On March 11th, 2021, around 10am in New York City, Christie’s announced that the auction for Everydays : the first 5000 Days by Mike Winkelmann, a.k.a Beeple, had just ended. Bids had escalated to unexpected levels over the preceding minutes, to the point of fearing a failure of the famous auction house's website.

But when the hammer finally fell, the digital collage was knocked down at $69 million, including $9m fees for Christie’s. It was then the third most expensive sale for a work of a living artist behind Jeff Koons and David Hockney.

Beyond its extraordinary price, Everydays : the first 5000 Days had the particularity of being a Non-Fungible Token (NFT)."Non-Fungible" means that this type of token cannot be substituted to another like a bank note could be substituted to another bank note of similar face value. In that sense, each NFT is unique and the blockchain technology guarantees its uniqueness and its ownership. The concept has been hugely successful since the second half of 2020. And with that $69m-sale, Beeple established a new record for an NFT, wiping out his own mark of $6.6 million for his Crossroads, which traded on the secondary market just weeks earlier.

Everydays: the First 5000 Days by Mike Winkelmann (a.k.a. Beeple). Source : Christie’s

At the time of these sensational sales, Beeple was still a relatively new name in the Crypto-art world as he had only produced NFTs for about 6 months. Long before this technological shift, he was already famous for his digital works, having partnered with the biggest brands and personalities, notably in the music industry. His fame could be measured by the millions of followers he already had on social networks. One of his major artistic projects had consisted in producing, each day, a new digital creation that he posted online. The series, called Everydays, spanned over 14 years.

For his first dip into Crypto-art, he sold 3 NFTs for $130,000 in total, including Crossroads for $66,666. This trial run quickly led to a first brilliant success since, in December 2020, several NFTs from his Everydays collection were sold for a total amount of $3.5m over a single weekend. In just 3 months, Beeple had become one of the most prominent NFT-artists. The $69m-NFT was created by collating the first 5000 Everydays, i.e. almost the entire collection, on a single token.

A new asset class

When they decided to write a $69m-check in March 2021, Vignesh Sundaresan and Anand Venkateswaran, the founders of the NFT fund Metapurse, could rely on their past experience in the sector, in particular with Beeple. These collectors had already accounted for $2.2m in the December auctions. Far from irrational, their strategy had a strong financial dimension based on a much more sophisticated plan than just holding the NFTs to speculate on a price increase.

In January 2021, they created 10 million new tokens called B20 representing fractions of the NFTs they had bought for $2.2m in December 2020. This process is commonly referred to as "tokenization" and can be applied to any type of asset, including physical assets in the real world. And it is extremely profitable: 2.6 million of the B20 tokens were initially issued for a total of $1m, or $0.38 per token. The price soared to $28 in March before falling back to $2 in May and $1 in September 2021. Those who bought B20’s at $28 might feel that a lot of value has been destroyed, yet the process converted $2.2m – the initial value of the NFTs purchased from Beeple in December 2020 - into $10m, the implied value of the 10 million B20 tokens in September 2021.

This example of millions of dollars created ex nihilo through tokenization is not an isolated case and the financial principles underpinning this probably deserve an in-depth analysis.

A Liquidity Premium

One the primary effects of tokenization is an increase in liquidity. Liquidity is defined as the ability to convert an asset into cash or, in other words, the ability to sell it quickly without affecting its price. By dividing one very expensive NFT into 10 million tokens, liquidity increases mechanically since, the lower the unit value, the greater the number of individuals whose disposable income or financing capacity allows the purchase. One of the most basic financial principles states that, all other things being equal, the greater the liquidity, the higher the price and the lower the return. The effect on price of a decrease in unit value is observable in many markets, including markets that are much more mature than NFT markets. However, a reference academic paper on the matter is critically missing. This may be due to the difficulty to completely isolate the liquidity effect from other consequences of splitting an asset into lower-value pieces. Here are some examples:

