Web 2.0 business models — Amazon, eBay, Facebook, Google,… emerged after the dot-com bubble.
All of them started to generate revenues/benefits compared to brick-and-mortar models, which translated into huge Discounted Cash Flow based valuations thanks to the network effects (value of the network increases in quadrat to the growth of the nodes in the network):
Search (google)
Advertisement Model (google)
Social Networks (Facebook, LinkedIn)
Marketplaces (eBay, Amazon)
Online Merchants
Pay per use Web Services Models
Client Data / Client Behavior-based business models
The internet was and is a major disruption enabler. However, interestingly — the initial business models on the Internet tried to mirror the brick-and-mortar world into the Internet. It took 5+ years before the new disruptive revenue generating business models emerged.
Analysis of the Crypto bubble
The crypto-bubble was driven by the belief in new technology — in this case, the blockchain. CoinmarketCap.com was full of projects without real business potential (remember that it was believed that you didn’t need cash flow/benefit based valuations then).
The initial focus was on the “smart contract platform” systems, which were the key enabler of blockchain disruption. However, being the key enabler doesn’t mean revenue generation. It can mean becoming a commodity as it happened with broadband during the NASDAQ bubble.
Our forecast is that smart contract platforms will consolidate, there will be some global/central platforms and other rather region specific platforms. (Having a smart contract platform could be compared to the importance of having/controlling maritime sea routes two centuries ago).
However, it is not the most technically advanced platform that will win the race, it will be the platform with the most users by now. Winning the race doesn’t mean becoming a cash flow generator, it will rather mean becoming a commodity or standard in the industry.
So, who will be the new eBay’s, Amazon’s, Google’s for the blockchain economy? The answer to this is in the new disruptive business models — it’s about cash flow/benefit generating disruptive business models.
So, what are the real disruptive revenue generating business models on the blockchain? There are the following:
Base money — Bitcoin, it disintermediated the central banks privilege to create base money.
Privacy money — Monero, it disintermediated government agencies control over your privacy.
Stablecoins money — DAI, TrueUSD, etc — it disintermediates the SWIFT network for the fiat money transfers and bank accounts for keeping your fiat money.
Credit money — SmartCredit.io, it disintermediates commercial banks privilege to create credit money.
My data is mine models — it disintermediates Google & Co’s advantage of monetizing your data.
Supply chain models — it allows real tracking of who produced what, where, when and from which materials.
Decentralized energy — disintermediating centralized energy production to the decentral prosumers model.
Distributed storage/hosting — disintermediating the huge data centers of today.
Digital rights — disintermediating centralized media rights companies.
Tokenization — tokenization of the real world and financial assets, disintermediating the safekeeping accounts of commercial banks.
Asset Management — disintermediating the mutual funds’ industry through tokenized investment schemas.
These business models — money, credit, data, supply chain, energy, rights, and assets are by their nature decentralized. Adding a transaction fee per value-added business transactions will allow easy monetization and enables discounted cash flow based valuations. Adding a network effect will multiply these valuations.
Summary
The NASDAQ 2000 bubble and the crypto 2018 bubble were similar events. The next similarity will be what will happen afterward.
In both bubbles, the platforms (broadband or smart contract platforms) had the highest valuations. In the case of NASDAQ, broadband became the commodity. We expect the same from the smart contract platforms.
In the case of NASDAQ, the real value adding disruptive business models emerged. Real value-adding transactions drove the discounted cash flow based valuation of these companies.
Our forecast is that the same thing will happen in the crypto sector — new disruptive cash flow generating business models will emerge. The companies behind these models will become the new Facebooks, Googles and Amazons.
How to find these companies — it’s actually pretty easy:
Look in the ecosystems which are from the logical point of view decentralized by design, but centralized in the current implementation.
Look at the companies in these ecosystems, which will generate real benefits to real business problems.
Some of these companies will become new Facebook, Google and Amazon.
We have heard many people saying “this time will be different”. We don’t think so, we think “this time will be the same”. History will repeat itself. Major disruptions are driven by real value-adding business models. It’s all the same. It’s the economy.
Bitcoin is digital currency which enables instant payments to anyone and anywhere in the world. There are many differences to other currencies: · Other currencies are issued by Central Banks...
Bitcoin is digital currency which enables instant payments to anyone and anywhere in the world.
