Let’s talk securitization….
Anyone who was around during the roaring 2000s probably remembers the hype in Credit Derivatives (namely in MBS and CDO). These were the hottest commodity in town, and everybody and their mother wanted a piece of the action. These products were, essentially, a type of securitization.
Securitization, without going too deep into the nitty-gritty of it, is a form of transforming non-tradable asset/obligation ( loan, company value, dividends) into an asset that can be bought/sold in the open market.
So how does this magic work? (And most importantly, why do banks need it?)
When a bank issues a loan it essentially assumes the role of the creditor. It gives the money in return for a cash flow by the borrower that’s made up of the principal and the interest. The bank can’t issue loans indefinitely. Regulators (and Risk Management) define a certain ratio of loans that banks can issue relative to their liquid capital/deposits (otherwise the bank will be a great risk in case of a massive default of the borrowers). This is where securitization comes into play. The bank, theoretically speaking, can pool part of its loan portfolio (it can be mortgages, auto loans, student loans, etc…) and sell them to an investment bank, that then issues them as a product that’s sold to investors (in a form of a bond, in most cases).
So to recap, the stream of payments from the borrowers is transferred via the issuing bank to the investment bank, to the end-users (investors), who in return bought the security (i.e., paid the value of the discounted cash flow of that pool of loans). Sounds amazing, right? Banks can keep on issuing loans, sell them, assume no risk, and basically has an incentive to give as many loans as possible (assuming that there is a demand of the CDOs).
So why did I tell you about this incredible form of structured finance? Well, because in today’s market the most obvious form of securitization is likely to be in the crypto-verse, and while I believe that 99% of the crypto instruments/underlying assets that we see will not last for long, the idea of securitization can (and probably) will attract institutional investors into NFTs and DeFi. Now, please don’t treat the following securitization mechanism that I propose as a recipe for structured products (or how to create crypto WMD). This merely serves as a test case for creating a structured product from literally bytes and pixels.
Ready, so let’s begin…
Obviously, we all want to have skin in the NFT game. We’ve all seen JPEGs bought (and sold) for radicicolous prices, but the matter of fact is that most of us don’t have a slight clue on how this market works, how crypto wallets work, and how money is transferred between the different wallets. Let’s assume that the Teachers’ Fund of Arkansas wants to diversify its investment portfolio and chase higher yields outside of traditional markets (like, shorting volatility in SPX or Natural Gas doesn’t cut it anymore…), so they ask their asset allocator to find a fund that specializes in crypto and DeFi so they could invest and enjoy triple-figures returns… Their allocator finds a well-respected fund — Allianz Structured DeFi alpha, which happens to invest in NFT pools via NFTbs (NFT Backed Securities) that they buy from the Morgan Sachs structuring desk.
So how does this NFTbs work?
Creating NFTbs begins with Morgan Sachs structuring quant team mapping the entire NFT universe (basically scrapping OpenSea), and pooling all the different unique NFTs into one giant pool of possible assets. Now that they have all possible assets to choose from they start slicing and dicing them. The easiest way to do that is to create sub-indices that share the same feature (say, based on their collection), so they will have BoredApe_Index, PeddyPenguin_Index, EtherRock_Index, etc…
Each index is constructed of the individual (unique) NFTs, so in BoredApe_Index, for example, you could find BoredApe #8720, BoredApe #1859, BoredApe #5625, etc…. Obviously, each one of them is a unique asset, but because we are not really interested in the aesthetic of these NFTs (we are only here for the money), we can generally treat them the same.
So now that we have different sub-indices we can pool them all together into one “master” index (think S&P500 of NFTs), but how do we decide the weights we will assign each sub-index? This is where the rating agency joins the game…
As the issuer of the NFTbs, Morgan Sachs doesn’t really know how to rate the different NFT subgroups (and even if it does have a clue, they are in a conflict of interest as they are both the issuer and the rating agent of their security), so they ask Moody’s NFT division to provide them 3rd party rating of the different NFT groups. Moody’s NFT division assesses the quality of the different sub-groups and determines that EtherRock is a solid investment, and therefore rate the sub-group as Aaa investment, meaning that it assumes EtherRock is unlikely to be worthless (in bond market terms, it means that EtherRock is unlikely to default). However, after reviewing BoredApe sub-group Moody’s team rates it as B3 grade, which is considered a speculative and high-risk investment. The rest of the sub-groups are rated Baa2–3, which puts them a notch above speculative grade.
After Moody’s provides the rating MS decides to create the NFTbs using 50% EtherRock, 20% PeddyPengiun, and 30% BoredApe. Obviously, the fact that 50% of the instrument is made out of Aaa makes it a “solid” investment, which allows endowments and pension funds to invest in.
So let’s recap what we’ve done so far: 1. we pooled many different assets and created various indices, then we graded them, and turned them into an index (the same way any index is created). This is the part where you might say: “But what makes NFTbs different than any ETF that invests in the S&P500??”