• Online gold exchanges can provide price information for different gold bar sizes. A glance at different platforms would confirm that the price per gram is consistently lower for a 20g ingot than for a 50g ingot, which is lower than for a 100g ingot,… this seems to hold true for all sizes. However direct conclusions can't be drawn because the cost of production is relatively higher for smaller sizes. Significant economies of scale are possible by manufacturing larger gold bars, which can be integrated in the initial selling price of producers.
• Sorare an NFT platform that PITTI have followed since its inception, allows the trading of virtual footballer « cards » for collection and/or for gaming purposes. These cards are issued in limited number each year with a maximum of one Unique card, 10 Super-Rare cards, 100 Rare cards and 1000 Limited cards. It is clear on this market that prices do not directly correlate to scarcity in the vast majority of cases: although the Rares supply is in theory tenfold that of Super-Rares, Rares typically trade for between 2 and 6 times less. And this tends to be verified between Rares and more-recently-introduced Limited editions (4 to 8 times cheaper). Yet, as for gold, it is difficult to isolate others constituents of value.
  103 "Limited" cards with a reference price of $855, 86 Rare cards with a reference price of $3,615, 8 Super Rares for $13,123 and 2 Uniques for $21,286. Source : soraredata.com

  Utility can be granted to NFTs and this is what makes this technology so promising. The cornerstone of NFT utility is that they can act as a proof of identity of their owners - or at least proof of rightful ownership - so a number of rights can be managed through them. For example, rights to access specific content, governance rights or, in Sorare’s case, rights to enter fantasy football tournaments. Gaming utility is an important part of Sorare's NFTs value, arguably more important than collection utility, yet fun is not necessarily the main reason for playing: on Sorare, depending on one’s performance in tournaments, significant monetary yield can be generated in game, so there is a financial dimension too (Play-to-Earn model). Gaming utility varies across categories of cards owing to Sorare’s gameplay design and, even within categories, gaming utility can vary over time depending on the number of cards in the market and the number of users on the platform. Sorare’s gameplay design leads to quickly decreasing marginal utility so, for a single user, total utility of 1000 Limited cards is negligible compared to utility of 1 unique card. However, total utility of 1000 Limited cards spread over 1000 users is significantly greater than that of 1 Unique card. And that alone is sufficient to explain a relatively higher price of limited cards according to the Neoclassical school of economics. Interestingly, the argument put forward for gold prices relied on a theory of objective value, which is relevant for Classical economics, whereas the Neoclassical theory relies on subjective value.

• The increase in liquidity resulting from a reduction in unit value can also motivate share splits for listed companies. A share split consists in dividing one existing share into several new shares. When this process leads to an increase in total value, it contributes to reinforce a company’s balance sheet - at least on paper. Shares splits have been the subject of several academic studies notably by David L. Ikenberry in 1996 and 2003. His work concluded that shares that had undergone a split overperformed their markets by approximately 8%, which can support the assumption that a decrease in unit value can lead to a relative increase in price. But as for Sorare’s NFTs, characteristics attached to shares must not be ignored. In particular the shareholders’ voting rights, and their implication when it comes to taking control of a company.

In the case of share splits, diluted control rights prevent direct conclusions regarding the effect of a decrease in unit value, but Ikenberry’s work provides an order of magnitude. And the 8% observed are nowhere near what Sundaresan and Venkateswaran have achieved when they transformed $2.2m into $10m… for assets with no other utility than being held in a digital vault.

If liquidity alone is not enough to explain the total value created through tokenization, what variables could be missing in the equation? Trying to answer this question using commonly-accepted financial concepts requires a great deal of caution because NFT markets are far from mature. The transparent nature of these markets due to the blockchain technology is simply not enough to make them perfectly efficient. But as volumes of transactions increase, it can be expected that market prices will eventually reflect an equilibrium between risk and return. Yet, this supposes that one is able to identify and measure the risks.

