A Deep Dive Into Web3 Infrastructural Needs For A Decentralized, Censorship-Resistant, Secure, and Private Future

In the great crypto circus, liquidations and Chapter 11 filings have become so common that people consider them almost synonymous with cryptocurrencies. But is that really the case? All of the multi-billion dollar hedge funds, firms, market makers, and trading exchanges that went bankrupt had one thing in common — opacity in their balance sheets enabled by an opaque ‘centralized’ system rather than a system of transparent ‘decentralized’ ledgers. To create truly decentralized, accessible, self-custodial, and censorship-resistant systems that can withstand attacks and fraud, we need more than a system of conventional settlement layers. This research explores the intricacies of Web3 infrastructure or middleware to identify existing challenges and future opportunities. We shed light on the utility of aggregation layers; various types of nodes; and Zero Knowledge Proofs (ZKPs) to further the mission of decentralization across the crypto ecosystem. This research is carried out and authored by 0xlol, and edited by ThePsychGuy. They can be reached on Twitter at 0xlol and ThePsychGuy respectively.

tldr;

• A robust and resilient Web3 Infrastructure is necessary to sustain decentralization, censorship resistance, transparency, and easy accessibility for crypto.
• Light Nodes or Clients make decentralization accessible to masses.
• Zero Knowledge Proofs (ZKPs) add massive value to almost every component of the Web3 infrastructure establishing it as a crucial piece of the middleware.
• ZKPs help establish a trust-minimized environment resulting into the enhancement of on-chain privacy, UX, security, and decentralization.
• Aggregation layers are one of the most important pieces of Web3 infrastructure puzzle when it comes to user and developer experience.

A Brief Introduction to Web3 Infrastructure

Web3’s infrastructure has continually evolved for the better and has the potential to generate tremendous value. It has obvious supply-and-demand drivers required to achieve sustainability and profitability. The ideal system needs to be censorship-resistant, decentralized, efficient, secure, and provide a great user experience. By Web3 infrastructure, we refer to all the components that can facilitate the workings of a decentralized ledger system. It’s a full stack required for the proper functioning of the blockchains.

In order to understand this concept better, let’s explore it in the context of Ethereum. Ethereum is a decentralized computer or a distributed network of computers, with each individual computer referred to as a node. These nodes utilize software and work together in order to verify transactions and keep track of the decentralized ledger. Even though these nodes can be said to form the backbone of the blockchain, they cannot be considered as the full stack required for its functioning. Other supporting systems that aid various functions (user interaction, data storage, etc.) of it together constitute a Web3 infrastructure.

There are three different types of nodes: full, light, and archive. A full node stores all the blockchain data up to the latest 128 blocks, validates blocks and verifies their states. An archive node has the same capabilities as that a full node, plust the ability to store historical block data dating beyond the latest 128 blocks. It makes them suitable for querying historical blockchain data. Finally, light nodes don’t record any block and instead, store the block headers. They also can’t validate blocks, but that shouldn’t make you doubt their utility! As we will in due time, they can provide ‘easy access to decentralization’ and don’t require powerful or expensive hardware.

The graphic above describes the typical anatomy of Web3 infrastructure. While the web of intricacies remains hidden from the end-user, much activity goes on to keep global decentralized ledgers in action. Even if you’re a crypto enthusiast, it’s not obvious that you understand what JSON stands for or what IPFS does. That’s because not everyone can directly interact with smart contracts connected to the EVM. It necessitates a user interface (UI) setup or a front end. The front end refers to the part of a decentralized application or system that users directly interact with. When you connect your metamask wallet to a DEX, the website or the ‘user interface’ you see is an example of the front end. When you wish to interact with the EVM, you actually interact with the front end which then relays the information via an Application Programming Interface (API) to nodes. These node providers then broadcast your transactions to the EVM. Thus, your transactions are relayed from the front end to the EVM through APIs provided by node providers, such as Infura.

To interact with a blockchain and change its state, you need to ‘sign’ a transaction with your ‘private key’. While querying data from the blockchain doesn’t require you to sign any transactions, the decentralized ledger necessitates that each change made to it is authorized by the user requesting it in the form of a transaction. Such transactions require you — the ‘signer’ — to approve a state change through your private key. It’s another crucial feature of the crypto wallets, bestowing the roles of provider as well as signer onto it since your private keys are stored on the web by wallets such as MetaMask’s applications.

Signing or authorizing every transaction on the distributed ledger requires you to pay a gas fee. The validators are rewarded with the base network fee (paid by users) to ensure that it runs with integrity. But with an increase in transaction frequency, the network gets congested. And to get your transaction processed on priority, a premium in the form of an additional gas fee has to be paid to validators. In recent years, due to significant network congestion, transaction or gas fee on Ethereum skyrocketed making the network unviable for retail users.

To mitigate the ill impacts of increasing transaction costs and time, crypto scientists have come up with Layer-2 (L2) solutions such as Polygon zkEVM. Such scaling solutions exist as an overlaying network atop the main settlement layer (in this case, Ethereum) and facilitate a batch of transactions to increase transaction throughput while lowering gas fees. We’ll shortly explore the role of Zero-Knowledge Proofs (ZKPs) which would highlight the significance of having a zkEVM infrastructure better.

Blockchains are data-generation machines, which requisites for decentralized data-storage solutions. They must stay in sync with the blockchain to maintain reliability. It must be noted that such solutions are necessary because storing data directly on the settlement layer can be very very expensive. Such solutions work by embedding the hash of the data stored in them onto the blockchain for permanent records in lieu of the actual data. Decentralized storage systems prevent important data from being controlled by centralized servers and offer incentives to users who participate in such peer-to-peer storage. Your favorite NFTs are probably stored on the blockchain in the same manner :)

Centralization, Privacy, Reliability, and Experience

The existing infrastructure for Web3 is still evolving and is not as mature as the infrastructure for Web2. Let’s investigate whether the ethos of decentralized systems — ownership, censorship resistance, and decentralization — can be sustained with the existing Web3 infrastructure. Is the current middleware competent enough to support this new paradigm?

Decentralized Enough?

Do you really own that cool monkey you bought as an NFT for 150 $ETH? Can you access and buy it from any part of the world? Suppose you sign a transaction for your NFT on the Metamask UI and it gets broadcasted to miners (proof-of-work) or validators (proof-of-stake) via Infura API. The broadcasted transaction will be queued for execution. After being put in a block by the miner or validator, the transaction undergoes validity checks and fraud screening before being executed. Upon execution, it results in a ‘state change’ on the blockchain. All irreversible transactions must change the state of the blockchain. You finally got your monkey!

Sadly, there’s a caveat here. It has been found that node providers don’t really verify the changes in the state of a blockchain once a call has been made through their interface. On top of that, they have access to all read requests, exposing transactional information before it even reaches the mempool. It exposes the user’s funds to unknown risks! Finally, node providers can censor your access to the transparent decentralized ledger and sell/leak your data to MEVors. In fact, Metamask (owned by the same company that owns Infura) has censored certain IPs based on certain geographical locations in the past.

How Reliable?

Speaking of the monkey, what did you actually buy when you paid 150 $ETH? Do you really own it or does it possess the ability to get lost in the dark lush forest? As previously discussed, storing data on the blockchain is very expensive. Usually, only a URL — generated from storing the data on platforms like IPFS or Arweave — is registered on the ledger. Opensea, one of the major NFT marketplaces, uses the aforementioned data-storage solutions. Solutions like IPFS work on a ‘content-based addressing’ in which the data is recalled directly by navigating the hash associated with it. You need to ‘pin’ the data to prevent it from getting lost. Data using content-based addressing is prone to be lost if the original file is only kept by a few specific nodes. If these nodes are corrupted, data is permanently lost. Your monkey is no longer yours to own. On top of this, the aforementioned URL generated doesn’t have any hash commitment to it. Even with permanent storage solutions like Arweave, you are at the mercy of moderators as they are responsible for filtering content before it gets registered on the blockchain.

Who Can Watch You?

Attaining privacy in Web3 is difficult since everything on the blockchains is exposed to the world. The data — or the URLs in the case of your monkey NFT — stored on decentralized storage solutions aren’t encrypted as well! Anyone can query the metadata associated with your NFT, breaching your privacy! For Web3 to succeed, it’s important that the infrastructure enables a robust layer of privacy. One of the most popular and secure traditional approaches is End-to-End (E2E) encryption, but we lack a similar arrangement in Web3.

E2E is a process of encryption where only the communicating parties have knowledge of the information being exchanged between them. Servers or intermediate components don’t have access to this information. Even if a third party manages to get access to it, they won’t be able to decrypt the communication. It is achieved by encrypting the information on the sender’s side with a key available to the sender and the receiver alone. The receiver can decrypt the information with their pair of keys. Pretty Good Privacy (PGP) and Secure Sockets Layer (SSL) are some of the popular E2E encryption methods. PGP requires a public and a private key and is usually employed to sign and encrypt emails; SSL is preferred for encrypting instant messages, given that both parties have SSL certificates. The transparency of blockchains makes it difficult to have complete E2E encryption.

User and Developer Experience Problem

User experience (UX) is going to play a big role in how successful Web3 or Crypto technology will be. A better UX means that more people will adopt the new technology. UX refers to a user’s experience (emotions, attitudes, etc.) after they have used or interacted with a particular product or service. There are multiple steps involved in interacting with a product, and the practical; experiential; affective; meaningful; and valuable aspects felt during those interactions contribute towards UX. The difficulty in understanding a product’s mechanics or estimating its utility in their life might contribute to a negative UX. It is not only with the product or service but also with the whole system involved in the delivery process.

At the same time, a developer’s experience is as important as that of the user. If the developers migrating from Web2 to Web3 don’t find it comfortable to adapt to the new environment, then it impacts productivity and innovation. Mass adoption of new technology is only possible when the users, as well as builders, feel comfortable and secure interacting with it.

For Users

How would you buy a monkey NFT if you’re new to crypto? Well, you can use a credit card on platforms like Opensea if you aren’t a resident of all the 77 countries mentioned here using moonpay. What if you are not one of the chosen (privileged) ones? Firstly, you will have to find an exchange that accepts fiat and convert it into crypto. Then, you will be buying ETH and creating a Metamask wallet; don’t forget to secure your seedphrase (you know, those 8/16/22 words which everybody asks you to memorize and never share, otherwise you can kiss your funds goodbye)! After that, you will find a way to send ETH from your exchange to your Metamask wallet. Now, you will bid on NFTs with an ever-fluctuating artificial floor (gas fee). Be cautious though, since once you sign and broadcast your transaction, you might get ‘sandwiched’ by front-running bots. When you somehow manage to execute a transaction, it will take around 120 blocks to achieve the finality, and you will finally be able to buy your monkey NFT. We hope you bought the right one and didn’t fall for a scam though, as many NFT pages get impersonated and the Metamask prompt to sign a transaction doesn’t come with Google’s “unverified security certificate” prompt. How easy and simple was that?

The design of Web3 makes it really difficult for anyone, especially beginners, to carry out operations smoothly. Honestly, we aren’t even done here. Accessing chain IDs of different chains, having knowledge of their remote procedure calls (RPCs), and being aware of different bridges; swaps; and chains isn’t an easy task. This ultimately results in a bad UX which is probably one of the worst things to happen to any new technology in terms of mass adoption.

For Developers

As developers have started migrating applications from Web2 to Web3, indexing; storing; and computing the colossal amount of data brought by them is going to be a huge task. While Web3 protocols are open source, and technically composable, actually achieving this composability in practice is much more difficult than it is in Web2.

Blockchains are state and computation machines that constantly produce data. It necessitates a robust infrastructure for indexation, node-synchronization, and backup durability. Correctly indexing data from blockchains is as important as difficult; distributed systems make it tough to retrieve data. Apart from the security and scalability of the underlying machine, such issues have long prevented blockchains from achieving instant finality (takes around ~120 blocks on Ethereum). The flexibility of storage, as well as efficient computation models, are required to circumvent the problem. The developer needs to be aware of each and every component to succeed, probably requiring a plug-and-play layer. When it comes to decentralized data storage, validity, and processing solutions — like IPFS, Arweave, Filecoin, Skynet, etc. — developers rely on centralized solutions from Amazon and Google. They find it more convenient, reliable, and easy to use. They provide mutability, while on the other hand, data on the aforementioned decentralized storage solutions are immutable, i.e., they can’t be deleted or manipulated.

The Hopeful Side: Emerging Solutions

We listed out a few key problems that are hindering Web3’s adoption as the next-gen technology. While the landscape is challenging, it would be wrong to assume that a dedicated community committed to decentralization would be deterred. New solutions and mechanisms are being developed to reduce Web3’s reliance on Web2 infrastructure; some of them require building pipelines from the ground up. Let’s have a look at these emerging and promising solutions.

Accessible Decentralization Through Light Nodes

A possible move against centralization is for individuals to set up their own nodes. However, in a world with economic inequality, not everyone can afford the 32 ETH required for setting up a node. Additionally, not everyone has the requisite knowledge to establish this infrastructure remotely. There has been a growing trend in major companies (especially small businesses) to move away from centralized control centers to cloud-based services. Developers can run their code at scale without worrying much about maintaining expensive servers.

Technologies like light clients or nodes can help achieve true decentralization, putting blockchains at the forefront of the serverless revolution. These light nodes interact with full nodes in a trust minimized manner. Since they don’t store or keep the state, they can be easily run on remote devices like a smartphone or a laptop. They can track block headers, verify inclusion proofs of state fragments sent from infrastructure providers or nodes, and verify state commitments. In this way, decentralization can be achieved with minimal storage, bandwidth, and computation costs.

Developers have also attempted to create trustless modifications to MetaMask, as can be seen in the case of Kevlar. After syncing to the latest headers of the blockchain, it will initiate a local RPC server which can be added to MetaMask or any other RPC wallet. It allows any call made by the RPC wallet to go through Merkle Inclusion proofs before being broadcasted. On the other hand, alternatives to existing node providers such as Infura have also come up; a good example is the Lavanet. As a P2P RPC network, it connects providers and dApps on the basis of service type and geography for faster processing. It focuses on censorship resistance and scalability as a whole, demeaning the need for centralized giants for connecting with Web3.

Trust Minimized Environment Through Zero Knowledge Proofs

Zero-Knowledge Proofs are a type of mathematical proof that allows someone to prove that they have knowledge of certain information without actually revealing that information. They help in establishing a ‘trust-minimal setup’ as the client need not trust the server/nodes every time the interaction occurs. The trust needs to be set up only initially where the server will send the client a commitment to the data (or its hash), which can be verified using a ZKP by the client. Subsequent inputs from the server/nodes can be taken without needing to trust the server. Such a trust-minimized setting significantly improves the security of the system. In this way, ZKPs eliminates the need to download the complete dataset just to verify a certain packet of information. This helps in the scalability and affordability of stateless clients as ZKPs save a lot of space and processing power. And finally, such zero-knowledge proofs can keep the user from interacting with a fraud or scam contract which can result in a loss of capital from the user’s wallet. Ethereum scaling Layer 2 zkEVM solutions like Polygon Hermez have been working in this direction to help improve the overall web3 landscape. Their open-source ZK Prover can be used to improve Web3 infrastructure apart from scaling Ethereum’s throughput.

Besides using ZKPs, read requests can probably be masked by using technologies like fuzzy message detection. It helps the fragments associated with the user’s state be obfuscated or muddled with a larger set of state fragments to make identification difficult, resulting in increased security.

ZKPs Enable Privacy on The Blockchains

In a traditional setting, every time a packet of information is exchanged, you need private and public keys or SSL certificates to decrypt it. The aforementioned ZKPs can be of great help here as the trust only needs to be established initially. They can improve E2E encryption by eliminating the need to query public and private keys after the first interaction. As they can easily verify certain information without revealing it, the information broadcasted to nodes by a client/device like a smartphone need not be revealed to the world. Hence, data or systems can’t be tampered with. This makes the system more efficient and secure as it is highly resistant to hacks.

Apart from using ZKPs, there are other methods to achieve E2E encryption on the blockchain. Raman Singh et. al. proposed a method where E2E encryption on the blockchain can be facilitated using certificates generated from a server for the sender and receiver (see figure below). Again, as discussed before, servers result in centralization; moreover, this approach shall require querying public and private keys every time the information is exchanged.

Nansen has recently launched Nansen Connect which provides Web3 E2E encryption to users. They claim to encrypt the private key on the user’s browser through Metamask before the information is sent. Since communication also occurs using a server, it might be affected by the same problems as discussed earlier.

ZKPs Make Blockchains Reliable

Several problems when it comes to the reliability of Web3 infrastructure, especially with decentralized storage systems can be solved using ZKPs. They can verify and establish the ownership of the data without exposing the owner or their other possessions. It establishes a layer of privacy and makes them more reliable. In case of ownership confusion or fraud because of loss, dislocation, or misrepresentation, ZKPs can help identify the correct data. In this way, data that is accurate and free of errors can be located. It is safe to say that your monkey won’t be getting lost anytime soon!

Improving The User Experience

As discussed earlier, a flawless UX is important to achieve the mass adoption of Web3. UX is a complex phenomenon that requires a combination of solutions ranging from ZKPs to other innovative solutions such as gasless transactions, ‘decentralized access control,’ seedphrase NFTs, etc. to bring about a significant improvement in how users perceive and utilize the crypto applications.

ZKPs can be a promising solution for improving Web3 UX from a security point of view. Seedphrases are an example of a sensitive Web3 component that results in bad UX. However, with ZKPs, wallets can be created without seedphrases by using a public key to generate a new wallet address. The public key is derived from a private key that is generated on the user’s device. Once trust is established through initial interaction, there is no need for a seedphrase. Therefore, with ZKPs, it becomes impossible to steal your monkey!

Apart from this, cryptography-focused solutions like Lit protocol seem promising when it comes to improving access control on the blockchain. Their ‘decentralized access control’ model gives users access to a service to only those who either hold an NFT or qualify for a particular requirement. After the requirement is met, nodes carry out a process called distributed key generation, resulting in the creation of a public/private key pair. But here’s a catch! The private key here is fragmented amongst each node involved in the process. Users can collect all these fragments to get the final key. Velas also uses a similar approach with a seedphrase NFT to create a passwordless solution. The only problem here is these fragments get stored on centralized servers like AWS, etc.

Turning our discussion towards gas and UX, ZKPs are going to make transactions cost-effective while maintaining the heightened security of Ethereum. Gas fees on Ethereum have gone up sharply after 2019 with blocks running at almost 100% capacity. By their very nature, ZKPs are a batch of transactions rolled into a single transaction, eliminating the need for discrete proofs. They help alleviate network congestion and bring down gas fees; certain With Ethereum Improvement Proposals like EIP-4844 and EIP-4488, it shall become almost free, faster, and frictionless to transact on the mainnet.

The concept of ‘gasless transactions’ put forth by protocols like Biconomy and Symbiosis Finance can also be considered as an attempt to improve the Web3 UX. With a very simplified interface, they enable users to pay for on-chain transactions in tokens of their choice. It does away with the need of understanding different chains, estimate gas, and figure out the correct RPCs. It is achieved by having versatile liquidity on multiple chains. With that being said, there are certain problems associated with this concept; price fluctuations are a major limiting factor as it makes the whole process unviable, probably sending us back to square one.