This is where we take a step back and understand the mechanism of CDO…
Explaining CDO in (very) short
Very much like what I described above, investment banks in the 2000s created Collateralized Debt Obligations (or CDO). As these investment vehicles were backed by loans, they generated a stream of cash-flows, which was paid to the holders of the CDO (on a periodic basis, like any other bond), in exchange for the premium the holder paid for the CDO. As implied by the name, the debt obligation is collateralized, meaning that the collateral used for the underlying loans will act as collateral in case of a default (and will ensure some recovery rate of the debt). CDOs are generally made of various tranches, which represent the different risk profiles of the assets within the pool. Usually, CDO is made out of three tranches:
- Senior Tranche — contains Aaa issuers,
2. Mezzanine Tranche—contains lower investment-grade issuers (from A-B3)
3. Junior Tranche — contains speculative-grade (high-yield/junk) issuers.
We can clearly see that when it comes to NFTbs we have one major issue:
The NFTs don’t generate a stream of cash flow (i.e., they don’t generate dividends, nor periodic coupons), just an appreciation in value, and their appreciation of value is a function of their trading prices in the open market. Now, because they are Non-Fungible, if we physically hold them, their value cannot appreciate/depreciate. Hmm… a problem!
Because the structure cannot be collateralized with the underlying the issuer needs synthetically create the underlying NFTs (or hold an asset that its value tracks the price dynamic of the NFTs the structure holds). Currently, there are two possible ways that MS can use to back their NFTbs:
- To use Fractional NFT — Basically allows partial ownership of a specific NFT, increasing its liquidity, and deals with the non-fungibility characteristic of NFT (to learn more, be sure to read this medium blog)
- To use Martingale Shares — Also allows partial ownership, but in a different way, using a Martingale process (which is very cool in itself). This contract, however, is less suitable for this specific vehicle, as the settlement process involves with cheapest-to-deliver mechanism, which can temper the original pool of NFTs
Let’s assume that MS chooses to use Fractional NFT. The question now is how this product works…
As we noted earlier NFTs don’t generate anything but appreciation/depreciation in value, and therefore we cannot use DCF (discounted cash flow) to evaluate bond-equivalent security based on NFT. Moreover, because MS would create the pool of NFTs synthetically, it makes more sense for them to use the Total-Return Swap mechanism. This is the point where we stop for a second and explain what TRS (Total-Return Swap) actually is…
Some of you probably heard about TRS back in January when Archegos collapsed and took Wall St. biggest banks down to a spiral of heavy losses.
The reason TRS had a significant role in Archegos loss, is because this derivative offers quite a leverage (compared to owning the physical shares), and actually doesn’t require the investor to actually own the underlying asset on her/his balance sheet (so if the underlying loses money it doesn’t show up on the reports). The basic mechanic of TRS is that between two parties, where one receives the total return of the reference asset (total return = asset appreciation/depreciation+ dividend/coupons), while the other party receives the reference index rate (mostly LIBOR/SOFR + spread)
Based on the mechanism of TRS, it’s easy to see that this structure is the most suitable to facilitate NFTbs. Using TRS, MS will pay the holders of the swap the average appreciation of the underlying NFTs of their corresponded tranche, while the holder will pay the Etherium funding cost + spread. The spread added to the funding cost represents the additional premium charged for the specific tranche.
Obviously the hardest part about creating (and trading) the NFTbs is the pricing… First, we don’t really have enough data to be able to value the expected drift/volatility of the different underlying NFTs in the pool. We can always use the historical data that we have so far, but as this market is relatively “young”, we are likely to have a somewhat biased sample. If we will try to simulate price paths using Monte Carlo simulation, we will essentially assume a normal distribution of log-price, which, empirically, don’t hold water, so it would be super interesting to see how Morgan Sachs quants come up with a pricing formula….
A plausible solution for estimating the “fair value” of the different tranches can be based on the floor price of the different sub-indices (that comprise the different tranches). Let’s say that for each tranche if the corresponded floor price falls below a certain threshold (pre-defined at the creation of the NFTbs), the tranche will default and be liquidated. The proceeds from the liquidation will be used to pay the higher tranches. Based on that process, the equity tranche will be the first to be liquidated if the NFTs start to depreciate, while the senior tranche is going to be the last, protected by the buffer of the junior and mezzanine tranches.
Lastly (and this is where the real fun begins), after we created our structure, we can always create another set of derivatives based on that structure. We can, for example, create NFTbs based on a pool of other NFTbs (so NFT²), or create options on that NFTbs. The idea is that once we have an underlying (whatever underlying that is, we can always leverage that into creating derivatives on that underlying, even if is a derivative of another underlying).
Just to emphasize the scope of possibilities that we can generate with one NFTbs, just think of “The Big Short”, where Mark Baum (Steve Eisman) learns about CDO²
I really hope that this short take on securitization, and how we can securitize literally ANYTHING was interesting, and opened the door to the world of structured products. Obviously, there is much more to be written about it, and I will put down a more comprehensive piece about structured finance sometime in the near future.
Published By : Volquant