If the “sum of the parts” is higher than the price of the underlying asset, it is implied that the expected return on the token must be lower than the return on the underlying asset. So the risk must be lower, and it is undoubtedly true for liquidity risk. However, there is no clear evidence at this stage that other types of risks are materially reduced. If anything, they simply seem to be ignored.

Largely ignored risks?

Cryptocurrency enthusiasts praise the decentralizing merits of the blockchain technology, which allows disintermediation and, therefore, should ultimately reduce costs and risks. However, tokenization puts intermediaries back at the core of the system. And with them, counterparty risk.

As a starting point, it is important to stress that an intermediary is necessary so long as the underlying asset cannot be entirely stored on-chain, which is mandatory to implement smart-contracts. For that reason, all tokenized physical assets imply a middle-man, but most digital assets, tokenized or not, also involve an intermediary: given capacity constraints and cost of storage on the most commonly-used chains such as Ethereum, metadata is typically stored off-chain although it can constitute the largest part of the value of a digital asset. For digital artwork, the high resolution image is rarely stored on-chain ; the NFT only contains the address of the server where the image is stored. If the server disappears, the image disappears. When the value of a token relies as much on off-chain information as on its rarity, it is necessary to understand if there is a risk associated with the counterparties who control that information.

The next step to grasp the inherent risks of tokenization, whether applied to physical assets, to intangible assets such as a brand or copyright or to NFTs, is to analyze the nature and the terms of collateralization. And chiefly : can the underlying asset be sold?

• If not, ask yourself what you really own. Is it just a right? In that case, why attaching an asset as collateral? If the value of your token only relies on the value of an underlying asset that is literally unsellable, then you own a call option. This call option can be exercized in the event of technological innovation or regulatory change that enables liquidity of the underlying asset. It is nonetheless worthwhile noting that the blockchain technology allows any individual to prove that a famous personality has owned a token before them, which can constitute value to collectors independently of any other characteristics.
• If the underlying asset can be sold, how are the proceeds of the sale upstreamed to the token owners? Is it automated via smart contracts or does it require an intermediary to intervene? Does the intermediary have discretion over the decision to distribute the proceeds of a sale and can the intermediary decide to reinvest them? If the intermediary has a discretionary mandate, should be it regarded as an asset manager and be subject to similar regulations?

As far as the assessment of counterparty risk is concerned, the slow start of regulatory bodies poses a problem for both users and issuers of tokens. So long as tokens do not represent systemic risk, they are unlikely to be subject to any form of prudential regulation ; stablecoins may be an interesting exception. However, a form of regulation aimed at protecting consumers should eventually be introduced. Regulators create norms for products sold on their domestics markets in order to establish a climate of confidence between customers and their suppliers, but also to create a favourable business environment where suppliers can invest and hire employees without fearing competition from new-comers dumping flawed products that could damage the reputation of the entire industry. Certification by a third-party authority, governmental or not, would solve this issue. But in the meantime, the asymmetry of information between token issuers and buyers leaves the door open to scandals at the great expense of the consumers.

It must also be expected that compliance with anti-money laundering obligations – to which issuers are already subject but which are largely ignored – will end up being enforced. The regulators’ delay to address this industry represents a medium-term risk for issuers: when adjustments are eventually requested, issuers may have to revisit their operational models, or even their economic models. What would be the impact of additional costs or fines? Could this lead some players to go under? And what if you own their tokens? Counterparty risk and regulatory risk are closely linked in the token industry.

Valuation is a challenge

Adjacent to liquidity risk, the risk of miss-assessing fair market value can be significant if transactions are not frequent enough and/or if it is not clear which currency was used to set the price of each trade, in particular when there is volatility in currency markets.

The democratization of NFTs is a relatively recent phenomenon. These markets have long remained the realm of crypto-enthusiast communities so NFTs have been denominated in cryptocurrencies by default. When cryptocurrencies soared in the second half of 2020, usual buyers of NFTs saw their purchasing power increase accordingly, and using cryptocurrencies as a reference for price was not a problem. An anecdotal evidence of this is that Christie's accepted cryptocurrency payments for the first time for Everydays: the first 5000 days. And this was also reflected in the demographics of the bidders: of the 33 individuals who bid, 19 were millennials (born between 1981 and 1996), and 2 were under 25 years old.