Improving The Developer Experience

Developing systems that are more composable would make life easier for developers working in Web3. Rather than having isolated solutions, there needs to be a focus on developing abstraction and aggregation platforms/layers like Spheron. On the other hand, solutions like Ceramic will enable better composability by storing the state and model of the application’s data. It will allow flexibility (mutability) with immutable data being stored on data storage platforms like IPFS or Arweave.

Also, developers well-versed in tech like SQL, and scalable; decentralized; and SQL-compatible solutions like Kwil can be of great help. However, for SQL-compatible solutions to work, data must be indexed properly. This can be achieved through solutions like Subsquid which provide APIs for such indexed data to make it easier for builders. On the other hand, protocols like Glitter make the Web3 onboarding process easier by providing indexing-as-a-service for developers. Data-validity solutions like Kyve can greatly reduce the errors and lag in initial node synchronization. Such solutions will stimulate the network’s security by facilitating new validators. In this way, developer experience in Web3 can be improved.

Apart from the solutions mentioned above, it’s important to note that the efficiency of systems has a huge role to play in the experience of agents in the system. When it comes to decentralized systems, efficiency is greatly impacted by tokenomics. Let’s take an example of a system where due to highly inflationary tokenomics, agents responsible for maintaining the network aren’t being incentivized properly. Such incentives are mostly in the form of native tokens. They make the system less secure for users and developers, and highly prone to attacks. Therefore, properly designed tokenomics, which is sustainable and ensures a healthy incentive system for every agent involved in the system, will result in a better experience for everyone.

Conclusions

The rate of development visible in the Web3 ecosystem is commendable and their commitment to their values serves as a glowing example for the path ahead. Although there is significant progress, the technology required for true decentralization is still underdeveloped, and as a result, many aspects of the crypto world are still centralized. Another problem is that the architecture required for decentralization is either not accessible (high requirements for hardware like a full node) or not user-friendly. There might be a general unwillingness among participants to help further this cause; as Moxie mentions: not everyone is going to set up their own nodes. Hence, centralized node providers are able to take advantage of this situation and censor information. Technology like light clients/nodes can help with decentralization and security on the blockchains.

The reliability of Web3 infrastructure is still low and needs to be achieved through significant improvements. It shall take a lot of effort to achieve true privacy on decentralized ledgers. Apart from that, a very important component of adoption is its ‘experience.’ We see that Web3 infrastructure provides a bad user and developer experience. Significant improvements through ZKPs, aggregation layers, etc can improve the experience.

While dealing with different aspects of the Web3 infrastructure, ZKPs seem to be stealing the show! They have the potential to increase the efficiency of light clients and nodes resulting in an efficient blockchain architecture. We also see how they can help establish a layer of security, reliability, and privacy for the ecosystem. By enabling the users to run business logic on their personal data to prove its correctness, ZKPs will enable them to have greater control over their data. Applications can scale using ZKPs as users won’t be required to establish trust multiple times. They will greatly improve the Web3 UX by drastically reducing the gas fee required to execute transactions. Also, the privacy enabled by ZKPs is regulatory compliant, which shall not create much friction with authorities and will potentially lead to the mass adoption of Web3.

Author is a Decentralized Finance (DeFi) researcher and analyst at Polygon with special emphasis on fundamentals, on-chain activity, and crypto narratives. Their other interests include studying Attention Economy, Layer 2 Solutions, and Derivative Protocols. They like to do gardening, scroll twitter, and explore different movie genres in their free time. They can be reached on twitter at 0xlol.

This research constitutes the personal views of the author formed as a result of research as well as their perspective. Polygon is completely unopinionated in its pursuit of excellence in blockchain ecosystems.

Additional Credits

Cover Picture Art: Darshan (Illustration) and 0xlol (Conceptualization)

Editing: ThePsychGuy

Meme: Shivraj

Additional Readings

Zero knowledge Proofs for Rollups & Stateless Clients

https://research.huobi.com/#/ArticleDetails?id=295

Design principles for web3. So everyone and their cat seems to be… | by Angela Ching | UX Collective

UX issues in web3 go beyond design, here is why. — Salil Naik

Web3 has a user experience problem | by Scott McDonald | May, 2022 | UX Collective

Defining the web3 stack

https://twitter.com/VitalikButerin/status/1479815125955715072

Infrastructure Lego: The Middleware Thesis — Deribit Insights

Blockchain middleware: The HTTP of the Web 3.0 age | by Apron Network

The web3 stack: how web3 will offer superior UX than web2 | by Polynya | Medium

Web3 Infrastructure Q1'22 Revenue Report | Messari

Web 3 Middleware — Zee Prime Capital

The Architecture of a Web 3.0 application

Moxie Marlinspike >> Blog >> My first impressions of web3

On Web3 Infrastructure — suzuha

A simple guide to the Web3 stack | Coinbase

Why calldata gas cost reduction is crucial for rollups | by Polynya | Medium

The Anatomy of MetaMask. An X-ray of Web3’s Beloved Fox | by Julia Wu | Jun, 2022

IPFS Usage Statistics

File.app

Filecoin Storage Stats

Filscout-Filecoin Explorer

Arweave Charts | ViewBlock

Decentralized Options Vaults (DOVs) are structured products offered on-chain, closely related to TradFi counterparts that combine several financial instruments to create a whole new payoff curve. The core function of DOVs is to use investors’ capital and employ options trading strategies in a completely automated and decentralized manner. These strategies may include covered calls, protective puts, or straddles. Before DOVs, option strategies were only available to accredited investors through over-the-counter (OTC) trading or by self-execution on option exchanges like Deribit or FTX.

DOVs allow their investors to earn true return on investment (ROI), not just passive income from liquidity provision. The capital is being actively invested in trading strategies, and is independent of the amount of trading being conducted i.e. there is no token “yield” in the traditional DeFi sense. From scratch, DOVs have grown exponentially to become the dominant part of the ~$1 Billion DeFi option TVL, with notionals trading in billions of dollars every month.

Over the past several months, DeFi ecosystems across different blockchains have witnessed a massive surge in new projects focused on structured product vaults with the objective of offering users sustainable yield. Given the infancy of these popular products, we aim to define some very basic suggestions on what a builder must keep in mind while launching DOVs. We aim to critically analyze core functionality behind DOVs, from the trading strategies used to the technology behind the vaults, and how we believe these vaults can be improved.

How do DOVs Work?

As mentioned previously, DOVs allow investors to deposit capital and then automatically trade popular options strategies with it. The most common options strategies employed by DOVs include covered calls and protective puts. Let’s look at these strategies in greater detail.

Through a covered call strategy, when vault sells a call option, it will also own the underlying security for that option. Similarly, through a protective put, when a vault sells a put option it will also sell the underlying security for that option. Let’s explore this in greater detail below.

Selling Covered Call Options vs Selling Put Options:

Let’s first look at the two of the most popular option writing strategies: selling covered calls and selling puts. A covered call is a financial strategy wherein the investor selling a call option owns an equivalent amount of the underlying security. This strategy can be created by holding a long position (spot) on an asset and then selling call options on that same asset to generate an income stream. This strategy entails very low risk as the investor’s ownership of the underlying can serve as a cover if the call option expires in the money and the buyer of the call option chooses to exercise. DOV users have a choice to choose either covered call or covered put strategy. If the user feels bearish, they can opt-in for the covered call position and earn yield as the market goes down. Vice versa for users who feel bullish, they can opt for the covered put option to earn yield. Let’s take a deeper dive into the two:

Selling a Covered Call:

- By selling a call option, you have the obligation to deliver the asset (e.g. ETH) at a predetermined price (strike price) to the option buyer if they exercise the option.

- If the seller of the call option also owns the underlying security (fully collateralized), the option is considered “covered” because they can deliver the instrument without purchasing it on the open market at possibly unfavorable pricing. Writing call options should be the same size as the underlying long position. For example, if you own 1 ETH, you can sell 1 covered call option. Owning the underlying asset is necessary because selling naked call options without owning the underlying asset exposes the options writer to unlimited risk.

- A covered call will limit the trader’s potential upside profit, capping gains above the strike price. For example, if you sell a call option with a strike price of $2,000, you are giving away profit of the underlying asset above $2,000.

- The goal of selling a covered call option is for the option to expire worthless, allowing the trader to earn the option’s premium while keeping 100% of the underlying asset as collateral

- A covered call serves as a short-term hedge on a long stock position and allows investors to earn income via the premium received for writing the option. Covered call selling typically does well during choppy or bearish environments as the spot price is unlikely to breach the call strike.

- Covered calls should be fully collateralized so that the risk does not come from selling the option as it is covered by the crypto the writer owns.

· If strike price < market price and it is fully collateralized -> writer still makes option premium + gains on holding the crypto.

· If strike price < market price and it is half/not collateralized -> then if crypto assets rocket in price, loss can potentially be unlimited.

Selling a Put Option:

• By selling a put option, you have the obligation to buy the asset (e.g. ETH) at a predetermined price (strike price) from the option buyer if they exercise the option
• Selling a put is an options strategy used to generate yield (income) when traders believe the underlying asset price is unlikely to fall below the strike price before the expiration date
• Note that the writer of a put option will lose money on the trade if the price of the underlying asset drops below the strike price at expiration
• The goal of selling a put option is for the option to expire worthless, allowing the trader to earn the option’s premium while keeping 100% of their collateral

What Should Buidlers Keep In Mind?

Adoption of ERC-4626:

The main problem developers face while building tokenized vaults is the integration of different yield bearing tokens. For example, in a situation where you want to build a DeFi app which requires integrating the tokens of each protocol, you will need to research each one, know their model of accruing yields, and adjust it into your code base. If you want to integrate vDAI of Maker DAO; stETH on Curve; and so on, you will need to understand the peculiarities of their smart contracts and build custom solutions to successfully integrate each of them into your DeFi app.

Apart from how stressful and time-consuming this process of integrating different yield-bearing tokens can be, it also increases smart contract risk because of potential errors. Developers will need to spend more time checking for potential loopholes in the adapters, and in some cases, they might even need to outsource it to smart contract auditors, which can be costly. This is more important now that attackers are breaching the integrity of a lot of protocols and DeFi apps. Hence, the creation of the ERC-4626 standard.

What exactly is ERC-4626? It is a standard API for tokenized yield bearing vaults that represent shares of a single underlying ERC-20 token. The vault standard introduces the concept of shares as a way of getting fractional ownership out of the entire pool. These shares refer to yield-bearing tokens. When users put any funds into the vault, the deposit function triggers the smart contract to mint a corresponding amount of shares to the depositors. The withdrawal function helps owners burn shares in exchange for assets. The ERC-4626 is a compatible extension of the ERC-20 standard. As a result, most of the usual variables, events, and functions that are applicable in ERC-20 token contracts still work with the ERC-4626 vault standard.

While there are a couple of prominent token standards at the moment, the DeFi world still has a recurring problem regarding tokenized vaults. DeFi aggregators have always found it quite stressful to aggregate several yield-bearing tokens because there was no standard. But now ERC-4626 makes it possible to have details of yield-bearing tokens with one API call.

The standard makes the integration of protocol easier and less prone to errors. Since there is a common standard that you can integrate, there is no actual need to build separate adapters any longer. It quickens development and enhances composability. Similarly, it reduces cost because builders no longer need to get auditors to help with their adapters and interfaces. Most importantly, ERC-4626 enhances security among dApps and yield aggregators that are dealing with yield-bearing tokens.

Who uses this standard? Protocols such as Balancer Linear pools, Yearn finance, Yield protocol, Alchemix v2, Convex finance yield pools, and more are already using this protocol actively. The problem of going the extra mile to enhance the security of DeFi applications with yield-bearing tokens is solved — to a large extent — with the introduction of this baseline standard. Use of composability and interoperability among various DeFi protocols will increase in the next couple of years. It is even possible that this standard will be a launchpad for building and shipping completely new products in the DeFi ecosystem.

Can Be in Line With Existing Successful DOV’s Strategies:

The appeal of the DOVs emerges from its seamless accessibility and simplicity for the user. Investors simply ‘stake’ their assets into the vaults which are automatically deployed into option strategies.

The strategies deployed thus far have been selling covered call and put strategies (which we discussed above) providing the highest base yield available in Defi (averagely 15–50%). On top of that, token rewards are distributed, providing an even higher yield for users. In some instances, the collateral in the vault earns staking/governance yields as well, creating three sources of yield in a single vault. This triple layer of option premiums, token rewards, and staking yield creates a significantly high and — more importantly — sustainable yield that is unprecedented in Defi.

Another major problem DeFi must solve is non-linear liquidations. Even centralized exchanges like Deribit manage non-linear liquidations with some difficulty. For the liquidation of large option portfolios, the delta (or spot risk) is managed first by executing a perp/futures position against the portfolio. The other greeks in the portfolio (non-linear risk) are then systematically liquidated over time with an active involvement by the intermediary.

By using a hybrid DeFi model where investment, collateral management, price discovery and settlement occur on-chain while non-linear risk management is performed off-chain, DOVs provide an elegant solution to this problem. All option contracts traded through DOVs are fully collateralized which eliminates the need for liquidations completely.

Refine Options Trading Strategies to Make Them More Dynamic:

All DOVs typically only offer covered calls or protective puts and they will trade on these options strategies on a weekly basis regardless of market conditions. While these strategies may minimize risk, DOVs are still dependent on market conditions.

Put simply, covered calls are riskier during bullish markets while protective puts are riskier during bearish markets. Covered call strategy faced a significant loss (especially in early 2021) when ETH jumped from $740 to $1200 in less than a week. Black swan events like this tend to be infrequent but significantly erode the strategy’s profitability. When the contracts being traded through these strategies expire ITM, it is the investors’ capital at risk, resulting in extremely low APYs and even principle risk.

However, these risks can be counteracted by simply accounting for market conditions before trading for strategies. DOVs should analyze the market through discretion, considering the option type, strike, maturity, and market factors, to trade rather than just employing automated strategies. For example, to predict extreme events, vaults can analyze the ETH price/option strike ratio. If the ratio is greater than 1, it indicates the sold call option is ITM whereas a ratio less than 1 indicates the option is OTM. This quantitative analysis can be done through a combination of oracles, on-chain data analytics, and well-built code.

If DOVs begin analyzing options and the market before trading through covered calls or protective puts, it may result in higher profitability for everyone!

Illusion of ‘Good’ Yield is ‘Bad’

Some of the protocols selling certain strategies in DOVs have been found to advertise fake high yield to make their vaults attractive. Who doesn’t like double digit APR in a risky environment? There are a number of ways to fake/tweak the numbers from excluding the loss from in-the-money weeks to only calculating the yield as an average of past few weeks (which necessarily smoothes any downfall).

Hence there’s a need to do away with the tradition of faking the actual numbers. True yield along with all the associated risks must be flashed on the UI to make the whole process transparent for investors. Doing otherwise is simply predatory.

Integrate Cross-chain Liquidity:

While “omnichain” or “crosschain” have become buzzwords for the NFT-enthusiasts, they are especially important in the context of DeFi. With capital in DeFi split across so many chains resulting in liquidity fragmentation, it’s necessary for any DOV to be functional across chains to their best extent.

There are two ways a DOV can be cross-chain: deploy on other chains or make use of cross-chain liquidity aggregators and Layer Zero. While deployment is typically preferred by most DeFi protocols, it could be expensive owing to the number of virtual machines and various deployment costs. Instead, making use of protocols like Layer Zero or 1Inch would allow for DOVs to maximize their capital and consequently their profitability.

Allow for LP Tokens Deposit

Most DOV deposits are typically single-asset: ETH, MATIC gOHM, etc., and there’s nothing much to it. If DOVs would allow for users to deposit their LP tokens (Polysynth, for example), this would allow for users to yield farm while unlocking liquidity for them to earn from option premiums as well. A protocol named Rage Trade approaches the deposit of LP tokens quite similarly through their “deep liquidity” functionality — LP tokens are used to dynamically unlock liquidity for perp trading as asset prices (and perp prices) increase and decrease.

Conclusion

The appeal of DeFi option vaults is tremendous. The current strategies that the vaults offer are just vanilla puts and calls, but these will gradually become complex in the future. The product’s structure will make it very difficult to use the vaults as a hedging tool. However, the protocols will be very approaching for bootstrapping liquidity for the options market, eventually making decentralized options more viable.

DOVs are an essential step toward democratizing finance for the masses. They also play a leading role in increasing demand for organic yield. Therefore, they address the issues of the unsustainable and circular yields that DeFi currently faces. Many of us have imagined the allure of AI and tech making their way into the financial industry — most people even believe the work of analysts and researchers to become obsolete as technology continues to develop. When you combine the benefits of automation in finance with decentralization — you get a DOV.

Authors:

This research article is authored by Polygon DeFi researchers: Eshana, Akhil, and 0xlol in association with Paradigm Trading. Eshana is a quantitative finance research intern at Polygon, and is a finance and computer science major at NYU. Akhil (Twitter) is a DeFi research intern at Polygon, and studies finance, math and computer science at NYU Stern. 0xlol (Twitter, Github) heads DeFi research communications at Polygon, with their research interests in DeFi derivatives, Web3 Infra, and Layer 2 Scaling Solutions.

Cover Picture Art: Darshan (Illustration) and 0xlol (Conceptualization)

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Additional Readings on DOVs:

DeFi Structured Products. Finance is complicated. There is no way… | by BenKaplan | Coinmonks | Medium

How to use DeFi Option Vaults (DOV): risks and return | by Andrey Belyakov | Coinmonks | Medium

Quantifying Risks of DeFi Options Vaults | IV League DAO

The Inner Workings of DeFi Option Vaults (DOVs) — Delphi Digital

A Deep Dive into Options Products in DeFi | by Juan Pellicer | IntoTheBlock | Medium

Overview of Options Vaults | Messari

A Quantitative Analysis of DeFi Option Vault Strategies

https://twitter.com/QCPCapital/status/1469963752623665152?t=CKZKKJZuZ9BmS4bGRSN7Rg&s=19

https://twitter.com/joey__santoro/status/1478489634300588032?t=DLCBrn1cEnBu6ecAlwEX3Q&s=19

https://twitter.com/two_prime/status/1513972960746483713?t=Wiyg3JyVjAA-S0PWxzuP8g&s=19

https://twitter.com/poolpitako/status/1388279685885440001?t=81SUbqYyVGG21cAmg9Gquw&s=19

The Ethereum Merge is a cryptocurrency event that will significantly change the way Ethereum operates. With this hard fork, Ethereum will operate on a new consensus mechanism “Proof of Stake (PoS)” from the originial “Proof of Work (PoW)”. It will also have an impact on the narratives surrounding ETH. The debate on ETH’s eco-friendliness shall take a new turn making it more ESG compliant, along with its utility as a long term debt (if you consider it as a bond). In this article, we shall cover the important proceedings taking place at various decentralized finance (DeFi) governance forums. We will not go into the intricacies of the merge as there has already been a considerable amount of debate and writing on the topic. This article is based on findings by our DeFi researchers Akhil Vajjhala and Jack, and has been edited for relevancy and readability by 0xlol.

Some Useful Resources to Learn about the Intricacies of ETH Merge:

On the Merge. Quick Takes | by Amber Group

What to Expect from Ethereum’s Merge Upgrade | Galaxy — Engineering a new economic paradigm.