There are many differences to other currencies:
· Other currencies are issued by Central Banks and have the role of legal tender. Bitcoins are issued de-centrally; there is no Central Bank, and they are not legal tender.
· Other currencies have some physical representations (bills). Bitcoin exists only digitally.
· Other currencies have central authorities. Bitcoin has no central authority; validation of transactions is done from Bitcoin Network.
· Monetary Base of other Currencies is continuously increased, which translates into inflation in the long term. But in Bitcoin Network will contain only 21 Million Bitcoins (smallest transferable unit being 0.00000001 Bitcoins), which translates into deflation in the long term.
Bitcoins is based on combination of several existing technologies:
· Peer to Peer systems (like bittorrent)
· Private / Public key Cryptography
· Application of this combination for creating a currency
First Private / Public key cryptography algorithms were published in 1977. First famous Peer-to-Peer system was napster, published in 1999. However, it took till 2008 when Satoshi Nakamoto (pseudonym) connected peer to peer systems with state of the art cryptography to create first crypto currency — Bitcoin.
Bitcoin has properties of currency — its unit of account; it’s portable, durable, divisible and fungible. However, Bitcoins are much more just as a simple currency. Satoshi’s ideas went much further — Bitcoin Network is a mean to describe economic contracts and transactions between the participants of the Network. Additionally, the distributed storage of transactions (Blockchain in Bitcoin terminology) can be considered as a public general ledger, where not only simple payment transactions, but many more complex economic contracts can be stored and easily distributed / published to any node of the network.
Bitcoin price development from Aug 2010 till Jan 2014 is described on the following graph. It follows a linear trend on the logarithmic graph.
There have been several price corrections, which have received quite some media attention:
· In 2011 from 31 to 2 USD per BTC
· In 2013 from 266 to 50 USD per BTC
· In 2013 from 1242 to 455 USD per BTC
However, we hardly recognize these price corrections on the logarithmic scale.
Will this logarithmic growth continue? Where will be the price of one Bitcoin in one year? How to calculate the fair value of Bitcoin? This article evaluates approaches for Bitcoin valuation.
Bitcoin Network has currently 2’400’000 addresses. One person can have more than one address.
Value of the network is not growing linearly but in square with the growth of network members (Metcalfe’s law). I.e. if we have 2 times more participants, then the value of the network grows 4 times; if we have 10 times more participants, then the value of the network grows 100 times and so on.
Currently network grows by 7000–8000 addresses per day. If we assume same constant growth for the year, then number of addresses will double in this year, implying the value of Bitcoin Network will grow 4 times this year.
As we are speaking of ca 2 million people using the network then we are still in early phases on the Bitcoin Network development. It can be compared to “pre-Mosaic browser” phase of the Internet — there were many enthusiasts on Internet, but most of them were “techies”. The breakthrough happened when Netscape introduced Mosaic Browser. The rest is history.
There are several discussions about intrinsic value of Bitcoin Network. One side has the opinion that Bitcoin Network does not have any intrinsic value; other side has the opinion that there is high intrinsic value.
Bitcoin Network is like Internet network. It’s not the Internet that has the value, but its diverse products and services on top of Internet network, which create the value of the Internet. It’s the same with Bitcoin Network — it’s the products and services on top of Bitcoin Network, which create value for Bitcoins.
The most exposed intrinsic value is Bitcoin Network as Payment Processor:
Bitcoin Network allows instant Bitcoin transfers between any locations in the world practically at no costs.
The service fees of Payment processors (Visa, Mastercard, Paypal) will become obsolete
Micropayments worldwide will be supported; mobile payments worldwide will be supported too.
Additional intrinsic value of Bitcoin Network is the “base money” functionality and “value added services”.
Bitcoin enables payments just in time between any countries in the world it practically no fees. Bitcoin is current 9th biggest payment processor worldwide. Additional adoption of Bitcoin Network will result in reduced demand for the services of companies like Visa, Mastercard or Western Union.
Visa’s market capitalization is 140 B USD, Mastercard’s capitalization is 100 B USD, and Western Union is 9 B USD.
Let’s assume total market cap of these payment processors is 250 B USD, If Bitcoin Network would replace 1/3 of their businesses, then this result in price of 3929 USD per BTC.