But as NFTs become mainstream, it will be fair to question whether the reference currency should instead be the currency in which the majority of buyers naturally reason. And a shift in reference currency could change the picture.

Sorare is a prime example of NFTs aimed at the masses, with very encouraging prospects of adoption of their products by a public outside the cryptocurrency communities. Like other companies in sports NFTs, Sorare's user base took off in early 2021 and nearly fifty thousand people owned at least 1 Sorare NFT by the end of October 2021. Update: over 140k unique individuals owned a Sorare NFT at the end of August 2022.

Owners of N Sorare cards.
Source : Soraredata.com

Blackpool AUM - Nov. 2021.
Source: Blackpool.finance

There is already at least one token “backed” by Sorare NFT collections. Blackpool is a European pioneer in tokens associated to Play-to-Earn NTFs. As explained on their website, “by staking BPT for xBPT, [a user] can participate in the shared ownership of blue-chip NFTs, capture the value attributed back to BlackPool”. For Blackpool, the value of “assets under management” (AUM) is expressed in ether (ETH). At the beginning of November 2021, the value of the 3 Sorare collections of Blackpool amounted to 2,758 ETH (12.6 million dollars) and included nearly 880 particularly illiquid cards. For these cards, reasoning in so-called FIAT currencies (dollars, euro, pound sterling, etc...) instead of ETH can make a material difference.

Taking the example of two "Unique" cards of Turkish player Orkun Kokçu, each corresponding to a different football season, and issued 6 months apart: for an individual who reasons exclusively in ETH, the sale of the second unique card, results in a mark-down by 1.4 ETH. But for someone thinking in US dollars, the second sale leads to an upward revaluation of $6,658. The situation becomes even more complex if someone reasoning in US dollars buys a token backed by an underlying asset expressed in ETH. In the case of the Kokçu card, the day before the sale of the second card, a unique card could be estimated at 7,463 ETH, or 23,331 dollars. The sale of the second card led to a downward revaluation of $4,414. The second card was traded for 9.5 ETH or $32,494 in early October 2021.

Source : sorare.com

As in the real world, the choice of an appropriate reference currency becomes an issue when the different currencies fluctuate rapidly in different directions. The strengthening of cryptocurrencies against FIAT currencies provides one obvious illustration of the more general challenge of assessing fair market value for illiquid assets.

Fair market value must be representative of a general sentiment on a market where participants act freely, in their own interest, and having the necessary time to execute a transaction. One or two transactions per year are not sufficient to establish a fair market value because a buyer-seller pair can form on the basis of matching objectives or motivations at a specific point in time, but there is no guarantee that other market participants can form a similar pair of objectives or motivations justifying such price for the asset. Infrequent transactions become all the more problematic if, over a short period, the number of market participants increases enormously or if growth slows down: given most assets evidence declining marginal utility, new market participants means relatively higher prices. The regulatory framework could also change between transactions or, more generally, the balance between supply and demand could be profoundly affected by external factors. Add a dimension of rarity and/or the adrenaline of auctions, and it becomes impossible to rely on previous transactions prices to predict what the next one could be.

Beeple's Crossroads provides another illustration: sold for $66,666 in October 2020, it was sold again 6 months later for 100 times that price. A unique work of art must be an extreme case of rarity, and everyone responds differently to its aesthetic. Another dimension of Crossroads’ uniqueness is that the 10 second animation was meant to change depending on the identity of the winner of the American election of November 2020. The NFT traded in February 2021 was therefore also a unique depiction of Joe Biden’s victory over Donald Trump.

Sorare's NFTs provide less extreme examples of rarity, which allows to measure how transaction frequency affects price predictability. The first NFT ever “minted” by Sorare was a card of Hans Vanaken, playing for Club Brugge in Belgium and for the Belgian National Team. He is one of the players with the most NFTs in circulation on Sorare and his cards have strong gaming utility given his usual stats lines. These virtual cards are therefore highly sought after.