A Step-By-Step Overview of Ethereum’s Merge Upgrade and Associated Risks | Galaxy

ETHEREUM MERGE — The Most Anticipated Event In Crypto Explained

Lido

Lido offers liquid staking for ETH holders who wish to earn yield on staked ETH2.0, but do not hold the required 32 ETH required in order to run a full node to stake their assets. Lido lowers the bar to entry for staking ETH, and provides stETH (a liquid derivative of staked ETH) that users can utilize within other DeFi protocols.

Lido is one of the most important pieces of the puzzle when we discuss the Ethereum Merge. It is concerned with the process of liquid staking, and has an important role to play when it comes to impact of the merge on ETH stakers in the PoS.

LIP-12: On-chain part of the rewards distribution after the merge

The Lido protocol upgrade that re-stakes newly appeared rewards after the Ethereum Merge will happen to achieve compounding rewards.

This proposal proposes to re-stake all collected execution layer (EL) rewards while minting only the protocol fee (10%) stETH as part of the beacon chain rewards distribution run. But doesn’t mint/distributes any protocol fee on the non-profitable Lido oracle report.

Distribution Mechanism should work as follows:

• Node operators collect ether-nominated execution level rewards on a dedicated vault contract. To be precise, MEV rewards could be collected in such a vault contract.
• The Lido contract withdraws all collected rewards from the vault, re-stakes it and mints new stETH only for protocol fee (10%) as part of the beacon chain (or consensus layer, CL) rewards distribution run.
• In case of the non-profitable Lido oracle report, don’t mint any new stETH (i.e. the protocol fee).
• The proposed way brings compounding rewards, has a fast shipment time due to little impact on the existing distribution scheme. It’s also reasonably automated and self-governed. And finally, it falls back to the already adopted solution in case the Merge hard fork is delayed.

Ethereum consensus rewards analysis

• Main goal: To measure if any client is consistently generating more block proposer rewards.
• Proposes to develop a custom piece of software that is able to get block proposals from all the clients at each slot and evaluate its score. The idea would be to store these blocks in a database and analyze them offline. Creating a fork of vouch (validator client) that collects the block proposal of each client and scores each of them, which should objectively output which blocks would give a greater reward.
• Will test if operating validators in different parts of the world could impact their performance. Hence, will monitor how latency impacts block proposal rewards, and whether the same client performs differently in different locations.
• Will analyze: What votes does an attestation have? Which aggregations should better be chosen to be included in the block proposal in terms of rewards?
• Every epoch (6.4 minutes) a validator proposes an attestation to the network. The attestation is for a specific slot in the epoch. The purpose of the attestation is to vote in favor of the validator’s view of the chain, in particular the most recent justified block and the first block in the current epoch (known as source and target checkpoints) — what votes are necessary?

Airdropping Fork Tokens & Protecting The Peg:

• If there is any airdropped ETH PoW to ETH stakers, it will be returned to the underlying holders of stETH.

Lending

AAVE

AAVE is a decentralized lending market, with borrow and lending yields based on the utilization rate (amount borrowed / amount deposited for lending).

Given that the merge is a perfect opportunity for either PoW airdrops or simply hoping that the merge hasn’t been priced in yet, leveraging your position and adding more ETH seems the move for most crypto investors.

However, there are quite a few issues with this:

• If there are any Merge-related issues -> ETH price falls -> mass liquidations occur.
• Aave lends user collateral -> issues with Merge -> both Aave and users get badly affected.

Aave’s borrowing limit has decreased, its fees have increased — until ETH borrowing has been suspended entirely until the Merge is complete.

Technical analysis Aave <> Ethereum’s PoS Merge

• Claims the merge should not affect AAVE’s systems
• Block structure: Not affected.
• Block time: Only Aave governance is slightly affected (voting duration).
• Smart Contracts: Aave is not affected.
• Sources of on-chain randomness : Not affected
• New concepts of safe head and finalized blocks (underlying change in Ethereum finality): Aave could be slightly affected, but not on smart contracts.
• Spoke with Chainlink, and their stand will be with PoS chain — Chainlink will not integrate in Ethereum PoW forks, it will fully commit to the PoS Chain; this ensures that there aren’t any issues with oracles and data

AAVE ETH PoW Fork Risk Mitigation Plan:

Most tokens, excluding ETH, will likely be worthless on an ETHPoW chain. Hence, a strategy which users may employ to maximize their cryptoasset holdings, will likely be to borrow as much ETH as possible (collateralized mainly by stablecoins or other tokens).

In addition, flows from stETH holders to ETH should also be observed, since stETH will likely also be worthless on an ETHPoW chain.

Speculative strategies related to the PoS merge and the potential ETHPoW fork will likely have implications for Aave, particularly because Aave enables ETH to be borrowed from stETH. stETH collateralised ETH borrowing has become a popular strategy, and has increased ETH market utilization to a level of 62% at the time of writing.

Risks related to the ETH market becoming increasingly utilized:

• High ETH utilization potentially makes liquidations harder or impossible.
• In a situation where the ETH market becomes heavily utilized and markets start experiencing high volatility as a result of the merge event, liquidations of regular ETH long/stablecoin short positions might not be possible.
• This will be due to the fact that liquidators will not have access to ETH as collateral since the majority of ETH will be borrowed.
• This could in turn lead to some positions becoming uncollateralized.
• High ETH utilization increases the ETH rate to a level where stETH/ETH positions are making negative APY.
• Once the ETH borrow rate reaches 5%, which happens shortly after 70% utilization rate (we are at 63% right now), stETH/ETH positions start becoming unprofitable.
• Currently, borrowers on Aave are not leveraged maximally due to depeg risks. As a result, it is possible that some positions will have their APY negative much earlier. This will cause users to unwind their positions up until the ETH borrow rate reverts to a stable level where the APY becomes tolerable.
• This means that we would see a lot of stETH to ETH redemptions, and in turn a downward push on the stETH price. It will already be under pressure due to regular stETH holders switching to ETH to gain upside on ETHPoW work.
• Already high ETH utilization causes regular ETH suppliers to start withdrawing their ETH.
• As a result of the uncertainty and risks related to the ETHPoW fork (and PoS merge in general, and ETH utilization on Aave in particular), current liquidity providers may become increasingly worried about their ETH on Aave, and in turn, may withdraw ETH on the supply side.
• The utilization rate would increase unrelated to ETH borrowers.
• Also, if ETH price drops then ETH long/stablecoin short positions will likely need to be deleveraged by selling supplied ETH.
• This is why ETH borrowing has been frozen.

Alternative: Increase the variable borrow APR at 100% utilization from 103% to 1000%

AAVE DAO stance on Ethereum PoW fork

• This ARC calls for the Aave DAO to commit to selecting the Ethereum Mainnet running under the Proof of Stake consensus over any Ethereum fork running an alternative consensus (such as Proof of Work).
• The ARC will formally signal that Aave DAO deployment will occur solely on Ethereum PoS.
• Authorizes the Community Guardian to take the necessary actions to shut down Aave Deployments on any forks arising from the Ethereum Paris Hard Fork (the Merge).

AAVE snapshot vote:

• Proposes to Limit ETH borrowing approaching merge

Compound

Compound is a lending market very similar to AAVE, but with less available assets for borrowing. It exists solely on Ethereum, while AAVE has gone multi-chain.

Adjust ETH Interest Rate Model

Update the cETH interest rate model to a new jump rate model with the following parameters:

• Rate at 0% utilization: 2%
• Optimal utilization (kink point): 80%
• Rate at optimal utilization: 20%
• Rate at 100% utilization: 1000%
• Set a borrow cap for the cETH market of 100,000 ETH.

Dexes

Bancor

Bancor is a decentralized exchange, enabling users to swap between tokens. Its unique value proposition is the ability to provide liquidity to the dex without facing impermanent loss through its native BNT token, however this has come under fire recently due to poor performance in the recent bear market where users did face impermanent loss.

Proposal: Determine action in the event of a PoW Fork — LEVEL 1 Under Review — Bancor Governance Forum

• Proposal to disable Bancor contracts on all PoW forks
• Disabling Contracts:

This option would include disabling all Bancor platform functions on an Ethereum fork. This option should incur little to no risk. The main argument for this is that most tokens on a proof of work fork will quickly become worthless, which would result in the Bancor platform being drained of any value that could be extracted on the forked chain.

• Do Nothing:

Taking this option: nothing would be done in the event of an Ethereum fork. This would incur no risk to Bancor on Ethereum Mainnet, however, any value that could potentially be extracted from an Ethereum fork would be quickly lost.

Derivatives

Synthetix

• Synthetix will suspend all Synthetix contracts on both Ethereum and Optimism, around 3 hours before the expected merge block and resume activities after ensuring that Chainlink feeds and the rest of the protocol are stable.
• The SNX token will still be transferable, but all other parts of the protocol, such as synth exchanges, futures, loans, staking (claiming, mint, burn), and bridging will be suspended. Once the suspension is complete, communications will be made on all proper channels, and all protocol partners will be informed.

Algo-Stables

Frax

[FIP — 101] Make FRAX stablecoins only redeemable on PoS ETH

• Sam Kazemian (FRAX’s founder) has submitted a proposal for the project’s stablecoin to be redeemable solely on the Ethereum proof-of-stake (PoS) mainnet.
• FRAX will reject any Ethereum PoW fork.
• While this is a step towards an Ethereum PoS future, it may create FUD amongst Ethereum PoW users.

Stablecoins (CDPs)

MakerDAO

Risk and Market Impact Overview

Futures Backwardation and Negative Funding

• Spot holdings of ETH would receive any POW forked tokens, while exposure to ETH quarterly futures or perpetual contracts would not. Assuming efficient markets, this means that quarterly futures after the expected merge date should begin to trade at an additional discount with respect to ETH, based on the expected value of POW fork tokens.
• Recently, we’ve seen the December 2022 quarterlies flip from premium to backwardation, which reflects the possibility of a POW fork accruing some ‘saleable value’. In practice, market participants can purchase spot ETH, and then sell an equivalent amount of ETH futures to wager on fork value while remaining delta neutral. As the expected date of the merge draws closer, we may see some similar activity on perpetual contracts, with significant discount and negative funding reflecting the expected value of POW forked Ether.
• Impacts on Maker:

Nominal cost of leverage through futures contracts (excluding potential fork value) declines, creating competitive pressure vs Maker vaults.

Users who consider market implied fork value to be too high are incentivized to leverage on futures, while those considering lower implied value may prefer leveraging with Maker vaults (where the vault owner will still receive any potential fork tokens).

• Responses:

Maintain competitive rates to avoid losing too much volume to futures contracts.

stETH Discount

• stETH and other liquid staking assets are likely to become worthless on any POW Ethereum fork.
• As a result, the market price of liquid staking assets may decline based on the expected value of a POW forked ETH.
• Impacts for Maker:

Nominal cost of leverage through futures contracts (excluding potential fork value) declines, creating competitive pressure vs Maker vaults.

Users who consider market implied fork value to be too high are incentivized to leverage on futures, while those considering lower implied value may prefer leveraging with Maker vaults (where the vault owner will still receive any potential fork tokens)

• Responses:

Monitor stETH liquidity and respond with parameter changes (increasing stability fee or liquidation ratio) if necessary

Monitor competitive rates using ETH collateral across defi lending protocols

External Asset Fork Choice

• Ethereum hosts a broad variety of externally backed assets. This includes cross chain bridges, centralized stablecoins, and real world assets (RWAs). Because these assets are backed by extrinsic collateral (either held off chain or on another chain), they can only be fully collateralized on a single chain at a time and the issuers will generally need to recognize one chain as canonical during a fork.
• The merge upgrade has strong support across the Ethereum community, DeFi users, and protocols, which should help ensure that fork choice is unanimously in favor of mainnet (POS) Ethereum. However, there is some level of risk that one or more external asset issuers could recognize a PoW fork, motivated by financial exposure to miners or other reasons. This could render relevant assets bridged into mainnet Ethereum worthless.
• Tether in particular has been raised as a possible risk, due to potential financial ties with miners.
• Impacts for Maker:

Minimal impact if all externally backed asset issuers support merge upgrade

If one or more issuer supports POW fork, this could cause significant impact to DEX liquidity pools and other protocols accepting the asset as collateral.

• Responses:

Confirm merge support from key external asset providers that interact with Maker protocol, including: Circle, Paxos, Binance, Bitgo, Gemini, Centrifuge issuers, other RWA issuers, and services bridging DAI out to other chains (eg. Wormhole, Axelar, Gravity Bridge, Multichain).

Liquidity Pool Protocols

• Maker does not make user collateral available to be borrowed, while many other lending protocols including Aave, Compound, and Euler do. In the aftermath of a PoW fork, a significant subset of assets on the fork chain (including stablecoins and bridged assets) would become worthless instantly. This could cause insolvency in pooled lending markets, and incentivize users to borrow all available ETH in the market (as the one asset most likely to retain some value in a fork).
• Withdrawals of ETH from liquidity protocols, particularly Aave and Euler, could cause a spike in ETH borrowing costs that would put pressure on leveraged stETH positions and potentially impact the price parity with ETH.
• Impacts for Maker:

Possible migration of some users from external lending protocols to Maker vaults.

Possible withdrawals of ETH from lending protocols putting pressure on stETH.

Potential for decline in decentralized exchange liquidity for ETH pairings around the merge.

• Responses:

Monitor user behavior and maintain competitive rates to facilitate any potential migrations or user acquisition.

Monitor stETH leverage positions and ETH lending utilization on Aave, Euler.

Monitor exchange liquidity and consider parameter changes if needed.

Oracle Networks and Indices

• Maker and other oracle networks like Chainlink are planning to support the merge and consider mainnet (POS) Ethereum as the canonical chain. However, the possibility of a POW fork complicates this somewhat, with heightened possibility of faulty data due to potential centralized exchange issues or ticker collisions.
• Impacts for Maker:

Increased possibility of bad / outlier data delivered to oracle feeds.

Possibility of market disruption due to bad price data incorporated in 3rd party oracles or perp indices.

• Responses:

Confirm centralized exchange plans with respect to PoW fork listing, tickers, and API changes.

Encourage industry players to adopt alternative ticker for any POW fork, avoid collisions, and ensure continuity of mainnet Ethereum data

Network Downtime

• The merge is arguably the largest upgrade in Ethereum’s history. With this significant protocol change, comes increased risk of technical faults that could potentially cause liveness failures and unavailability. If Ethereum goes down for a period of time, defi protocols like Maker could experience price gaps (discontinuous price drops) in collateral assets that could push vaults into liquidation or even insolvency.
• Impacts for Maker:

Increased risk of downtime and liveness faults around time of the POS merge.

Possibility of negative price gaps during any network downtime.

Reduced ability for users to deleverage or defend their vault positions.

• Responses:

Consider parameter changes to increase margin of safety on vault positions (e.g. raising liquidation ratios, increasing stability fees on higher leverage vault types).

Encourage users to increase their own margin of safety against liquidations in the lead up to merge upgrade.

Replay Attacks

• Replay attacks allow for a transaction or message signed on one chain to be “replayed” on another chain in certain cases. Ethereum users (and even custody or infrastructure providers) may fall victim to so-called “replay attacks” in the aftermath of a POW Ethereum fork.
• While EIP-155 offers a simple protection against transaction replaying by adding chain id as a transaction signature parameter, there is no guarantee that a PoW fork would adopt a different chain-id from Ethereum mainnet (chain-id 1).
• Impacts for Maker:

Increased possibility of unintended transactions on mainnet, replayed from POW fork chain (eg closing vault positions, selling fork-DAI or fork-MKR tokens, etc).

Possibility of mainnet transactions, including Maker oracle and keeper operations, being replayed to POW fork chain.

• Responses:

Share info about replay attack risk within Maker community.

Advocate for POW fork to use alternative chain-id (instead of chain-id 1 which will continue to be used by mainnet Ethereum) to avoid replaying transactions.

If your favorite protocol is not mentioned here, it is either because we were unable to find any significant information about it on forums, or we simply missed it (not intentionally).

Credits:

Research and Compilation: Akhil (Twitter) and Jack (Twitter)

Editing: 0xlol (Twitter)

Art:

Illustration: Darshan (Twitter), Conceptualization: 0xlol (Twitter)

Where are we now?

Today, there are roughly 3.8 billion social media users, and with the proliferation of cheaper mobile devices worldwide, the number of users expands yearly.

While a part of everyday life, social media in its current form is almost as addictive and toxic as it is beneficial. Existing networks face criticism about biased moderation, exploiting user data, addictive algorithms, and siloed ecosystems. Truly ‘fixing’ social media requires a complete paradigm shift, and decentralized social media solutions are the closest we’ve come to a truly democratized social sphere.

Reimagining Social Media from the Ground Up

While web2 companies focus on social media as a single product, web3 expands the idea of social networks into multiple layers. The base layer is a social graph: it maps profiles, followers, and their connections. Next is the app layer, where users can consume content and interact with their social graphs. For reference to web2, think of social graphs as followers and app layers as feeds. Through blockchains, there is no single entity controlling the social graphs. Instead, your social graph becomes an asset rather than a product owned by a corporation.

Obviously, the allure of owning your social graph isn’t enough to convince billions of users to ditch their existing products. There is another gap to fill, given how users are becoming increasingly upset with social media policies and executives. Aside from data ownership, complaints over fragmented followings, censorship, and closed source algorithms offer a chance for Decentralized Social media (DeSoc) to usurp market share. There is frankly no better time for this potential transition to DeSoc than right now. Existing users are demanding a better experience, and DeSoc can act as a catalyst for crypto adoption; the latter is in need of a popular product that can catalyze its early adoption stage.

Tackling the Issues

While web2 followers and connections are siloed within each app, web3 social networks allow you to bring your followers with you to each app. Imagine the simplicity and time saved if you could have all your YouTube subscribers instantly follow you when you launch an Instagram page for your brand. This is the beauty of separating the social graph from the app layer; your graph remains the same while the app layer is flexible. With future customizability, the possibility of a self-permissioned follower transfer, where only select followers are ported over, can be easily implemented.

This idea of owning your connections becomes more significant when discussing moderation and censorship. Donald Trump received a ban from Twitter, then went off to make his own social media application: Truth Social. With that transition, he lost his existing followers and funneled into a deeper echo chamber. It remains far worse for individuals who are not political figures and risk losing their livelihoods from social media bans. Competing DeSoc applications are experimenting with a variety of moderation techniques to remain within legal bounds while also avoiding the overreach of web2 moderation.

Lens protocol, a social graph layer built on Polygon, has arguably the best approach to moderation: they simply leave the moderation up to the app layers, where the content is posted. If users are banned or censored on one app layer, they can simply move to another protocol that offers a similar experience. The users get to keep all their followers and continue as if nothing happened. Now, instead of turning social media companies into the arbiters of truth and hate speech, users get to interact with whatever frontend will accept their content. Truly a free-market experience!

The final piece of the social media puzzle requires solving algorithms. Arguably more valuable than gold nowadays, popular social media apps prevent their algorithms from leaking into the public domain like they are the holy grail. However, these algorithms are designed to be as addictive as possible. Your data is how these companies profit, but your time is how they gain more data. You have no control over the algorithms currently. If you want to see more motivational videos one day, or a less addictive algorithm another day, you have no way to do so. In a DeSoc protocol, individuals can create open-sourced algorithms or multiple app layers with different algorithms to give users greater control over the content they see. Not only is this a step forward in customizability, but also potentially groundbreaking for the next generation of social media users, such that they don’t become as addicted as the current state of Gen-Z users.