Payment Processors total Market Capitalization (in B USD)250Substitution ratio with Bitcoins 33%Total Bitcoin Network Valuation (in B USD) 82.5Final Number of Bitcoins (in B USD) 21'000'000Value per 1 BTC (in USD) 3'929
Bitcoin can be considered as “base money”, it can be considered as gold — “crypto gold” in this case. One way to value Bitcoins is to compare the money supply of Bitcoins to U.S. money supply.
Current market capitalization of Bitcoins is 12 B USD. Current monetary base of U.S. is 4’000 B USD.
If Bitcoins would substitute U.S. monetary base, then their value should increase 4’000 / 12 times. However, let’s assume 10% of US monetary base will be substituted with Bitcoins. Money velocity of Bitcoins is much higher (let’s say 10 times higher than the velocity of fiat money); this would reduce the demand for the Bitcoin base money. This would result in following valuation:
U.S. Base Money (in B USD) 4'000Substitution ratio with Bitcoins 10%Increase in money velocity (in times) 10Total Bitcoin Network Valuation (in B USD) 40Final number of Bitcoins 21'000'000Value per 1 BTC (in USD) 1'905
However, Bitcoin is not national currency; it’s a supra-national currency. If we repeat the same exercise for the world monetary base and if we use substitution ratio of 5% then we get following valuation:
World Base Money (in B USD) 26'903Substitution ratio with Bitcoins 5%Increase in money velocity (in times) 10Total Bitcoin Network Valuation (in B USD) 135Final number of Bitcoins 21'000'000Value per 1 BTC (in USD) 6'405
Levers for valuation:
The higher the substitution ratio of base money, the higher the valuation.
The higher the Bitcoin velocity, the less demand for Bitcoin base money, resulting in lower valuation
The more QE, the higher price per Bitcoin
Bitcoin is not only payment mechanism; it allows building a stack of additional services and products on top of Bitcoin protocol.
It’s the same as Internet — what started initially as simple web browsing with Netscape Browser, developed into Google search and Web 2.0 — Facebook, LinkedIn and Twitter. All these products are based on Internet stack. However, it took 10+ years, till these Web 2.0 products emerged.
Bitcoin protocol allows moving asset ownerships into Bitcoin network — for example share registries and safe keeping accounts can be implemented as part of Bitcoin network. Ownerships of any assets (real estate, shares and cars) can be stored into Bitcoin network. Most public registries will become obsolete as all this information can be mapped into Bitcoin network.
We are still in very early phase of Bitcoin adoption; we are in “pre-Mosaic Browser” phase. We can expect many new applications on top of Bitcoin network — in the same way as it happened with Internet network. However, we are not able to quantify the value of these additional services. We just say — there will be many additional services.
We looked on three valuation approaches. All of them are complementary.
Ergo Bitcoin valuation is:
Bitcoin as Payment Processor 3'929Bitcoin as Base Money 6'405Bitcoin as Additional Services NAValue per 1 BTC (in USD) > 10'334
We foresee continuing network growth (based on Metcalfe’s law) and we foresee significant potential for Bitcoin price appreciation.
We recommend allocating part of alternate assets in investment portfolios into Bitcoins.
(This article was first published in Swiss CFA Society Magazine 2014 January Edition)
My friends, myself and my brother published book Blockchain Technology: Einführung für Business- und IT Manager Blockchain Technology - Einführung für Business- und IT Manager OK, it’s in German. However, it’s...
Blockchain Technology – Einführung für Business- und IT Manager
OK, it’s in German. However, it’s very praxis oriented and follows always the thought about what is business value and what business models we will have.
Video of the first book presentation is available here. I’m starting to talk at 18:28, my brother follows immediately to me.
If you have more time to watch, then we had here as well very nice presentation about Hyperledger and discussion about Ethereum Classics versus Ethereum.
On 29th of March I was giving a lecture about Blockchain Use Cases in Finance at University of Applied Sciences in Basel. [caption id="attachment_381" align="aligncenter" width="556"] Basel[/caption] Blockchain started with...
On 29th of March I was giving a lecture about Blockchain Use Cases in Finance at University of Applied Sciences in Basel.
Basel
Blockchain started with the Bitcoin and we can consider Bitcoin as a new base-money. But Bitcoin is just one of many use-cases in the blockchain economy.
In this lecture we analyze what are blockchain potential use cases in finance. Here are the slides:
SmartCredit.io