Crossroads by Mike Winkelmann (a.k.a. Beeple)
Source : niftygateway.com

The chart representing all transactions of Hans Vanaken's Rare cards between October 1st 2020 and October 1st 2021 shows homogeneity of prices: although the trend is upwards, very few transactions deviate materially from previous trading price. Super Rare NFTs perfectly illustrate how uncertainty increases when the frequency of transactions decreases. Even homogeneity observable at the beginning of October 2020 is misleading: in the cluster, prices range from $578 to $1,236. Then, each transaction is made at a price at least 25% higher than the previous one (respectively 127%, 26% and 347%). As for the Unique category - there are in fact 3 "Uniques" of Hans Vanaken -, the only trade over the past year was at $5,546 on October 3, 2020, more than six times higher than the previous one. Therefore, using $5,546 as the best proxy for current fair market value does not seem appropriate. Just as inappropriate as to assume that the next trade on a Super Rare card will settle around $14k, the last price paid for an NFT of this kind at the time of writing this article.

Hans Vanaken Rare - Price
Source : Soraredata.com

Vanaken Super Rare - Price
Source : Soraredata.com

Vanaken Unique - Price
Source : Soraredata.com

Against the backdrop of liquidity enhancement that can justify a relatively higher price for tokens compared to their underlying assets, the lack of liquidity of the latter remains a major problem for the valuation of the former.

In Finance, valuation biases associated with infrequent trading are widely-documented. For this reason, finance professionals avoid to benchmark returns of very illiquid asset classes such as Private Equity or institutional Real Estate against that of liquid asset classes like public equities. In liquid markets, risk-adjusted returns are calculated taking into account variance or standard deviation of transaction prices over a given period. For illiquid assets, if there is no trade over a given period and reference price remains unchanged, variance and the standard deviation equal zero. Yet it does not mean that the risk is null, it only means that these indicators are not statistically significant for this use-case.

So Managers of Real Estate or Private Equity funds use other tools to issue credible valuations on a quarterly basis, even if there is no trade over the period. The most common approach is to use so-called “comparable” transactions as proxies. Valuations can also be calculated by discounting expected cashflows over the following years.

The cashflow approach relies on financial concept assuming perfect markets with rational participants. Tokens, and NFTs in particular, do not really meet the requirements. Given the lack of maturity of these markets, information is either simply lacking or asymmetrical between participants making a limited numbers of sellers or buyers very influential. Some participants are de facto market markers. In any case, these markets cannot be considered transparent. In addition, investment decisions can have an irrational dimension if they are partly influenced by factors such as adrenaline released during auctions. Even if it were possible to predict cashflows - which is not completely unthinkable for tokens with a recurring yield, notably through staking - discounting would represent a hurdle that is impossible to overcome: choosing the appropriate discount rate requires to quantify the required return for assets with similar risk profiles. Drawing such parallels less than a year after the start of this digital goldrush is dangerous at best, and misleading at worst.

Using “comparables” seems a more tangible approach, at least for NFTs having utility. For digital artwork, trying to compare transactions with each other seems pointless as the sole dimension of utility is collectability which is directly linked to aesthetics and above all the uniqueness of the tokens. Apart from the author (the Artist) and possibly the platform on which the work was sold, very few objective criteria can be used to establish a scalable valuation methodology. In that case, valuation seems destined to remain the prerogative of few experts in specific niches. The physical art market is based on the same principles and perfectly illustrates this challenge. It is not coincidental that NFT collections such as Cryptopunks or Bored Apes include features for each NFT (skin colour, haircut, accessories…) that play a major role in their valuation. These collections are interesting examples at the intersection of digital art and utility tokens : they are rare yet issued in a sufficiently high number so that it is possible to feel part of a club, just like you are part of a club when you own a diamond. That alone is a constituent of utility, albeit very subjective, justifying a certain price tag.