DeSoc Trilemma

Though it seems like DeSoc is the answer to all our problems with web2 social media, there is no perfect solution. Yes, DeSoc solves the problems mentioned above, but it introduces its own set of complications. We’ve coined the term “DeSoc Trilemma” to highlight the tradeoffs made in security, scalability, and user experience (UX) when designing a DeSoc protocol. A slight twist on Vitalik’s “Blockchain Trilemma,” no protocol we’ve reviewed has been able to successfully optimize all three characteristics.

Security vs Scalability

Foremost, security indicates two things in this trilemma: the decentralization of a blockchain as well as the executor of transactions. Decentralization of a blockchain is simple: with more validators, blockchains become more decentralized and secure. However, this introduces the tradeoff between security and scalability. The more decentralized and secure a blockchain is, the harder it is to scale. That explains why no DeSoc protocol could ever truly live on Ethereum, as the gas fees are too high and the network would become too congested. For the time being until Zk-rollups become cheap and usable, a DeSoc protocol needs to operate either on a sidechain, sub/supernet, or a standalone L1. The most secure blockchains are not the best homes for DeSoc protocols, but in fairness these protocols don’t necessarily need the security of Ethereum unlike DeFi protocols.

Security vs UX

When it comes to the execution of transactions, some DeSoc protocols execute the transactions themselves. For example, a user follows someone and only signs a message to make this happen. They don’t pay the gas fee or actually execute the transaction, instead this role falls onto the protocol itself. This introduces the tradeoff between security and UX. Obfuscating gas fees is a massive step forward in UX. Imagine how horrible it would be to pay a small fraction of Instagram’s AWS bill every time you wanted to post! In fact, the ultimate UX is one where you connect your wallet but never have to deal with metamask pop ups prompting you to sign contracts or pay for transactions. This comes at the cost of giving further permissions and control of your wallet to smart contracts, which run the risk of being hacked. While facilitating mass adoption, it goes against the decentralized nature of web3. UX is arguably the biggest friction point in crypto adoption; in order to facilitate widespread adoption, decentralization maxis may need to look the other way.

In fact, Lens’ gasless API is the industry leader when it comes to tradeoffs between security and UX for executing transactions. The API allows users to perform transactions on a blockchain network without paying any fees. It makes DeSoc comparable with free-to-use web2 social media. Reducing the users’ need to wait until their transaction has gone through, the gasless API allows them to scroll to the next post and continue interactions freely.

The API allows the user to simply sign a message (e.g., as a comment), then a relayer receives this message with the relevant information needed to post the data on chain, completing the transaction. This method is slightly more gas-intensive for the relayer since they must verify a signature and then post the data on-chain. However, it makes the experience far more enjoyable and rewarding for the user. The app layer platform is required to pay the gas fees, meaning it would be the duty of Lenster or LensFrens to pay the expenses. While the downside of using the gas-less API is that users rely on the relayer to post the transaction on-chain rather than completing the transaction themselves, the trade-offs are worth it, given that social media posts don’t require the same security level as financial transactions. Additionally, the relayers have increased flexibility, with an hour grace period for posting the transactions on-chain officially, they can avoid periods of high gas fees.

UX vs Scalability

The tradeoffs made between UX and scalability are trickier to analyze. Take for example, DeSo (not to be confused with the term DeSoc we’ve been using), a blockchain specifically created for social applications. DeSo has scaled to over 1.5 million users (far greater than competitors like Lens, with just over 50,000 profiles) but it lacks the surrounding ecosystem that Polygon users can benefit from, such as gaming and DeFi protocols. Imagine being able to use your Lens profile on Polygon as collateral within a DeFi protocol to take out a loan. This value-additive composability benefit simply does not exist on DeSo or any DeSoc protocols built on stand alone blockchains. Similarly, Cyberconnect is extremely scalable with over a million accounts, as it is blockchain agnostic, allowing you to take your social graph to any blockchain. However, the tradeoff is that Cyberconnect cannot utilize NFTs within its ecosystem because of its design. While saving on compute and simplifying the overall design process, losing out on NFT compatibility is a massive loss. Take for example in Lens, where NFTs represent both your profile and your follows. It enables secondary sales of profiles, creating an entirely new market. Don’t want to create a meme account with a large following? Just buy an NFT profile that caters to that audience already. Additionally, NFTs enable further revenue capture for creators. By making posts collectible, creators can introduce exclusivity and therefore charge a fee for the content.

Can Decentralized Social Media Become a Reality?

Decentralized social media may provide the only realistic solution to the challenges users face with existing web2 social media platforms. But the question remains: is mass adoption even possible? From what it seems, the decentralization maxis will have to waive the white flag in order to prioritize UX and scalability so that DeSoc can finally see sustainable product market fit. The correct approach appears to be the separation of social graphs and app layers to further push customizability and avoid moderation concerns that exist in web2. Finally, prioritizing composability by building on blockchains with ecosystems outside of social media, such as gaming and finance, as well as utilizing NFTs within the design, allows for the best user experience while offering optionalities not found in today’s social media design.

This article was written by Jack McCarthy in collaboration with DeFinci Digital. Jack is a Decentralized Finance (DeFi) Analyst at Polygon, highly interested in designing premier tokenomics designs and real world applications of DeFi. He is currently the Co-President of Boston College Blockchain Club, while studying finance and business analytics at the Carroll School of Management. Feel free to reach out on twitter @offdeblockchain

Cover Picture by: Darshan Adroja

Editor: ThePsychGuy

In part -1 of this research series, we tried to analyze the various problems associated with the Black Scholes Merton Model’s (BSMM) assumptions as well as certain associated fractals. Now we will analyze how such problems are being solved in practical environments. It must be noted that it’s not appropriate to study a ‘mathematical model/equation operating in an engine’ as an ‘isolated entity’. This equation/model gets impacted, as well as impacts other parts of the system, and hence a ‘systems overview’ is required to get a comprehensive evaluation. Through this article, we 0xlol and Akhil Vajjhala try to investigate the adjustments made to standard BSMM by DeFi Protocols to increase its accuracy in pricing option positions on the blockchain. You can connect with us on twitter at 0xlol and Akhil.

Summarizing Part — 1

Read part -1 here

BSMM is based on the concept of dynamic replication of a portfolio such that the price of a derivative should be equivalent to the cost of replicating this portfolio. The model theoretically estimates the price of European-style options on a stock/asset that doesn’t pay any dividends (during the lifetime of that option). It takes into account certain assumptions which makes it ‘kind of’ unfit to price on-chain options.

The model assumes that this portfolio can finance itself i.e. no transaction fee or taxes are involved, contrary to which in DeFi — there exists significant gas-fee, costs to borrow collateral, etc. Further we see that the concept of risk free interest rates (RFIR) isn’t properly formed in DeFi. Since BSMM assumes that position’s strike price is discounted for a constant RFIR, this can introduce certain errors. Also dividends are pretty common in DeFi, which is in contrast to model’s assumption that there are no dividends throughout the life-time of the option.

BSMM assumes a constant level of volatility throughout the life-time of the option. This is certainly not true as probability distribution of rate of returns (RORs) on major crypto assets (ETH and BTC) are skewed. This can result in certain estimation errors, especially when estimating for implied volatility (IV).

Although we have majorly focused on assumptions taken by the model, it must be noted that in a trading environment — factors like trade size, demand-supply dynamics, IV skew, etc. impact the option pricing. And hence, it becomes necessary to factor them to have a healthy pricing model.

Now, let’s have a look at how such assumptions and problems are being adjusted for when pricing options on the blockchain infrastructure.

SYSTEMS:

In this section, we will review how different protocols have been using BSMM with some adjustments. BSMM can also be considered a ‘base’ model, on top of which certain manipulations are carried out to make it appropriate for the immediate environment. As researchers, we have criticized the arrangements below to draw attention towards certain flaws, but it shall not be construed as ‘FUD’. No matter to what extent such protocols have been successful in their quest, pricing options accurately on-chain isn’t an easy task. Therefore, these experiments should be considered as stepping stones towards a better future for DeFi derivatives.

SIREN

Siren is an options trading platform that uses the BSMM to price its options. It uses an on-chain oracle instead of an off-chain oracle to retrieve the IV. SIREN’s automated market maker (AMM) includes features that create a simulation of market depth, including price impact. This feature ensures that liquidity is always available for other traders, as the price impact will increase with an increase in trade size.

Additionally, the price impact creates an “urgency premium”. If a trader wants to complete a very large trade all at once, it will cost them more (benefitting SIREN’s liquidity providers (LP) in the form of increased premium profit). This prevents market manipulation and is a safeguard to option writers. These factors together form the basis for SIREN’s option pricing.

Analysis:

However, Siren’s variant of BSMM doesn’t deviate much from the standard version. We’ve already demonstrated this is part -1 that this doesn’t work well under the realms of DeFi. There’s a need to drastically improve this mechanism to bring stability to the system, as well as to safeguard the LPs from the adversarial impacts of using standard BSMM.

LYRA

Lyra is an options trading protocol that utilizes an automated market maker (AMM) to trade options with their collateral in the pool. The protocol’s pricing mechanism uses BSMM as a base model, and adjusts IV by taking into account the skew (through skew ratio or SR) and the trade size (by the concept of standard size or SS). SS is linearly related to number of contracts traded.

One of the major problems with on-chain options is IV arbitrage, which can be attributed to skew. So, how does Lyra solve this problem?

Lyra uses a variable called ‘trade volatility’ which prevents arbitrage in the protocol by neutralizing the gains one can earn through arbitrage. Let’s suppose an on-chain arbitrageur or searcher comes across a front-running opportunity. The ‘trade volatility’ dynamically sets price impact in such a way that even if someone buys a few positions in hope of selling them higher, there’s a high probability that they have to sell them for a lower price. The graphs below illustrate this dynamic.

Trade volatility is calculated as a product of baseline IV and SR (ratio of the ‘IV at a particular strike price’ to the ‘baseline IV’ with the same expiry) to adjust the IV at the strike of a particular option in the set.

The protocol initializes a ‘baseline IV’ for each set of options with the same expiry. Baseline IV is the IV of an option whose strike price is equal to the spot price at a particular moment in time. This IV serves as a baseline or reference to adjust or fine-tune IVs of other option positions in the set. Also, it is adjusted according to the number of SS traded. It is increased by 1% when 1 SS is bought by AMM (or sold by pool) and vice versa.

At different points in time, different option positions will be at their strike price, and hence baseline IV is dynamic.

It must be noted that to accommodate the price impact created by the position size, for every SS bought, SR is increased by a constant value (initialized as 0.0075). Hence the SR is directly proportional to the IV of the option at the strike price and the position size.

In this way, Lyra adjusts for skew as well as the trade size. In the end, after these adjustments, a base premium (W) is generated by BSMM.

On the top of this base premium (W), to compensate for liabilities and fat-tailed events, Lyra incorporates two additional (dynamic) fees on the premium apart from the gas and exchange fee. So, how do these fees compensate for liabilities and fat-tailed events?

As discussed earlier, the ‘intensity’ of fluctuations in IV (and therefore option prices) changes according to the contract’s proximity to its strike price, resulting in a volatility smile. This sensitivity of option prices to fluctuations in the price of the underlying asset is called vega. A high amount of vega indicates the presence of increased liabilities for the system (as options with higher vega represent unstable entities in the system), especially to pools consisting of option’s writers collateral, and premium.

And hence, every other trade which contributes to ‘net liability of the system’ or ‘vega risk’ or ‘net vega exposure relative to the size of the pool’ is charged a dynamic fee to disincentivize such liabilities, and vice versa. This variable fee results in an ‘asymmetric spread’ around the base premium (W) obtained earlier to make option positions expensive for agents inducting extra risk in the system. Another dynamic fee (variance fee) is to hedge the system against the ill-effects of fat-tailed events such as AMM losing out to impermanent loss (IL)etc.

In its current form, Lyra is integrated with the Synthetix pools. This means that when a trader purchases a CALL option from the AMM, the AMM purchases the base asset (for example sETH) from the Synthetix debt pool. LPs are typically left with long exposure to the underlying asset, and are exposed to IL. These risks will be hedged in the next release of Lyra, called “Avalon.” Cross-chain IL protection may also be employed to hedge IL risk exposure.

Analysis:

In spite of all these adjustments, there are other harmful factors in the system like toxic order flow. The usual practice is to increase the fee which disincentivizes such flow. But at the same time, it results in illiquidity for the system. Lyra AMM allocates a certain capital for insurance or ‘delta-hedging’ to protect LPs’ capital (from certain negative exposures) along with keeping the system liquid (as LPs would prefer to provide capital in a system where it’s safe) while keeping the prices ‘competitive’.

Lyra does a good job by deploying corrective measures for all the potential hazards resulting from flawed assumptions of BSMM as well as for other harmful factors. However, certain ‘rigid adjustments’ in IV (a constant change of 0.0075 per SS trade, for example) can be made dynamic.

Also, even though the factors like baseline IV and SR are initialized from the liquid markets, moving further in the time, only SS determines their value majorly. And hence, there’s a need to factor in the supply-demand dynamics from the liquid markets to make the price-discovery more accurate.

PREMIA

Premia is a DeFi protocol that is concerned with American-style options. Its pricing mechanism consists of 3 parts: the modified BSMM, current pool level (adjusted for the impact of position size), and a coefficient to update the price level depending on the market’s liquidity.

The protocol uses a modified version of standard BSMM by using a full volatility surface (put on chain w/a Chainlink Oracle) rather than using single, constant volatility. The oracle takes the traded IV from the most liquid options markets for each cryptocurrency (BTC, ETH, etc.) and interpolates the entire surface for each asset based on all known points of IV.

Volatility surface is then parameterized and put on-chain through Chainlink’s decentralized network of nodes. This allows anyone to query the oracle on-chain to get the specific IV for any option (strike, maturity, call/put).

This IV is plugged into the BSMM in Premia’s contracts to get the base premium.

The price of an option on Premia is directly proportional to the C-value of the pool in which it is traded. The C-value, which represents a ‘dynamic multiple’ to standard BSMM (as a base model), is regulated by demand and supply dynamics as well as position size in the pool. When liquidity is added to the pool, the C-value decreases, and when liquidity is removed from the pool, the C-value increases. Initially, the pool has a very high C-value in order to incentivize LPs, and penalize liquidity removers (option buyers). If there are no option buyers, then C-value adjusts itself accordingly to create demand for the contracts.

Along with factoring in demand, the pricing mechanism makes sure that liabilities associated with a large position size are taken care of. A trader cannot buy out the entire pool of options at the same premium, hence discouraging the ‘fragmented liquidity’ in the pool. Also, the C-value acts as a ‘discrete liquidity adjustment coefficient’ as it is correlated with liquidity in the pool.

Analysis:

Even though the mechanism is sophisticatedly designed to mitigate risks provided by inappropriate pricing through standard BSMM, it introduces certain inefficiencies and illusions. The very-first LPs in the pool are lured to get the maximum yield on their deposits, but the probability of option buyers buying expensive positions is pretty low. And if someone buys these options, it is harmful for them.

This mechanism also creates a problem of illiquidity for option holders as they can only buy, and exercise positions from, and in the pool, there’s no way they can sell them back (as it introduces bi-directional risk to LPs). Along with this, there will always be excess liquidity in the pool as a result of the pool’s design (as initially, high prices for the contracts won’t create a demand for the liquidity provided at the same time). Instead of creating a zero-sum game, there’s a need to compensate the initial LPs with ‘real-yield’ to establish a sustainable incentive structure.

Updates: Premia has recently launched on Optimism where:

— they have enabled the sell-feature

— users can take advantage of cross-chain arbitrage.

DOPEX

Decentralized Options Exchange (Dopex) on the other hand takes a different approach. They price their options through BSMM, but with unique differences between highly liquid and less liquid assets. For highly liquid assets, Dopex uses volatility smiles from IV oracles. The IV taken from the weighted average (weighted proportionately to the liquidity at various centralized exchanges like FTX, Deribit etc.) of these smiles is plugged into BSMM and the option premium is calculated. For less liquid assets, the IV is calculated as a 30-day rolling average of the realized volatility (actual volatility) of the asset, but the same BSMM is used for the premium as well.

“Unlike protocols making use of flat IVs and black-scholes pricing which usually results in incorrect pricing across strikes and expiries especially farther out of the money, dopex uses a combination of RV (realized volatility), a volatility smile replicating formula and “delegates” who quote on multipliers that influence the steepness/dampness of curves formed by the pricing formula. This allows for the dopex option chain to be far more realistic and fair in terms of pricing.

Delegates are incentivized to quote fair pricing to gain more liquidity and usage of the platform to receive higher incentives such as pool rewards and platform fees. They are also penalized incase of inactivity and/or malicious/incorrect reporting. So who are these delegates? To begin with we handpicked 5 of the largest derivative trading firms in the crypto space to be dopex delegates since they have the expertise, knowledge, data and resources to provide accurate fair pricing for all dopex option chains.” — TzTok-Chad (Dopex’s Founder on Twitter)

Analysis:

But what happens when any of these major exchanges or delegates face a problem? Surely they get penalized, but what about the LPs and option buyers on the other end? Can’t that result in major arbitrage and frontrunning? Also, unlike other major protocols, Dopex doesn’t actively price in the effects of large trades on premiums. Wouldn’t that result in a fragmented liquidity problem?

The protocol also plans to use a loss-rebate token (rDPX) for option writers. It’s ‘little complicated’ value-accrual mechanism is inspired from SNX, LUNA, OHM, DPX, and LQTY. Unfortunately, the price-action doesn’t substantiate the claims to the said mechanism. There’s definitely a need to make it more sustainable so that the writers are fairly incentivized.

Though pricing less liquid assets using ‘realized volatility’ sounds like a good approach, it exposes them to arbitrage through front-running during periods of high volatility.

RYSK

Rysk is a protocol that uses options in order to provide LPs with returns that are diversified, adjusted for risk, and uncorrelated (diversified portfolio). The protocol does this by continually buying and selling option positions in order to achieve a delta-neutral state. Rysk claims to protect their writers from volatility risk in the market, and allow for option buyers to find cheaper options than on other on-chain exchanges.

Options that would make the returns of a liquidity pool more uncorrelated — will be made cheaper. It incentivizes buyers to purchase these options, and vice versa. Option buyers can use arbitrage and benefit from cheaper options because of Rysk’s pricing adjustments. LPs provide collateral for options to be minted. They invest in Rysk for the uncorrelated returns so as to protect their investment from excess volatility and sharp changes in value.

Rysk prices option positions through BSMM with its IV skewed manually (based on market data and pushed to contracts, later to be done by an oracle), which is then adjusted to incentivize options in a way that will provide uncorrelated returns to LPs.

Analysis:

As we don’t have much information on how this IV skew will be dealt with, therefore we can’t comment anything here. But going through description on their mechanics, it’s clear that the protocol will be selling as well as buying option positions very frequently. First of all this creates a huge ‘gas-fee’ problem which impacts the sustainability of their portfolio management. Also, as protocol is still in its development phase, and we don’t have much information on how do they plan to tackle the problem of fat-tailed risks, vega-risk, IV arbitrage, toxic order flows, adjustments for RFIR and dividends, etc.

Further, Rysk has embraced the idea of arbitrage in DeFi, and fits it within the exchange. However, a big problem arises in the manual skew of IVs. There isn’t an automated way to skew the IV, and it could be adjusted later than needed during periods of high volatility, once again opening the doors to front-runners and trading bots.

GRAPHIC SUMMARY:

Conclusions:

The Black Scholes Merton model, which is very sophisticated, does not seem very suitable to price on-chain options. In fact, valuation models like BSMM are not designed to ensure accurate price discovery; they are better suited for ‘valuation’ purposes. Using BSMM ‘as it is’ to price on-chain options can give rise to severe problems such as arbitrage through front running, mispricing due to volatility smiles and skews, and overpricing due to other apparent or non-apparent costs.

Although some of the protocols have been successful in mitigating these problems to an extent, they either willfully or hopelessly ignore other problems. For example, all on-chain option protocols take RFIR as 0, which can lead to major consequences, as described here. Similar minor estimation errors in volatility can also drastically impact model outputs. Furthermore, we don’t see any adjustments made to factor-in the impact of dividends or additional costs (gas fee, borrowing interest, fee to get margin, fee for insurance, fee to adjust liabilities, etc.), which impacts the market spread. When you have to adjust for every other assumption and its side effects, it results in disincentivization of liquidity.

When it comes to TVL, we see only Premia (an American-style options protocol) has been able to retain significant liquidity out of four functional option protocols using BSMM. This is surprising because BSMM was only originally created to price European-style options. Is this a comment on protocol’s pricing mechanism? Well we don’t have any evidences! However, it would be worth investigating the reasons behind this phenomenon.

Now, let’s talk about an issue which doesn’t really exist at a protocol’s level, but is definitely due to these protocols: the problem of toxic order flows. Toxic flow originates when a market participant can be said to have an edge or an unfair advantage in the market which isn’t factored in by the system(s). Due to different pricing/mathematical models deployed by each protocol, there’s definitely a possibility of someone figuring out the best possible inter-protocol strategy/model to carve out the best returns. Our previous discussions show how on-chain option protocols are green fields for such toxic order flows. To fix this issue, there needs to be greater synchronization among these protocols despite their differences.

Crypto’s volatility has a centralization problem. Because on-chain exchanges are highly illiquid, every protocol has to source its IV from off-chain centralized sources. This means that too much of the volatility is dependent on exchanges like Deribit. If there is a major issue with one of these exchanges, it could have a significant impact on the market. In addition, blockchain scientists should focus on creating ‘pure’ on-chain volatility. Ribbon Finance’s RVOL can be taken as one of the examples.

In conclusion, it is unclear whether all of the changes made to BSMM are sufficient or if more need to be done. If further adjustments are needed, is it worth making all of those changes? Wouldn’t it be better to find a solution that is more compatible with decentralized ledger infrastructure?

Credits

Research and Writing: 0xlol and Akhil Vajjhala

Art Works: Darshan (Illustration), 0xlol (Conceptualization)

Technical Advice:

• Individuals: Thogard
• Teams: Rysk Finance, Premia Finance, Siren, Dopex, Lyra Finance

Quant Analysis: Eshana, Baldwin, Ishank

So, let’s suppose, you are an aspiring options buildoor. You are excited about your hand-crafted option contracts trading on the blockchain one day. But you don’t know how to price your DeFi options. What do you do? You go ahead and look for some popular pricing mechanisms. One fine day, under an apple tree, in a garden full of butterflies and velvet flowers, you come across the Black Scholes Merton Model, which immediately sends you in a state of epiphany. You are excited about using a valuation model for on-chain price discovery! Epiphany fades, and the realization hits. Realization of it not being perfect for DeFi, and the blockchain infrastructure. Realization that the model’s assumptions are not in line with the blockchain’s intricacies. What adjustments do you gotta make now? Through this article, we 0xlol and Akhil Vajjhala try to investigate the appropriateness of the Black Scholes Merton model (crafted for ancient traditional financial markets) in the context of decentralized finance (built on advanced blockchain technology). You can connect with us on twitter at 0xlol and Akhil.

Before getting started, if you would like a quick review of on-chain or DeFi Options ecosystem, you can read our research article here.

TLDR

• Black Scholes Merton Model is based on principle of dynamic replication. It is used to price option contracts which’s underlying asset doesn’t pay dividends and has the constant level of volatility during the lifetime of the option.
• Several assumptions undertaken by this model makes it (the standard version) unsuitable to price DeFi options.
• Crypto assets exhibit skewed distribution when it comes to their risk-premiums, contrary to ‘Gaussian distribution’ assumption of the model.
• This skewed distribution along with oracle’s latency can result in front-running opportunities which cause major harm to LPs.
• Volatility fractals are also a major factor in determining the option premiums.

Black-Scholes-Merton Model

If you are aware of Black Scholes’ intricacies, then you can skip this section on model’s description, and start directly from the next section “The Fault in Our Assumptions”.

The Black–Scholes–Merton model (BSMM) was published in 1973 by Fischer Black, Myron Scholes, and Robert Merton. It is a mathematical valuation model through which derivatives are priced in financial markets. The Black–Scholes formula theoretically estimates the price of European-style options on a stock that doesn’t pay any dividends (during the lifetime of that option). It is widely acknowledged to be amongst the most important mathematical formulae, alongside Newton’s second law and the Pythagorean theorem.

What’s the Purpose?

The BSMM’s core principle is “dynamic replication”. This means that, for a given option, you would form a portfolio of risky and risk-free assets (ex. A US Treasury Bond, Cash, etc.) to hedge the risk of the option expiring out of the money. Lily Francus explains this in a more intuitive fashion here:

Black-Scholes, like most derivative pricing, is built on the idea of portfolio replication — given no actor preference, the price of a derivative should be equivalent to the cost of replicating a portfolio (uncreatively called the replicating portfolio) that, over the lifetime of the derivative contract, provides identical cash flows. Identical is doing heavy lifting in that sentence. In practice, very few contracts have a true perfect static (meaning, after t=0, no further buying or selling is needed to hedge during the contract’s lifetime) or even dynamic (further buying/selling/rebalancing) hedge.

Portfolios and options must have the same valuation because their cash-flows are identical. A portfolio would be managed by dynamically rebalancing the weights of the assets without any cash entering or exiting the portfolio — an entirely self-financing portfolio. The main reason for creating such a portfolio is to conserve capital value over time against factors like opportunity cost and inflation. This becomes clearer when we try to understand the intuition behind the Black-Scholes equation.

The Intuition:

The intuition behind this equation can be thought of as — how much should one pay (option premium) for the option contract such that the overall investment would cause you to break even? And to break even, it’s necessary that the contract expires in the money (ITM) at a minimum value equal to the sum of strike price and premium paid (price at which this contract was bought) for it.

To put it simply:

• You can break even when: Spot Price at Expiry = Strike Price + Option Premium. Therefore, Option Premium = Spot Price at Expiry — Strike Price
• You earn profit when: Spot Price at Expiry > Strike Price + Option Premium
• You are in a loss when: Spot Price at Expiry < Strike Price + Option Premium

Option expiring at-the-money (ATM) would still keep the investor in losses as expenses/costs (option premium) weren’t recovered.

Now that we’ve understood this intuitively, let’s try to understand the two terms in the equation.

The first term of the Black-Scholes equation (“N(d1)St”) describes the projected price of the underlying asset at expiry. In other words, it tells us what price the market expects the underlying asset to reach at the time of the option’s expiry. This essentially tells us about the probability of how far ITM can the option expire. The farther ITM the option expires, greater will be the revenue, and hence greater will be returns or profit generated from it.

The term “N(d2)Ke^-rt” tells us about the cost of exercising an option contract. This cost is only incurred when the option is exercised, so the option needs to be ITM in order for this fee to be paid out. “N(d2)” represents the probability that the option will be ITM, while “Ke^-rt” is the present value of the strike price. This present value is calculated by discounting the strike price (K) by risk free interest rate (r), or RFIR, through the discount formula (e-rt). The price is discounted for RFIR to factor in what is known as the opportunity cost for not investing this capital in a completely risk-free instrument. In other words, it’s the rate of return you could generate without any risk on certain risk-free assets in financial markets.

Essentially, the BSMM formula can be written like this:

Option Premium = Expected Revenue from Exercising the Option — Expected Cost of Exercising the Option

Another way of looking at this equation is by saying that it models the price of an option over time as a sum of the ‘price of underlying asset’ and the ‘risk-premium’. This risk premium is basically the rate of returns (ROR) in excess of RFIRs, and can be considered as the ‘cost’ one pays to the market to hold/bear a risky asset.

Now as we are aware of intricacies involved in BSMM, it will now be easier to investigate all the factors (model’s assumptions) which can determine the compatibility of this model with the decentralized ledgers.

The Fault in Our S̵t̵a̵r̵s̵ Assumptions

BSMM, just like any other mathematical model, takes into account several assumptions:

• Option contract is European-style.
• No transaction costs or taxes are involved in the construction of the dynamic replication portfolio.
• The portfolio involves a risky as well as a risk-free asset.
• A constant RFIR to discount the strike price for the present.
• The probability distribution is Gaussian (normal).
• The volatility of the underlying asset is a constant function.
• The underlying asset pays no dividends during the lifetime of the option.
• There are no arbitrage opportunities in the system.

The accuracy of BSMM’s output depends on these assumptions, so to determine the accuracy of BSMM, these assumptions need to be thoroughly tested!

Specificity and Transaction Costs:

The aforementioned portfolio requires a consistent re-balancing of the risk-free and risky assets, and it should be able to do so at no additional costs (otherwise the portfolio cannot be truly self-financing). What if we create a similar portfolio on the blockchain?

In DeFi, most option positions are fully collateralized. To rebalance such a portfolio, you would need to pay charges to borrow collateral (apart from gas fee) as well as carry out other trades. Such costs result in a wider spread. So not only do such costs impact the pricing accuracy, but they also make the market less liquid and price the options higher than usual. Until someone figures out a way to have a portfolio margin system for the blockchain, this problem shall be a major determining factor in option pricing.

Also, BSMM assumes options to be of European-style (contracts which can be exercised only at expiry). You definitely can’t use it as it is to price American-style options (contracts that can be exercised before expiration). In 2nd part of this series, we will see how some protocols have been using a modified version of BSMM to price American-style options.

Risk-Free Interest Rates:

BSMM uses a constant RFIR to discount the strike price when calculating the option premium. This is because the model is derived from the replicating portfolio, which requires a constant interest rate for the accurate calculation of value.

In traditional finance, risk-free assets (bonds, bills, and notes) are guaranteed by sovereign governments. The rate of return on such assets over a particular period of time (depending on the maturity) is RFIR. So, this is what you can earn without taking any risks.

Investors use RFIR to estimate the risk-reward ratio for investment and decide whether or not it’s worth taking on extra risk for a potential return.

Unlike in traditional finance (TradFi), where money printing agencies provide guarantees, in DeFi, the only law is the code written into smart contracts. This begs the question: can we truly have risk-free assets in DeFi? Stablecoins (crypto assets pegged to USD or overcollateralized by other crypto assets) offer partial solutions, as interest earned on these stablecoins from money markets like Aave can be considered risk-free. However, given the various risks associated with stablecoins, this RFIR shall not be ‘risk-free’ totally. Similarly, the conventional RFIR from TradFi can’t be considered completely risk free. So, to each their own!

One can still use the return on US treasury bonds as the RFIR in DeFi. This is because on-chain options are largely measured in dollar value, and thus we can use dollar-value risk-free assets.

Dividends:

BSMM’s assumption that no dividends are paid out during the lifetime of an option doesn’t make sense in light of reality (with DeFi as well as with TradFi). They are very common, and sometimes the primary reason investors hold a particular security. This determinism in asset prices caused by dividends goes against the assumption of BSMM that price fluctuations are completely random (‘normal’ or ‘Gaussian’ probability distribution can only be achieved when price fluctuations are completely random). Such determinism (predictable price action) results in variable volatility, which is another contrast to BSMM’s assumption of constant volatility. Since we can’t assume that no option contracts are active when dividends are paid out, BSMM’s output could be significantly affected by them at any point during an option’s life.

Probability Distributions and Volatility:

Now, what problems can assumptions on ‘distribution being Gaussian’ and ‘constant level of volatility’ create?

Skewed Distributions:

BSMM was based on Bachelier’s assumption that stock returns are normally distributed. The model further went on to take from Paul Samuelson’s conclusions (1950s) that stock prices follow a Geometric Brownian Motion (GBM) with constant drift and level of volatility, i.e. a ‘random walk’ with drift (a positive drift causes an upward trend and vice versa) where the movements of the stock market were a Markov process, i.e. the next state of a stock price (up, down, or same) was entirely probabilistic and could not be predicted.

BSMM works on the assumption that an asset’s risk premium is necessarily normally distributed. To validate this assumption, we plotted probability distributions as well as quantile-quantile or q-q plots for the RORs on BTC and ETH taking into consideration different time intervals (RFIR isn’t accounted for simplicity in calculations).

As you can see in the graphs above, the data isn’t normally distributed at all, especially when you take shorter time intervals (anything less than 1 month?) into consideration. This is mainly due to the fact that crypto is highly speculative and narrative-driven. Factors like token unlocks, change in issuance, dividends, fluctuating APY, etc. result in abnormal volatility in shorter time frames. And even if the distribution seems to approach a Gaussian distribution at larger time intervals (ex. 3 months), it is skewed and has fat tails. So, essentially feeding skewed data with excess kurtosis to a model like BSMM can prove to be dangerous for all the agents involved in the options ecosystem.

The data is said to be skewed when it’s not evenly distributed and has a longer tail on either side of the distribution. Skew results in asymmetrical distribution (skewness) with a higher probability of witnessing outliers or extreme events (kurtosis). Kurtosis refers to the peakedness of a distribution. When looking at the RORs at shorter time intervals, cryptocurrencies tend to exhibit excess kurtosis, which means that they have more pronounced tails than a normal distribution. This indicates a greater likelihood of outliers or extreme events.

Volatility Not Really A Constant Function:

Now let’s elaborate upon the model’s assumption of volatility being a constant function. As already discussed, the volatility of an underlying asset will continue to change over the lifetime of an option. Over a week’s time, the asset could shift from being quite stable to completely erratic owing to a variety of factors — narratives, supply-demand, interest rates, etc.

There are two types of volatility: historical and implied. Historical volatility is a measure of how much an asset’s price has fluctuated in the past. Implied volatility (IV) on the other hand is a measure of how much an asset’s price is expected to fluctuate in the future. It is a measure of the market’s expectation of the asset’s future volatility and is derived from the prices of the options. The higher the IV, the higher the expected volatility of the instrument. IV is a forward-looking measure of volatility and is affected by a number of factors, including the underlying instrument’s price, the strike price of the options, the time to expiration, the interest rate, and the dividend yield.

But, how does this assumption of a constant level of volatility create problems, especially for on-chain options? First of all, IV is derived from the Black Scholes formula by back-solving it for the value of volatility, using the market price of an at-the-money option as an input. As this IV is calculated by BSMM which assumes a constant level of volatility (which is wrong as described before) the IV i.e. predicted volatility calculated is most probably wrong.

Even after making adjustments to account for certain flawed assumptions (presence of transaction costs, dynamic interest rates for risk-free assets, and dividend payouts), the model still doesn’t seem suitable or efficient enough to price on-chain options. This necessitates either DeFi-specific amendments or an entirely new model. To make DeFi specific adjustments, we must first understand that the flawed factors discussed before don’t work in isolation, but in sync.

One of the ways to study this ‘sync’ is by understanding the fractals witnessed in volatility or IV when the options are actually trading in a free market.

Into the Dark Allies of Implied Volatility

Even though we get to see a variety of adjustments made to BSMM by different DeFi protocols (in part 2), major emphasis has been on adjusting for fractals associated with IV. Let’s try to understand such patterns or fractals:

The Smiling Chaos — Volatility Smiles

Every option position has an expiration date and a strike price. At different points in time before this expiry, the value of IV is observed to be different. It results into a phenomenon popularly known as ‘volatility smile’.

It has been observed that as we approach the strike price, IV falls, and vice versa. This is because when the underlying asset is trading at a price closer to the strike price, the probability of it being exercised increases. So more certainty = less chaos!

The typical ‘volatility smile’ pattern can be intuitively thought of resulting from the need for option buyers and writers to avoid extreme positions. Option buyers need to stay away from out-of-the-money (OTM) positions because they will lose the premiums they paid, while option writers need to stay away from ITM positions because they are dangerous to their collateral locked into option positions.

Chaos’ Asymmetry — Skew

It’s important to note that a free market will consist of multiple positions rather than a single position. Now let’s consider a set of options with same underlying and expiry, but different strike prices. Ideally, all the contracts in this set should have the same IV, since they are based on the same underlying asset. However, in reality, even if the underlying and expiries are same, we often see IVs differing according to the strike prices.

Considering the aforementioned set of options, at a given point of time, some of them might be closer to their strike prices (ATM), while others might be OTM or ITM. And this proximity or extremity of option contracts to their strike prices will affect their IV (as explained before). The difference in IVs of these contracts is called skew. It describes the asymmetry (skewness) as well as the existence of outliers in the data (kurtosis). A positive skew indicates positive skewness, and vice versa.

Skew also impacts the price of options. For example, suppose investors in the market are bullish on $ETH, and expect prices to go up. In that case, call-option contracts of $ETH with the same expiry but different strike prices will exhibit positive skew. This means that IV for contracts with lower strike prices will be much higher than those with higher strikes. And as IV impacts option premium, contracts with lower strikes (OTM positions w.r.t a standard system) will be much expensive than contracts with higher strikes (ATM or ITM positions w.r.t a standard system). Intuitively — this is because the options with lower strike prices will get them a higher yield than the options with higher-strike prices.

On the other hand, if investors’ sentiments are bearish, to maximize their yields, they would prefer to sell call options with lower strikes as compared to that of higher strikes. This would result into negative skew for call options.

As we are clear on how skewness impacts option prices, its very easy to understand the impact of kurtosis on option prices. Any asset (and therefore the position) attains high kurtosis due to heightened volatility. Extreme and abnormal volatility result into chaos. And hence, such position will most probably be priced higher given to the risk-reward ratio associated with it.

The Disaster

These IV fractals clubbed with a blockchain’s (or oracle’s) latency is enough to bring on the disaster! But how?

The disaster is brought forth as the crypto clouds start rumbling by the sudden sparks of volatility. This volatility or price change is updated on the blockchain by oracles. Unfortunately due to latency, oracles update these changes later (maybe by a few milliseconds?). This time lag brings about a perfect opportunity for front-running bots to attack those option positions. These bots front-run you by arbitraging on this forthcoming fluctuation in the IV. So till the time blockchain is updated with the correct metrics, your on-chain option traders are probably rekt! This tells you why it is so difficult to incentivize liquidity for on-chain options. Also, this process tells us why BSMM’s assumption of ‘no arbitrage’ doesn’t hold much substance here.