The fewer the subjective dimensions, the easier it is to categorize NFTs. Metadata can play a key role but the blockchain technology can facilitate the aggregation of information concerning transactions, at least for public chains.

Again, Sorare can shed interesting light on the merits but also on the limitations of this approach: one of the dimensions of their NFTs value is their utility to enter in fantasy football tournaments. Platforms such as SorareData compare players based on stat lines and can automatically provide a list of NFTs with similar gaming utility. However, even within in the same age group and for the same player position, it is clear that multiple additional criteria, more or less subjective, must be taken into account. Football fans would immediately identify the shortcomings of the approach as a Japanese player from the Belgian league is considered "comparable" to two players from the Korean league, but also to a worldcup winner playing for Real Madrid or a Europeancup winner playing for Paris-Saint-Germain. Additional criteria can be taken into account such as number of games in a year (driving the number of opportunities to play-to-earn) or frequency of injuries but ultimately, the collectible dimension is where the “comparables” approach breaks. This explains differences in price : on the day of this screenshot, the Rare card of the Japanese player from Charleroi was worth 30% less than that of the Italian from PSG and 68% less than that of the German from Real Madrid.

However, “comparables” are not necessarily a dead end. Isolating utility value from collection value can already be an important step towards a good estimate of fair market value, not directly in relation to comparable transactions but using comparable blocks of value: if one can establish that, for a set of players with similar gaming utility, less liquid cards like the Super-Rares are sold for 6 times more than the liquid cards like the Rares, then one can probably infer prices of these players' Super Rares relative to the value of their respective Rares. Whether this approach fully accounts for a relative increase in collectible value as rarity increases is uncertain, but if the player set is large enough, the result will likely be a better proxy than using “comparable” transactions on illiquid NFTs.

Is it what motivated the following transaction between the Blackpool managers ? Manager 2 had bought the Unique card in July at a very high price compared to the Super Rares, and Manager 3 subsequently sold a Super Rare to the Manager 1 for twice the price twice of the last transaction on Super Rares. This readjusted the ratio between Super Rare cards and Unique cards to a more normal level but it also doubled the value of the card in Blackpool's AUM.

Trades on Paul Pogba 2020 - 3/10.
Source : Soraredata.com

Interestingly, Managers of illiquid assets in the real world would typically seek a sign-off from investors in context of such transaction. And that would be an amazing use-case of the “governance” tokens issued by Blackpool. Blackpool did not wish to respond to our requests as to the motivations and decision-making processes for this transaction.

Methodologies usually applied in the Finance industry for illiquid assets are not totally useless but they remain imperfect for NFTs. Additional help to pinpoint fair market value may come from the trading platforms, which can log information on trade offers that are not converted. By consolidating information on appetite of potential buyers and sellers, they can assess the bid-ask spread, which is the interval where the fair market price lies.

Information on listings (offers for sale) is more or less public on most NFT platforms. Listings allow to establish an upper limit to the fair market value pursuant to a simple principle: if 100% of the listings at a certain price are converted into trades, that price is likely lower or equal to the fair market value. Conversely, if none of the listings are converted, this means that this price is definitely higher than the fair market value. For this approach, conversion rates constitute critical information to determine the upper limit of the fair market value.

History listings of Crossroads by Mike Winkelmann (a.k.a. Beeple)
Source : niftygateway.com

Listings of Rare cards of Hans Vanaken (USD) between 07/07/21 and 20/07/21
Source : soraredata.com

According to the reverse principle, if one can aggregate unsolicited offers from interested buyers, they can determine a lower limit for the fair market value: if all unsolicited offers at a certain price are accepted, that price is likely higher than the fair market value. But if none are converted, then that price is lower than the fair market value.