Towards Part -2

Read Part -2 here

The Black Scholes Merton model, which is very sophisticated, does not seem very suitable to price on-chain options. In fact, valuation models like BSMM are not designed to ensure accurate price discovery; they are better suited for ‘valuation’ purposes. Using BSMM ‘as it is’ to price on-chain options can give rise to severe problems such as arbitrage through front running, mispricing due to volatility smiles and skews, and overpricing due to other apparent or non-apparent costs.

When accounting for impact on option prices, ‘skewed distribution’ as a factor is pretty apparent, but other factors like RFIR, dividends, etc. are also important, and shouldn’t be ‘approximated’. It can lead to further complications as described in this research paper.

In next week’s release, we will investigate the various ways option builders are accommodating the faulty assumptions of BSMM. By reviewing their pricing mechanisms in detail, we will try to evaluate different environments in which this mathematical model is being put to work. Can the option builders make everything alright, or are the flaws impossible to fix?

Credits

Research and Writing: 0xlol and Akhil Vajjhala

Art Works: Darshan (Illustration), 0xlol (Conceptualization)

Technical Advice:

• Individuals: Thogard
• Teams: Rysk Finance, Premia Finance, Siren, Dopex, Lyra Finance

Quant Analysis: Eshana, Baldwin, Ishank

Power corrupts; absolute power corrupts absolutely. This adage holds true in politics, but what about in a decentralized, trustless financial system? Can dominating powers use their influence for good, or are they destined to fall from grace like so many past leaders? This research article by Jack McCarthy attempts to see if smart contracts and DAOs can be the secret weapon needed to fight against corrupted despots.

The one exception to the absolute power sterotype is that of a “Benevolent Dictator.” Throughout history these leaders have wielded absolute political power, yet ruled for the benefit of the population as a whole. These rulers, while autocratic, tend to produce economic and cultural prosperity. Take for example, Lee Kuan Yew, who along with the People’s Action Party ruled over Singapore from 1959 until 1990. Following the Island’s independence in 1965, under Yew the country rapidly grew from an agrarian society into one of the 4 Asian Tigers and now has the second highest GDP per capita in the world.

The Country

So what country does the benevolent dictator rule in this story? Dystopia Swap. A ve(3,3) decentralized exchange (dex) that improves upon all of Solidly’s downfalls. Different from other ve-dexes like Curve, Dystopia offers swaps for both stable and volatile token pairs. Meaning in one place, you can provide FRAX-WETH in a Uniswap v2 style AMM and DAI-USDC in Curve v2 style AMM.

Dystopia aims to incentivize trading fees rather than liquidity with the ve(3,3) model. Liquidity providers (LPs) receive $DYST token emissions as incentives and veDYST stakers receive trading fees for the pools they vote to direct emissions to. This creates a flywheel effect where the pools with the highest trading volumes receive the most votes, thus incentivizing LPs to deposit into these pools for the rewards. Increased deposits makes the best trading experience for users since they experience low slippage.

In just over three weeks since emissions began, Dystopia has seen a peak of $28M TVL flow in (now at $14M), over $1M in trading volume each day, all while offering over 20% APY on popular stablecoin pairs. Expect to see the daily volume jump rapidly in the very short future, as integrations with dex aggregators such as 1inch and Paraswap have just been completed in the past two days.

Now if Dystopia is the country in this case, we still need a benevolent dictator to complete the story. Rather than subverting the existing power structures to assume its power, this Dictator was bestowed the right to rule from its loyal allies.

It all begins with Dystopia’s initial token distribution, which gave 100% of the initial token distribution to powerful allies in the form of 4 year locked veNFTs. While these allies received 100% of the ammunition supply leading up to the war, their firepower will be depleted through $DYST emissions, ultimately getting diluted to just 20% of the total supply after 4 years based on emissions projections. (given 90% $DYST is staked)

First week with 100% supply in the Allies’ hands before emission:

• The Polygon Ecosystem DAO — 55%
• Genesis Liquidity Stablecoin Providers (FRAX & QiDAO — 20%
• 26 Polygon native dApps that qualified for Polygon Liquidity Mining 2.0–25%

By the end of 4 years the 20% distribution will be:

• The Polygon Ecosystem DAO — 11%
• Genesis Liquidity Stablecoin Providers (FRAX & QiDAO) — 4%
• 26 Polygon native dApps that qualified for Polygon Liquidity Mining 2.0–5%

So initially, each dApp received 0.96% of the total supply, which will eventually decrease to a minimum of 0.19% . This gave each Polygon dApp far more than the 0.2% threshold needed for whitelisting their native tokens for emissions eligibility at the beginning. Once whitelisted, these protocols can use their veNFTS to direct $DYST emissions to their liquidity pools at absolutely no cost to themselves.

More importantly, it gave the Polygon Ecosystem DAO 55% of the supply initially, until it reduces to 11% over time. A full 57x more voting power than any single dApp. Tyrannical? No. Extreme Power? Yes.

The Great Leader

Our story continues with our main character, the Polygon D(ictator)AO. So who is this mystery cabal? Currently, the Polygon Ecosystem DAO is run by a multisig of 6 doxxed DeFi leaders from Polygon, Aave, Frax, QiDao, and Dystopia. However, to further embrace being a community owned dex, the DAO will decentralize and be run by a Grants Committee voted upon by veDYST holders that will serve on 1 year cycles.

“With great power comes great responsibility” — Spiderman’s Uncle or something like that

While giving the DAO massive power, Dystopia ensured there were guard rails such that the DAO always acts in the best interest of the community and Dystopia users. The DAO must vote for the highest performing pools based on volume, which in turn generate the most trading fees. This guarantees that rewards will always flow to popular pools regardless of targeted bribes and/or how users and dApps vote.

More so, all the trading fees earned by the DAO will be used for grants within the Polygon DeFi ecosystem to support new native projects and builders. In this way, using Dystopia as Polygon’s main dex ensures future growth for the entirety of Polygon DeFi. It was specifically designed to act as a community based dex for users and projects alike. Initially, the DAO will hold 50% of the grant voting power and veDYST holders will have the remaining 50%. During these voting stages, the DAO will deposit the funds into LP positions in order to compound the yield and earn $DYST to increase its potential for generating grants.

The DAO is bestowed with significant power — major influence on voting for pool emissions and 50% voting majority on grant allocation — but is this a bad thing? No, by embracing the role of Benevolent Dictator, Dystopia is able to create a unique selling point that differentiates itself from other dexes. When deciding between what dex to use, if they both have the same swap fees and deep liquidity, the one that generates benefit for the entire DeFi ecosystem will be used. When deciding what dex to LP into, if they both have high performing pools with similar volumes, the dex that is guaranteed to distribute emissions from a benevolent dictator will be used. Through its veNFT allocation to the Polygon Ecosystem DAO, Dystopia is that uniquely positioned dex.

Other than the purposeful allocation to the DAO, Dystopia’s airdrop to the 26 polygon dApps ensured that each DAO received the same amount. Dictators and socialism, a match made in heaven (or maybe hell)! While throughout history this pairing has not been successful, in a world run by code rather than military might, the outcomes shall prove to be much different. In fact, this equal distribution is incredibly important for the effectiveness of the $DYST rewards as incentives.

One of the obvious benefits of an equal distribution is each protocol beginning with the same ability to draw in liquidity deposits for their respective token pools. Every protocol needs deep liquidity for seamless trading of its native tokens, and if one protocol dominates the control of emissions, then users are incentivized to deposit in only that single pool. This initial emissions equilibrium enables both newer and established protocols to have a fighting chance at utilizing Dystopia for their liquidity needs. Of course, projects and DAOs can provide their own liquidity to earn $DYST, or purchase more $DYST to increase their voting power, but beginning with an even playing field, then seeing how each project adapts will be an interesting social experiment that plays out.

Oligarchy vs Socialism?

Velodrome, another ve(3,3) dex that launched on Optimism after Dystopia’s release, similarly gave locked veNFTs to protocols on their chain, but opted for an unequal distribution. Velodrome decided to give each protocol a subjectively determined amount. This distribution style massively benefits the established blue-chip protocols that receive more of the initial distribution, while hurting the upcoming native projects that can drive new and unique innovations during this bear market.

Since Veldrome’s launch, Dystopia has maintained a stable TVL within the $15–25M range, all while enduring the worst bear market in recent times. Conversely, Velodrome saw a massive run up in TVL initially, peaking at just under $50M, but has since dropped below Dystopia on its down only trend.

Both Polygon ($MATIC) and Optimism’s ($OP) native tokens dropped by 38% and 41% respectively since June 10th, when the market began to crash. $WMATIC makes up 9.92% of Dystopia’s TVL, while $OP makes up 5.99% of Velodrome’s TVL, meaning that the recent drop in native token prices cannot explain this massive performance gap. Rather, three more nuanced differences stick out to me as answers for why Dystopia has outperformed Velodrome: Emissions, Benevolent Dictator, and Yield Optimizers.

The preferable emissions schedule of Dystopia is a function of the amount of $DYST staked. A higher percent of the tokens staked leads to lower emissions, and thus dilutes $DYST holders slower. Velodrome opted instead for beginning with 15M $VELO in emissions (3.75% of initial supply), which then decay at a rate of 1% each week. The added incentive for $DYST holders to stake, in order to avoid dilution, comes with added benefits, such as boosted $DYST rewards for stakers who also provide liquidity. Velodrome lacks this extra flywheel effect for increasing liquidity, while Dytopia’s emissions are entirely designed around it.

Additionally, Velodrome lacks the community based connection that Dystopia so strongly clings to. Velodrome airdropped 60% of the $VELO supply to Optimism users, while Dystopia gave 55% of its supply to the Polygon DAO. The issue with airdropping to a handful of ecosystem users is that they have the potential to be parasitic and simply sell off the airdrop immediately. These users have no connection to the protocol and are oftentimes more than happy to cash out a free check. Dystopia, however, wanted the airdropped tokens to go to interested parties. While no Polygon users saw direct financial benefits from the large airdrop to the DAO, the Benevolent Dictator has agreed to permanently re-lock its veNFT for the maximum length of 4 years. This removes a massive portion of the available $DYST supply, keeping the price-action as healthy as possible for an emissions based project. Through the Benevolent Dictator role, the Polygon DAO indirectly incentivizes users to deposit liquidity and earn $DYST, knowing that the emissions will actually maintain value due to the permanently low supply.

The last competitive advantage lies in the protocols building on top of Dystopia. Penrose, a yield optimizer for Dystopia, plays the same role as Convex in the Curve ecosystem. Penrose allows users to deposit their $DYST for a liquid staked version of the asset, $penDYST. Penrose then locks this protocol-owned $DYST for the maximum 4 years. This ensures that users who stake their Dystopia LP positions on Penrose earn the maximum possible boosted $DYST rewards along with $PEN emissions on top. Velodrome’s design does not currently support yield optimizers, but users may demand this innovation in the future. For the meantime, the lack of yield optimizers prevents Velodrome users from utilizing the type of composability that the Dystopia ecosystem currently offers.

Looking forward 6 to 12 months, TVL and daily volumes can be surface level indicators to compare which distribution style was more effective, however an essential but often overlooked metric to look at will be the innovations that arise as a result of each dex.

Battle Tested

The veNFTs allow for projects to incentivize liquidity without having to dilute their own native token. Non-diluting emissions are a massive gift to these protocols, allowing them to test new ideas at zero cost. Take for example Curve, where DAOs and protocols had to either accumulate $CRV and/or $CVX or spend thousands of dollars in bribes to drive emissions to their pools for liquidity. Spending massive amounts of protocol owned liquidity to test out a new mechanism or product would be ludicrous for any project through Curve, but Dystopia provides this same mechanism for absolutely free.

So what innovations have we seen already in two weeks since the emissions began? VESQ, a reserve currency on Polygon, proposed a method for easily creating their own stablecoin by leveraging $DYST emissions. Simplifying the blog post, VESQ can issue bonds for its native $VSQ token in return for $MAI and $DAI. Following an even accumulation of both assets, VESQ would use half of the accumulated $MAI/$DAI to mint $vUSD, their new stablecoin. Since VESQ received a veNFT from Dystopia, it can use its voting power to not only whitelist and create a gauges for $vUSD/$DAI and $vUSD/$MAI, but also vote for $DYST rewards to go to the LP’s of the pools. With incentives in place, demand for $vUSD will be created, and VESQ can allow users to permissionlessly mint $vUSD up to a certain threshold. Hence, with 0 expenditure, VESQ can ensure that the users of $vUSD are compensated for their participation in the liquidity pools. This mechanism not only creates new value for $vUSD holders but also the $VSQ holders, showing how simple value creation through Dystopia can be for the 26 dApps that received veNFTs.

While we won’t see 25 more stable coins created through this mechanism, each protocol can leverage the $DYST emissions to reinforce its current model or try something brand new at zero cost. With an overarching Benevolent Dictator that supports the Polygon DeFi ecosystem by directing emissions to burgeoning and well-performing liquidity pools, alongside a socialist airdrop, Dystopia may provide the necessary roadmap for other chains to create community based decentralized exchanges. But don’t take our word for it, let’s let the innovation speak for itself.

Author, Jack McCarthy, is a Decentralized Finance (DeFi) Analyst at Polygon, highly interested in designing premier tokenomics designs and real world applications of DeFi. Also, he is currently the Co-President of Boston College Blockchain Club, while studying finance and business analytics at the Carroll School of Management. Feel free to reach out on twitter @offdeblockchain

Overcollateralized lending is a popular form of loan in crypto. It is a great option for individuals who need exposure to new assets without selling their current position. Here, a question arises: in a world plagued by income disparity, how does overcollateralization fulfill the very purpose of taking a loan? Besides the issue of issue of capital efficiency, overcollateralization prevents one from accessing cheap capital to achieve their financial goals. Meanwhile in a trustless financial system, undercollateralization is only going to make your liquidity providers poor. So what’s the solution? This research article is a collaborative effort of Jack and 0xlol for Polygon, who can be reached on twitter at Jack and 0xlol.

Humans have been involved in the lending-borrowing dynamic from time immemorial. Earliest examples can be traced back to 2000 BCE Mesopotamia, where farmers borrowed seeds and animals to generate agricultural yield. Such social dynamics introduced the complexity of trust and risk, but opened up the horizon for a quantum leap in economic growth. Those with wealth found a new mechanism for earning yield on their assets and those who lacked wealth gained the ability to borrow it and produce their own wealth. Simple, but nothing short of genius!

Leverage is the cornerstone of entrepreneurship and creation, allowing individuals to take on risk and develop new products and services. In fact, excluding the value of outstanding loans, the modern global lending market is currently valued between $7–8 trillion, based on the money made on interest by all private and public institutions.

Moreover, peer-to-peer lending — which DeFi aims to pair with institutional lending in order to kickstart exponential growth — is currently primed for rapid expansion. While institutions now have a firm grip on lending, enabling greater access to individual lenders through DeFi can help provide higher yields on one’s assets by eliminating the need for middle men. In fact, by 2025, the peer-to-peer lending market is expected to reach $1 trillion in value.

This rapidly changing environment is being eyed by many DeFi protocols. They gaze at an extremely profitable market, as our financial system has started rolling over to transparent ledgers i.e. blockchains. While DeFi presents an option for a decentralized and trustless financial future, undercollateralized (UC) lending is the current bottleneck in accelerating DeFi adoption.

TradFi or DeFi?

While traditional finance (TradFi) systems have abundant access to credit scores, KYC documents, and legal protections to recover funds, they suffer from various issues. The issues don’t stop there. Keeping your money with the traditional banks imply that you don’t have custody of your assets. There have been multiple instances where governments and banks have used these assets to bail out ‘friendly frauds.’ Following the 2008 mortgage crisis, major banks were bailed out by the US government, shifting the burden onto taxpayers.

Even with laws preventing race-based discrimination for loans, a 2019 report that examined two million US conventional mortgage applications found that black individuals were 80% more likely to have their applications rejected compared to financially comparable white applicants, largely due to biased algorithms. DeFi presents an opportunity in certain cases to reduce identity based discrimination from lending markets by relying entirely on smart contracts and on-chain identities.

Through governance systems majorly run by the stakeholders DeFi lending markets present a new era of possibilities in which only those who choose to deposit liquidity into the protocols can be on the hook for poor management of funds. It prevents mighty governments from thrusting tax burdens onto those who never participated in bad business practices, such as the sale of subprime loans. In TradFi, if you keep your money in a bank, you earn single-digit annual interest and have no control over whosoever the bank writes loans to. DeFi lets the lenders have a say in its administration, a true form of financial sovereignty!

Most importantly, 31% of adults world-wide are unbanked, while 91% of the world’s population has access to a smartphone. Requiring just an internet connection, DeFi can help unbanked and underserved communities access to previously unreachable financial services. If done correctly, UC loans can give such individuals financial leverage which can change their lives for good.

Beginnings of Lending in DeFi

Decentralized lending first began in its simplest form: overcollateralized lending. Many popular platforms such as AAVE, Compound and Maker pioneered this role, where users deposited their crypto assets as collateral and borrowed an amount that is less than the value of their deposit. Take for example DAI on AAVE, it has a max loan to value (LTV) ratio at 77%, meaning for every $100 deposited in DAI, a user can borrow up to $77 in assets.

On the other hand, UC lending can be either partially collateralized or totally uncollateralized. In a partially collateralized lending system, an individual deposits $x to borrow y($x) worth of assets (y > 1), while in an uncollateralized lending system one could borrow $z with no collateral at all. UC lending is also referred to as unsecured lending while overcollateralized lending is also called secured lending.

We analysed 7 such protocols w.r.t their risk assessment modules, lending mechanisms, total outstanding debt etc. Also, it should be noted that for this article, we aren’t considering flash loans or “one block liquidity” as UC loans. Before diving into the details, let’s first try to understand the different purposes these protocols serve:

Maple Finance, TrueFi, & Clearpool: UC lending protocols for Institutional Borrowers.

DebtDAO: Revolving line of credit for growth- stage DAOs and protocols taken out against future revenue. Offers a new way for DAOs and protocols to raise funds without diluting or releasing a native token.

Goldfinch Finance: Credit lines for real world businesses to exchange for fiat.

Gearbox: 0% funding rate for up to 4x leverage on whitelisted protocols.

Teller Finance: Marketplace for UC loans. It currently supports USDC for crypto backed mortgages in Texas, and for personal loans in Singapore up to $6,000.

Risk Assessment Methods

When dealing with UC loans in a financial sector based on anonymity and trustlessness, risk is the primary concern. Nobody wants to give a loan to a random twitter anon in the hopes of getting repaid while the borrower rides away into the sunset with a fresh lump of cash. So, what actually prevents someone from stealing away all the borrowed funds in real life, but not on-chain? Well, banks and other lending institutes most probably know their whereabouts, can impact their credit score, and cause a lot of legal as well as financial trouble.

Each on-chain protocol tackles this problem with their own custom risk assessment method. The varying methods for risk assessment exist due to the different purposes each protocol serves, such as varying targeted customer bases and levels of control over loaned funds.

Maple Finance, TrueFi, and Clearpool all have similar processes before the loan approval stage. First, each institution gets whitelisted by the individual protocol through an application process where they fill out KYC/KYB (know your customer/business) forms, provide financial documentation, and pass a protocol performed credit score assessment. The credit assessments slightly vary from protocol to protocol, but essentially analyze the business risk and reliability of the applicants. While the initial whitelisting stages are all quite similar in the loan application process, the differences between the institutional lending protocols occur in the specific loan approval process. These are discussed below, alongside the risk assessment methods used by non-institutional lending protocols.

Pool Delegation: Maple Finance, DebtDAO (Yet to Release)

Maple Finance and DebtDAO rely on professional credit analysts that stake the native governance tokens ($MPL and $DEBT) in order to assess and approve loans. However, Maple Finance allows the pool delegates to negotiate the terms of the loan with the borrowers, such as interest rate, date of maturity, and collateral ratios. DebtDAO risk analysts simply approve or deny the loan request that is given to them. It is non-negotiable. These pool delegates are rewarded for their work with portions of the interest earned from borrowers.

Community Vote: TrueFi

Similarly, TrueFi adopts a community voting layer atop the credit risk team. The credit risk team initially sets all the terms for each loan, but the borrower cannot simply accept these terms to receive funding. In order to be funded, the loan must be approved by individuals who stake the native token $TRU for the governance token $stkTRU. Each loan request requires an 80%+ approval rate in order to open the lending pool for deposits. The voting procedure essentially acts as a veto power for the community, given that only two loans have not met the approval threshold.

True risk assessment comes from the professional credit analyst team, but this community engagement allows for greater democratization of the protocol.

Third-party Outside Organization: Clearpool, Goldfinch

Clearpool Finance requires whitelisted institutions to stake at least 500,000 $CPOOL in order to be eligible for a credit assessment. This protocol mentions a different staking requirement. It requires the institution (borrower) to stake governance tokens, rather than the credit risk analyst. The staked amount acts as a sign of good faith from the borrower that outsourcing the credit analysis to its third-party partner, X-Margin, will be worth it. Following approval, the institution’s lending pool is open to receive funds.

Goldfinch also requires businesses to stake its native token, $GFI. Rather than a strict nominal amount, one needs to stake an amount of $GFI equal to 2x the cost of an audit. After which the protocol outsources the credit check of financial statements and identity legitimacy to its third party partners, Persona or Parallel Markets. After a successful audit, each business receives a non-transferable Unique Identity (UID) NFT linked to its specified wallet to avoid sybil attacks. Following the whitelist approval, a 20% threshold must be met in the first-loss capital pool. Then 6 out of 9 randomly selected auditors (individuals who stake $GFI for auditor voting rights) need to approve the loan for the borrower to access capital.

Predetermined Smart Contracts: Gearbox

Gearbox is a totally permissionless protocol that relies on its credit accounts. They are preset smart contracts for each pool type that bind together lenders and borrowers, curated by individuals known as credit managers. The credit accounts hold both the user’s deposited collateral and the borrowed funds. Borrowed funds can only be used in whitelisted protocols and/or swapped for specifically allowed tokens to avoid extreme volatility. Since users deposited funds can be liquidated by smart contracts at a determined risk level, there is no need for a credit assessment.

Though Gearbox might appear to be an interesting protocol, it is not the true form of UC lending that can enable loans for everyday life activities such as car loans and mortgages that TradFi currently has a choke-hold on.

Off-Chain Integration: Teller

Teller gets its own category since it’s not really in the same ballpark as the others. Teller creates standalone products for specific cases that act as marketplaces to connect borrowers and lenders. Such products can be accessed once the proposed borrowers have gone through Teller’s proprietary credit risk algorithms. In fact, USDC.homes on Polygon relies on Teller’s credit assessment before funding a loan from TrueFi. Teller’s algorithmic credit risk protocol computes credit and banking data off-chain privately and securely. It is used to generate individual loan terms for users that are routed on-chain. Inputs involve collateral provided, risk premium, loan-to-bank balance, loan-to-monthly net income, and loan-to-monthly income.

First-Loss Capital

While the risk assessment models provide the initial wall of protection for lenders in UC lending protocols, a ‘first-line of defense’ system offers LPs extra protection from loan defaults by using other stakeholders’ liquidity as the “first-loss capital.”

Stakers as First-loss: Maple Finance, TrueFi, Goldfinch

Maple Finance requires that pool delegates stake 8–12% of the pool’s loan balance as $MPL and $USDC in a 50:50 Balancer pool. In this way pool delegate incentives are aligned with LPs. Also, the funds can be easily liquidated for $USDC in the event of default. Aside from pool delegates, anyone can add to the reserve pool to increase the first line of defense to earn a share of 1/10th of the pool’s interest fees and $MPL rewards. Similarly, Goldfinch relies on backers, who evaluate the borrowers, as the first line of defense. Backers deposit into a “junior pool” for higher nominal interest rates, as they get a 20% share of the interest earned by general LPs in the “senior pool” for taking on the extra risk.

TrueFi relies on the participants who stake $TRU for $stkTRU for voting rights, $TRU emissions and protocol fees as the first line of defense. In the event of a default, up to 10% of $stkTRU may be liquidated to repay the loans. Importantly, there is a cooling down period for staking $stkTRU: it cannot be withdrawn immediately.

Insurance Pool as First Loss: Clearpool

In every block, a percentage of each pool’s interest is diverted to an insurance pool which acts as a claimant pool for LPs if the borrower defaults on the loan. The current governance vote has it set to 5% of a pool’s earned interest.

Spigot Function: DebtDAO

DebtDAO has developed a “spigot function,” which controls the borrower’s revenue generating contracts, and escrows a fixed percentage of the revenue while diverting the rest to the borrower’s treasury. In the case of a default, the spigot can claim the escrowed assets to help pay back interest and principal payments, acting as a debt collector. As arguably the only true form of debt collection in DeFi, this spigot function can be extrapolated for use in other protocols. Its only limitation is in its applicability to protocols and DAOs. If an individual is aware of spigot function claiming any funds sent to their wallet, they can create a new wallet to avoid the penalties.

Tokens Available for Loans and Pool Risk Variety

Aside from risk assessment methods, the types of tokens offered for loans is also an important differentiating factor. While individuals can use UniSwap to exchange the loaned assets for a preferred asset not offered by lending protocols, users may want to avoid facing slippage, transaction fees, and added smart contract risk. The aforementioned protocols offer the popular and dependable USDC, given that it is considered to be the safest stablecoin within the DeFi ecosystem. TrueFi offers UDT, BUSD, and TUSD in addition to USDC, while Maple offers USDC and WETH. Gearbox has the most variety, offering DAI, USDC, WETH, and WBTC for loans since they have the ability to restrict the use of funds to only whitelisted protocols.

Another added functionality of UC lending protocols is the offering of multiple lending pools for the same asset. A great advantage of having multiple pools of the same asset is the ability to have pools with varying levels of risk for liquidity providers. Maple Finance, Clearpool, and Goldfinch offer multiple pools per asset type based on the specified borrowers, while TrueFi, DebtDAO, and Gearbox offer just one single pool per asset type. For example, on Maple Finance users can deposit USDC into either Maven 11 Capital’s pool for 11.3% APY or Alameda Research’s pool for 10.5%, with the difference in APY being due to the delta in estimated risk determined for each institution.

Potential Limits for Undercollateralized Loans in DeFi

While all these on-chain UC lending concepts are exciting, and are pushing the entire DeFi space forward, it is important to discuss their potential drawbacks. First, scalability is a core tenet for the growth potential of such platforms. While the concept of pool managers work well for protocols like Maple Finance, these only succeed as they are limited to institutional borrowers. If such protocols plan to enable the retail’s participation, then the pool-delegation bandwidth required to review and assess borrowers will be enormous. TrueFi has a similar issue: It requires each loan request to pass a vote from $TRUE stakers. What happens when you open the gates to millions of retail borrowers? This is the reason why the loans are only available to institutions. While both protocols lack the design for massive scalability, Maple’s approach to using pool delegates is superior to TrueFi’s community voting mechanism, because it allows for more informed decision making. In reality, community voters with distributed responsibility won’t give the same attention to detail as a single person in charge of one pool.

Moving away from institutional borrowers, on-chain ‘algorithmically determined’ credit scores allow for ease of scalability to the masses, but are relatively weak at the moment due to the limited on-chain data availability. Also, on-chain credit scores, if not connected to a single real-world identity might be susceptible to sybil attacks. In context of an on-chain UC lending, a random individual can slowly build up good credit with a particular account only to borrow a large sum with no plans of paying it back. What happens when someone iterates this process through multiple wallet addresses? Individual’s KYC connected to a single wallet can help avert this disaster-in-the-making. However, for security and personal reasons, individuals often have multiple wallets with assets distributed amongst them. This essentially makes the concept of ‘KYC attached single wallets’ a limiting factor leading to gross inefficiency.

The off-chain credit integration system is relatively scalable and existing institutions seem interested, as Teller has had strong partnerships thus far. Within 1–2 years, one can expect to see people receiving loans on-chain without even realizing the presence of Teller in the back-end.

Additionally, individuals may not want their KYC details kept on-chain for privacy reasons, even if cryptographically encrypted. Along these lines, off-chain credit scores based on the lines of traditional finance not only go against the ethos of DeFi, but also introduce the risk of keeping KYC documents and personal information in a risky off-chain system.

What do the Numbers Say?

Most of the DeFi protocols today are compared based on their TVL. When it comes to lending protocols, it’s surely not the gospel’s truth. Lending protocols, specially those with UC loans usually have their capital’s net-flow outwards rather than inwards. At the same time, this capital should generate a regular income. To understand these aspects better, we take into consideration four different factors (apart from TVL) — total loans originated (TLO), total outstanding debt (TOD), net interest accrued from borrowers (NIA) and treasury or protocol’s revenue (TR).

For a lending protocol, it’s very necessary that capital from your lenders or LPs doesn’t sit idle. It should generate income. So, what do you do? You lend it out to those in the need. All this capital lent to borrowers, cumulatively accounts for protocol’s TLO. This amount is later paid back by borrowers with interest. Usually, a small part of this interest along with a ‘fee’ charged from different parties involved in the process goes to the protocol’s treasury. The rest is paid back to the lenders. The capital which hasn’t been repaid yet accounts for protocol’s TOD.

If we look at the data, it mostly goes in favor of Maple and TrueFi. When compared to the whole UC lending ecosystem through their TLO, NIA and TR, they seem to be establishing themselves as the leaders. They can also be said to have a first mover advantage in the institutional lending space. Goldfinch seems to be picking up the pace with around $120M in TLO, and around $3M and $0.7M in NIA and TR respectively.

Clearpool has effectively differentiated itself within the space by offering variable interest rates rather than the fixed interest rates of Maple and TrueFi. This important yet subtle change primes Clearpool for dominating an untouched sub-sect of undercollateralized lending. As a younger protocol in its growth phase, it is primed to realize its massive potential alongside the growth of crypto UC lending as a whole.

Also, data on all the aforementioned parameters for Teller couldn’t be found as it’s architecture is fundamentally different from other UC lending protocols.

An Optimistic Future

As DeFi continues to proliferate into the mainstream, on-chain credit scores paired with KYC or off-chain credit score integration (for ex. Teller) for retail investors shall push the migration of personal loans from an off-chain manipulated ecosystem to fair on-chain protocols.

More than just credit assessments, legal protections will be pivotal for creating trust between lenders and borrowers. Protocols like TrueFi which have legal agreements with their institutional borrowers shall be able to enforce the loans and recoup any defaults if necessary. Applying this framework to personal loans, on-chain signatures through protocols like EthSign can be implemented to further instill faith in retail UC lending.

While still nascent, on-chain UC lending protocols with their rapid rise and current success have laid solid foundations in this space. It opens up the doors for similar protocols looking to enter DeFi. One can expect further expansion of such concepts into untapped consumer bases. Each and every innovation in this space brings DeFi one step closer to flipping TradFi. Maybe one day, the fortress of Bastille shall fall!

Authors are DeFi Research Analysts at Polygon. 0xlol’s (twitter)interests include studying Attention Economy, Derivatives and Ethereum Scaling Solutions. While Jack’s (twitter) interests lies in accelerating the adoption of DeFi and NFTs in a sustainable manner.

As central banks sound the alarm against decentralized finance (DeFi) and its currency (stablecoins), a new David vs. Goliath battle is catching fire. While the former has the advantage of regulation, institutions, and government oversight, the latter has decentralization and a community built against the overreach of government. As central bank digital currencies (CBDCs) take economies by storm, can the DeFi survive? This article has been written in collaboration with Tommy La for Polygon, you can connect with us on twitter at Tommy La and 0xlol.

This article was originally published at https://medium.com by @0xlol on April 14, 2022.

In the Biblical story, champion fighter Goliath decimated the armies of Israel. His strength was unmatched, leaving only death in his wake. As he destroyed David’s homeland, David took the mantle to challenge him. Armed with the inferior weapons of a simple shepherd — a slingshot — but empowered by unique combat strategies, David killed the “invincible” Goliath. Often, David’s Biblical victory over Goliath is seen as an exception, an abnormality in a world where Goliaths always seem to win. In a society where the “little guy” always seems to lose, the tale of a shepherd whose five smooth stones topple a giant seems increasingly out of reach.

Today, a new ‘David vs. Goliath’ battle is emerging: the battle between DeFi (stablecoins) and central banks (CBDCs). As the widespread adoption of DeFi and stablecoins proliferates, governments throughout the world are taking notice. The elephant in the room, regulation, has quickly become the issue in the closer-than-it-appears side-view mirror. As central banks from China to the Bahamas float their ideas for CBDCs and begin implementation, Goliath’s sword is being drawn — and David’s slingshot pulled.

Before we dive into an analysis of CBDCs and their battle against DeFi, we must first understand what prompted central banks to adopt a digital currency. That answer lies in stablecoins.

When the DeFi architects on Ethereum envisioned a new financial system in the early 2010s, they settled on a core principle: the world of finance ought not to be beholden to the Goliaths. So, they developed fast, easy ways to send and receive payments on the blockchain while also using cryptocurrency as a store of value. Transactions occurred on blockchains, with many stable assets being minted. This is how the concept of “stablecoins” came into existence. Stablecoins are exactly what they sound like: cryptocurrencies that are designed to retain a specific value. From tracking the value of dollars to gold, stablecoins seek to ensure a predictable, stable currency that individuals can reliably transact with.

The world’s first stablecoin “BitUSD” was created in 2014 by two developers, Daniel Larimer and Charles Hoskinson. Launched in July 2014 on the BitShares blockchain, its goal was to use native BitShares tokens as backing for BitUSD tokens. But there was a problem. Without “tangible” assets to back BitUSD, how were users supposed to evaluate its worth? That’s where RealCoin (today known as Tether) came in. Through the acquisition of assets and fiat currency, RealCoin minted USDT tokens backed by real, tangible money. Today, USDT maintains a relative peg of 1 USDT: 1 USD, acquiring more than 50% of the stablecoin market share to date.

So, you’re probably wondering. Why can’t we just use a digital currency to transact with instead of using the blockchain? While electronic payment systems in traditional finance are on the rise, they are still expensive to purchase and maintain. When individuals transact, their credit card company, bank, transacting bank, merchant, and merchant bank all take a cut — leading to fees of up to 10%. All this while large corporations are able to aggregate — and sell — consumer data to third parties without their knowledge. Stablecoins on the blockchain solve all these problems.

Today, fiat-collateralized stablecoins take pointers from USDT’s legacy. Most are simple. When users deposit fiat currency, they are able to withdraw the same amount of stablecoins. This fiat currency is held by a centralized entity that controls the stablecoin until the user decides to withdraw their collateral. Decentralized applications like Maker accept a user’s fiat or cryptocurrency, which goes into a treasury or vault controlled by that application. The users can then mint a stablecoin pegged to the value of their deposit. These stablecoins, like USDC and BUSD, are considered the “safest” stablecoins and are now the backbone of DeFi.

‘Crypto-collateralized’ stablecoins on the other hand, allow stables to be backed by other cryptocurrencies like ETH and BTC. In these, an entity maintains a treasury or vault of cryptocurrencies while issuing their own stablecoins pegged to the assets within them. One such example is DAI, which is pegged to USD but also backed by crypto assets.

Algorithmic stablecoins have also been on the rise. Many protocols have begun using complex algorithms to maintain stablecoin pegs. For example, FRAX, a stablecoin protocol, doesn’t require the native stablecoin $FRAX to be 100% backed by collateral. It has got an ‘agnostic-deterministic-reflexive’ mechanism to regulate the peg where it makes no assumption about the market-demand of its stablecoin, nor the collateral-ratio the market is going to settle on. Often, these stablecoins have algorithms that are extremely efficient, only allowing for 2–3% fluctuations in price.

Increasingly, stablecoins have allowed market participants to move digital assets with lower fees and without regulation. Instead of moving money electronically through a system of banks like SWIFT, stablecoins on blockchains like Solana and Polygon allow for almost instantaneous, cheap transactions. On SWIFT, each transaction is required to be settled and verified by intermediaries. Most importantly, unlike bank transactions, stablecoin transactions on the blockchain are anonymous, barring any central entity from being able to track its users. Overall, the myriad uses of stablecoins have resulted in them becoming the center of thousands of dApps.

Stablecoins Have Witnessed a Significant Growth Probably as a Result of Trade in Cryptocurrencies in Last Few Years. Source: McKinsey & Company and IMF

With so many advantages, stablecoins’ abrupt rise has sounded the alarm at central banks. Without regulatory oversight and power over them, DeFi stables represent an existential threat to the banking system. Without the ability to track and exert influence over currencies, governments fear an “unstable” financial system arising. U.S. Senator Elizabeth Warren even dubbed it as “The Wild West of Finance.” And that’s why central banks are scrambling to create their own coins, i.e. so called CBDCs. Without an ability to control currencies, central banks will lose their power. As central banks race to combat DeFi, the battle between David and Goliath seems inevitable!

Source: McKinsey and Company

So, what are the Goliaths of the financial world creating to defeat the Davids and their stablecoins? Well, increasingly, central banks are almost exclusively developing CBDCs that don’t rely on a transparent-ledger technology at all. Instead, they’re developing proprietary technology that retains the status quo.

Functions to be carried out in a CBDC environment. Source: IMF

In order for CBDCs to work, a central bank must first create or issue the currency. The currency must then be validated by a network, guaranteeing its authenticity. Once created, a shared ledger or database of “who owns what” has to be updated to reflect the new currency created. All this while central banks continue to collect data on users to “ensure anti-money laundering” and “combat the financing of terrorism” via a policy of “Knowing your Customer.” So, the question here is — did terrorism and all those illicit activities start only after the invention of cryptocurrencies?

As we are now aware about the Goliath’s mischief, let’s look at what’s actually cooking? There are three main conceptual models that central banks have used to develop CBDCs: unilateral, intermediated, and synthetic CBDCs. Unilateral CBDCs are designed so that central banks unilaterally control currency. The central bank issues CBDCs, performs all transactions, and creates all infrastructure to interact with both merchants and consumers. In doing so, central banks maintain total control over their currencies. Another purported strategy for CBDCs is the creation of ‘intermediated CBDCs’. Similar to those created in the Bahamas and China, these intermediated CBDCs utilize a network of intermediate banks which are in charge of settling and executing transactions. All the central bank does is issue the CBDC. It’s these intermediaries — think your local Chase or Bank of America — that will continue doing all the transactions. The last strategy is the creation of Synthetic CBDCs. In this, non-central bank actors issue money that is backed by central bank assets acquired by central banks. Sound familiar? This is how reserve-backed stablecoins operate in DeFi!