Unsolicited offer
Sorare - Sept 21

Unsolicited offer
Sorare - Nov 21

Illustration of bid-ask spread

So listings and unsolicited offers, converted or not, can be used in a form of a squeeze theorem to estimate fair market value, and this may be the most credible approach to give a valuation of a given NFT at any time. The main hurdle is that unsolicited offers are very rarely public. Platforms getting their hands on this piece of information should play an important role in NFT ecosystems once these markets have reached a certain maturity. In the meantime, valuation risk will remain significant for NFTs with limited transaction volumes.

A feeling of deja vu

When an asset is tokenized, it is crucial to understand to what extent the relative increase in value of the "sum of the parts" compared to the asset itself does not reflect a partial or total dissolution of the risks associated with the asset. Save for lower liquidity risk, nothing could justify such dissolution.

Ironically, Decentralized Finance (Defi) seems to have borrowed some recipes to bankers of the late 1980s. The tokenization process very much reminds of securitization, which consists in grouping assets together in a special purpose vehicle that issues securities to finance the acquisition of the assets. The art of securitization lies in the tranching of the issued securities ; each tranche having specific characteristics in order to spread the risks and the value across different investor profiles.

Securitization in its modern form dates back to the end of the 17th century, when the British Empire restructured its debt by selling it up to commercial companies which, in turn, issued shares to investors. However, due to lack of investor support in the long run, this first documented example of securitization at large-scale was stopped at the beginning of the 18th century, and the concept remained in investment bankers’ drawers for nearly 250 years. Securitization reappeared in the US in the mid-1970s with the first Mortgage-Backed Securities (MBS), guaranteed by the governmental agency Ginnie Mae. MBS convinced both investors and finance professionals and the securitization industry really took off in 1983, when another government agency, Fannie Mae, issued the first Collateralized-Debt Obligations (CDOs). The model was quickly extended to car loans (1985) then to credit cards (1986) and soon to other verticals of the Finance industry, most notably with the securitization of insurance policies in the 1990s.

Securitization was primarily attractive to bankers because it allowed to redistribute risk – mainly credit risk – from banks to the market. For centuries, the banking business relied on pooling risks on the banks balance sheets, but this new tool gave them opportunities to off-load part of these risks. And this proved particularly useful to meet the increasing constraints of global prudential regulations including, amongst others, the Cooke ratio introduced in 1988. Investors and rating agencies considered these securities or bonds very safe due to the extreme diversification of the portfolios and complex credit enhancement mechanisms improving the risk profile through tranching. Securitization was long regarded as a panacea for banks and the markets for these products reached a climax in the mid-2000s before a spectacular collapse that triggered a global financial crisis.

Pretty much everyone pointed the finger at securitization which had diluted the notion of risk so much that it had become impossible– or maybe not even conceivable – to try to challenge the valuations for these extremely complex products. Critics have highlighted a vicious cycle whereby banks, after cleaning up their balance sheets and/or generating substantial profits through securitization, could reinject the proceeds into the system. Reinjecting the proceeds means underwriting new mortgages or loans with the comfort of knowing that it would always be possible to get rid of the risk later… through securitization. This allows to take more risks in terms of credit worthiness and the resulting commissions encourage to chase more volumes, which in the medium-term creates inflationary pressure on the underlying markets. It is widely accepted that the banks thus fuelled the bubble until it burst.

Drawing the parallel between securitization and tokenization is just a reminder that there have been precedents to the significant dichotomy that may exist between the value of tokens and that of the underlying assets. But this parallel also raises questions about the role of token issuers in the rise of NFTs prices if they constantly reinject into the system the money they create ex-nihilo.

Price of B20
Source : Coinmarketcap.com

It is probably not insignificant that, when they placed the final bid on Everydays: the first 5000 days, the auction winners sat on 5 million B20 tokens, valued $28 each on that day, i.e worth $140 million in total.

This anecdotal example shows that it seems fair to assume that billions of dollars could end-up disappearing in a large-scale version of the collapse of the B20 price, which was divided by thirty in 6 months. Until a major krach wipes out unsustainable tokenization strucutres, it will be difficult to consider token markets as mature.