Ultimately, every one of these systems have their pitfalls. Unilateral CBDCs deprioritize efficiency (as the transaction network is only as strong as the central bank’s systems) and resilience in favor of security and tracking capabilities. Intermediated CBDCs, on the other hand, simply route CBDC transactions through existing financial institutions (banks) who process and verify payments. This approach is similar to that currently done with credit card payments. In essence, this strategy is simply an extension of the status quo — governments print money, with banks creating networks to transact. While synthetic CBDCs look promising (as they would give consumers the choice of providers that prioritize different aspects of transacting) no central bank developing CBDCs has been reported to favor this technology.

Three Conceptual CBDC Operating Models. Source: IMF

So, it’s pretty clear now that CBDCs allow central banks to retain a significant amount of autonomy and control over their currencies. Most claim that their oversight will bolster safety and accountability for their users. Who are they trying to fool?

By far the most advanced of these is China’s Digital Yuan. Following the successful adoption of the Digital Yuan for millions in China (260 million active users), the Chinese central bank and Chinese Communist Party (CCP) are seeking to expand their CBDC to over a billion individuals by 2022. Today, people can access the digital yuan via an app on their smartphone and on platforms like Alipay and WeChat. The Digital Yuan makes it impossible for users to maintain anonymity in transacting. Big brother in China can see everything inside your wallet! While anonymity for small transactions is being proposed, the ability of the government to continue tracking users is inevitable.

Ultimately, the Chinese government’s authoritarian solution to David’s growing strength is to create a tool that makes him totally obsolete. Goliath seeks to use his sword to destroy everything David stands for in the process.

As one of only two fully-released retail CBDC projects, The Bahamas’ “Sand Dollar” CBDC has taken hold in the small island country. In PwC’s ranking of the top 10 retail CBDC initiatives across the world, the “Sand Dollar” took first place. However, instead of using a transparent ledger, The Bahamian central bank uses an Intermediated CBDC strategy similar to that of China’s.

While the central bank has claimed that the Sand Dollar has “built speed, efficiency, and security in payments,” it also claims to provide an excellent record of income and spending. While this is a great tool to track individuals’ credit (which has been touted to be used for application of revolutionary microloans in the country) the CBDC’s purpose is clear: to ensure the Bahamian central bank’s authority over transactions. For a nation that’s built a culture of throwing Goliath, the British Empire, off its back in the 1970s, it seems that its own central bank once again seeks to put a yoke on the back of its people.

Moreover, the same is true for Uruguay’s CBDC. Uruguay’s e-Peso is being widely used for peer-to-peer transactions in the Latin American country. However, each e-Peso includes a digital ID serial number, meaning that every transaction made using the e-Peso is being tracked by the government. Not only are individual transactions tracked, but so are the individuals who currently hold those specific bills. This means that individuals who haven’t been involved in illicit transactions, but simply have possession of specific bills in the electronic wallets, will likely be subject to regulatory scrutiny.

Overall, it seems like governments all over the world want to have greater control and surveillance over their people through central banks in the name of so-called efficient currency.

In order for CBDCs to have significant power over the status quo financial system, they need to provide tangible benefits to speed, efficiency, and safety. However, it seems as though most CBDCs are using the existing FinTech architecture. They are specifically using intermediate banks that are already responsible for our everyday transactions.

The Digital Yuan is not on the blockchain, it instead utilizes Chinese government-developed technology routed through existing financial institutions. The Chinese Digital Yuan system is built upon private-sector banks’ distribution and maintenance of the Digital Yuan, creating ledgers for each customer — and records of every transaction. While faster than traditional clearing systems, as Huang Qifan, the chairman of the China International Economic Exchange Center put it, “[The Digital Yuan] can achieve real-time collection of data related to money creation, bookkeeping.” In this system, CBDCs don’t provide anything revolutionary — they’re simply an extension to the status quo.

The Sand Dollar does the same. It uses existing financial institutions and banks to verify and hold digital currencies, giving them to account holders. Those who’d like to transact with the Sand Dollar need an official mobile app or physical payment card. Moreover, in order to decrease possible abilities for users to sell assets quickly, the Bahamas has created quantitative restrictions on the number and size of transactions with the Sand Dollar, just like existing credit limits in centralized finance. In the end, no CBDC implementation till now has shown an improvement over existing financial systems — largely because central banks likely don’t want it.

Design Features of CBDC Projects. Source: IMF

While few fully-fledged CBDCs have been rolled out, the majority of central banks in the world have plans to release them in the near future. That provides some hope to those wishing for better, more innovative architectures for CBDCs. From India to Japan, CBDCs are becoming inevitable.

Unfortunately, it seems that few central banks are willing to embrace DeFi’s spirit of decentralization and privacy. In what will be the largest nation in the world in the next two decades, India represents an enormous opportunity for blockchain technology. Yet, its CBDC is seemingly looking the other way.

As the former finance secretary of India wrote, “A dematerialised form of banknotes will serve as the best option instead of a blockchain cryptography-based digital currency. I think the RBI will find it very difficult to develop an appropriate design for the retail digital currency. India should do a pilot with dematerialised banknotes.” It seems he was right, as the Indian central bank announced it would design its own CBDC using proprietary, trackable technology — not a blockchain or synthetic CBDC technology.

On March 10, President Joe Biden signed an executive order to mandate the Treasury and Federal Reserve to begin urgent, government-wide focus on the research and development of potential American CBDCs. This order marks the first official presidential nod to a Fed-backed CBDC. With the order, now both the Federal Reserve and European Central Bank (ECB), arguably the two most influential central banks in the world, have announced plans to develop and research a CBDC. Yet, it still doesn’t look well for DeFi. The Goliaths of the ECB and the Fed have awoken and are ready to battle David.

As SEC Chairman Gary Gensler described in response to a question on stablecoins, he likens stables to “poker chips” in the “Wild West Crypto Casino.” The G7 also committed to endorsing 13 public policy principles for CBDCs, including adherence to central banks’ ability to track currencies. While ECB’s President Christine Lagarde may be more reserved in her sentiments, it seems that sweeping regulation and the introduction of centralized, trackable CBDCs is imminent.

While India, the EU, and the US seem to be antagonistic to stablecoins, the UK tells a different story. On April 4th, the UK’s Chancellor of the Exchequer Rishi Sunak released a comprehensive plan for the UK government to “make the UK a global cryptoasset technology hub,” promising to implement stablecoins as a legal form of payment. While the UK does plan to comprehensively regulate stablecoins, the country provides hope (and a roadmap) that other nations could follow.

So, why will people use CBDCs? That’s the million dollar question, isn’t it? The reality is that the proliferation of CBDCs will likely occur simply because powerful “Goliath” institutions want it to happen. And they certainly will try to lure you with ridiculous incentives.

In an IMF report, they found that prudently designed CBDCs will offer more resilience, more safety, greater availability, and lower costs than private forms of digital money. The Federal Reserve also released in a report that their potential CBDC could serve as a new foundation for the payment system globally, including identity verification to reduce crime,money laundering, and “balanced privacy protections.” Although CBDCs are touted to have myriad benefits, one problem still remains: CBDCs don’t hold true to the spirit of a decentralized economy. They in no way favor the rights of common people.

Stablecoin-based DeFi has the advantage that it can provide all of the above benefits while maintaining user privacy. DeFi protocols using stables are often backed by tangible U.S. dollars, representing a strategy of synthetic CBDCs. With the introduction of layer 2 blockchains, transaction speeds have rocketed while the gas fees have come down significantly. On the other hand, stablecoins on DeFi could also comply with anti-money laundering and crime regulations. Perhaps more protocols and watchdogs should be dedicated to tracking suspicious wallets or even ban/blacklist known illicit wallets.

Imagine a world where peer-to-peer transactions are seamless, free of government regulation, and enable complete freedom and transparency to users. That’s the world stablecoins and DeFi offer! Indeed, if central banks recognize this, there’s a possibility that both CDBCs and stablecoins can co-exist.

As bridges and vaults allow users to convert one asset to another on the blockchain, it’s possible that traditional DeFi infrastructure could incorporate CBDCs to become another stable currency for transactions. Users could deposit CBDCs into a vault or wallet on traditional central banks’ user infrastructure, which could then be minted into tokens on-chain alongside stablecoins. That would grant users access to so called security of CBDCs with the flexibility, yield, and *some* decentralization of DeFi and its decentralized apps (DApps).

The UK seems to be on this track. Their intent is to regulate stablecoins while also researching a CBDC. In future, perhaps you’ll see their citizens transact in CBDCs while financial institutions and individuals leverage the blockchain for its features and yield applications. While the utopian world of synonymous and commonplace DeFi may never take hold, it will still hold a large and out-sized role in the world of finance.

In the Biblical version of David and Goliath, Goliath doesn’t just dwarf, outmatch, outmuscle David. No, he brings the social order of the Philistines against David. “And the Philistine cursed David by his gods”. Like central banks, Goliath uses the existing social order as a weapon to detract from David’s strength. For when David plays by the rules of the status quo, David loses.

But even with the weight of traditional warfare bearing down upon him, David chooses to stick to his guns, his unorthodox fighting style. When David “hastened and ran out of the lines toward Philistine,” it was David’s difference and deviation from the “norm” that brought him victory. That’s what the Davids have to do to beat the Goliaths: play outside the normal rules. Yes, CBDCs have an unfair advantage against DeFi. With regulations, institutions, banks, and the apparent “world order” against DeFi, this truly is a battle of David vs. Goliath. But DeFi has made it this far without playing by Goliath’s rules! If David wants to win and survive the onslaught of regulation from Goliath, he needs to continue doing what would make him unique. The sacred principle of decentralization!

In the millions of battles between David and Goliath, David often wins.

1. CBDC and stablecoins: Early coexistence on an uncertain road
2. DeFi May Push Governments to Adopt CBDCs
3. G7 Finance Officials Endorse Principles for Central Bank Digital Currencies
4. CBDCs and DeFi: The Future of Stablecoins
5. The Future of Money: Gearing Up for Central Bank Digital Currency
6. Behind the Scenes of Central Bank Digital Currency
7. Money and Payments: The US Dollar in the Age of Digital Transformation

Authors are decentralised finance (DeFi) research analysts at Polygon. They can be reached on twitter at Tommy La and 0xlol.

Are Decentralized Derivative Markets the New Meta?

On-chain derivatives are a tough nut to build. From pricing mechanisms to assimilation of collateral in the engine — everything has to be done in a sophisticated manner to ensure liquidity in the system. The work doesn’t end at maintaining liquidity, you have to keep it from getting fragmented. Market sentiments go south, and that fragmented liquidity blows your system out of proportion into an absolute chaos! So what do you do as a protocol? You go ahead and lock it for the time being. But what about your liquidity providers? As an LP or an options writer, your time is running, and your capital keeps accruing an opportunity cost. There’s nowhere to go, your precious collateral is at the risk of those positions being exercised at in-the-money! But wait, this sounds confusing right? So how does one figure out a way through rabbit-hole of on-chain options? Before we move forward, you can connect with me on twitter at 👉 0xlol

Entering the Rabbit Hole…

Alright, let’s dive deeper into this rabbit hole, shall we? First up, we’ve got to talk options. You might be wondering, “What the heck are options, and should I even care?” Well, they’re a type of contract in the big, wild world of derivatives — think of these as bets on the future price of stuff. Essentially, these contracts are a way to get in on the action of an asset’s price movements without having to own the actual thing. You pay a small fee (a ‘premium’) to potentially rake in gains or shield yourself from losses depending on where the Bitcoin rollercoaster heads next. It’s like paying for a lottery ticket, hoping the number you bet on hits the jackpot.

But why would you throw your hat in the ring? In a nutshell, derivatives can be your best friend for making big moves on the cheap or your trusty umbrella in a downpour of financial uncertainty. They let you play the game without putting all your chips on the table. Looking at the bigger picture, though, derivatives are like the ocean: vast and deep. The total value of these financial deep-sea creatures hit over $600 trillion in the first half of 2021 alone. But when we zoom into the crypto universe, things are still heating up, with the market not yet breaking the $1T mark.

Let’s also not forget the thrill of the gamble that comes with the territory. Stashing your treasure in these digital chests can give you a shot at glory, but let’s be real — it’s a bit like walking a tightrope. There’s always the chance of taking a tumble. That’s where derivatives swing in like a superhero, offering a way to dodge those financial bullets. You can play it smart, aiming your bets in the right direction to shield your stash. But here’s the kicker — if things don’t go as planned, you might just see your premium vanish into thin air. It’s the ultimate balancing act, weighing the chance for epic wins against the risk of your safety net getting snipped.

Most of this action happens off the blockchain, in the realm of traditional exchanges. Think of places like Binance or Deribit, where the air is thick with trades. Yet, the frontier of on-chain derivatives is just beginning to blossom, especially the options scene. None of the protocols hosting on–chain options currently have a total value locked (TVL) on the upside of $1B. This doesn’t indicate the extent of traction they get, it just means that crafting scalable and stable on-chain options is a tough task. It’s a challenging puzzle to solve, making such options platforms that don’t buckle under pressure.

Before we try to dissect different on-chain option protocols, let’s first understand the dynamics of an option contract. Broadly, options can be of two types — ‘call’ and ‘put’. By paying a premium, call buyers have the ‘right’ to buy assets at a fixed price (strike price) in future and vice versa for put buyers. Option sellers, on the other hand, earn this premium by selling or writing the contract to option buyers. They have the ‘obligation’ to sell the underlying to the option buyer at strike price. This premium can be decided by a number of pricing mechanisms. It should be noted that standard option contracts have an expiration date, based on which they can be exercised in two different ways — either before expiration or at the time of expiration. American-style options are flexible and can be exercised before expiration as well as at the time of expiration, while European-style options, on the other hand, can only be exercised at expiration.

Below we see the standard graph for a ‘long call’. It clearly demonstrates how a ‘long call’ hedges your risk by capping your losses when the asset price keeps depreciating.

Now, as we have a little clarity on the structure of an ‘option contract’, lets try to understand their execution on a blockchain infrastructure.

For this research, we went through documents and whitepapers of more than 20 different on-chain option protocols (having complete or partial engine on-chain). As mentioned before, the execution of option contracts on-chain is a tough task. But what exactly makes it difficult? The answer is liquidity. For any financial market to function efficiently, it requires deep liquidity. In its absence, these protocols face sharp fluctuations resulting in chaos.

To understand this better, let’s try to understand the collateralization process involved in writing an option. Basically, an option writer puts up a unique amount of collateral in the engine to generate/draft the contract. As the position is unique — it makes it ‘non-fungible’. Hence, not everyone would want to buy that unique non-fungible position — making the ecosystem illiquid and fragmented with big fragments (as there will always be whales with huge positions). So, along with being illiquid, the ecosystem is now prone to risk large positions being exercised.

This problem of fragmented liquidity on the blockchain is being solved by ‘tokenization’ of positions on various ERC standards. A derivative on the top of a derivative! Since the ERC-20 standard provides space for fungibility, it can be seen as a popular choice among various protocols like Opium Network, Ribbon Finance, Opyn, Dopex, etc. Though this approach solves the problem by introducing fungibility — exercising large position sizes can still cause huge disturbance in the liquidity pools.

This problem can be solved by keeping the liquidity locked till expiration, which is the case for European-style options. When we look at the traction (through TVL and volume) — European-style options have been majorly successful, ex. Opyn, Ribbon, Dopex, etc. At the same time, some protocols like Friktion and Premia seem to be performing well with American style. Though they might have performed well with their novel mechanisms to conserve liquidity, their TVL is still less than that of many European-style ones. Below we see how Premia’s TVL reacts strongly to bad market conditions. With this kind of volatility, it becomes hard to maintain a steady state in the protocol.

On the other hand Hegic, an American-style option protocol tries to deal with the liquidity problem differently. Their hedge contracts distributes gains (premiums) as well as risk (capital loss if positions exercised at ITM) equally among all the LPs. Though this ‘diversification of risk’ might seem to go in its favor, TVL shows otherwise. TVL on Hegic has been in a downtrend since December ’20, and almost dead now.

Derivatives are risky, and are kind of tricky when it comes to capital loss. Most of the option-writers have to take this risk in order to earn the premium. We found that most of the protocols have certain in-built sophisticated mechanisms to avert the risk. Arrow Markets on Avalanche has a comprehensive system to deal with it through a dynamic collateralization mechanism for its insurance pools, whereas protocols like LYRA avert the risk by charging a higher fee to traders who bring a greater amount of liability with them. Base-primitives like Opium Network keep their losses capped through fixed margin mechanisms. While protocols like Opyn hedge any non-linear exposure (Uniswap LP) with a linear instrument (futures) and a quadratic instrument (SQUEETH).

Though all these protocols have dedicated risk-aversion tactics, Dopex has adopted a different approach. Thanks to its clever dual-token tokenomics it compensates the LPs or option writers for their loss using its rebate token ‘rDPX’. Additionally, it captures stable liquidity by rewarding LPs with its governance token ‘DPX’, which comes with other benefits like fee-accrual and discounted option purchases.

It should be noted that despite of all these risk-aversion mechanisms, they still carry some risks, which can be attributed to their architecture. Smart-contract risk being one the major problems here. Most of these protocols have administrator rights with their teams and aren’t decentralized enough. LYRA has been found with significant capital-loss risks in their audit, while Thetanuts has been found mispricing the orders in synthetic mining for certain vaults. In hybrid protocols like DERI, LPs realize profits at the expense of traders. Such vulnerabilities/faults are a big hindrance in mass adoption of option derivatives on the blockchain infrastructure.

Liquidity/Collateral Mechanisms/Risk Aversion to LPs

Since we already discussed the risks associated with the absence of deep and continuous liquidity for on-chain option protocols, let’s take an in-depth view of the mechanisms involved in ensuring an efficient flow of capital/collateral in their systems.

With base primitives like Opium, Katana and Opyn (GAMMA), liquidity is usually dependent on the products/apps made on top of them, but at the same time they have their unique in-built mechanisms. Though derivative recipe may decide the leverage flow in the apps built on Opium, the base-primitive layer allows swaps for existing positions. It discourages minting and burning of new tokens and encourages deeper-liquidity on the applications. Similarly, on Opyn (GAMMA) one can access features such as partial collateralization, wider spreads, and flash-minting of o-tokens to achieve capital-efficiency and deeper liquidity.

GAMMA has a very special feature where vault collateralization is checked only in the end of a transaction. Hence, option positions i.e. o-Tokens can be minted (flash minting) even without putting any collateral as long as they are burned before a transaction is concluded. Even partially collateralized o-Tokens can be generated and sold to buyers for a premium. This premium could then be used to compensate for the remaining collateral.

Through partial collateralization one can have greater control over their in-protocol liquidity, whereas through wider-spreads one can create put and call options to enable the collateralization of short o-Tokens (ERC 20) by long o-Tokens (ERC 20). Rysk, a protocol focused on delta-neutral strategies leverages features from Opyn’s Squeeth as well as GAMMA to effectively hedge and manage its collateral.

As we now have an idea about base primitives, let’s look at the collateral mechanisms involved in protocols with native engines for generating option positions. Some of the examples are Arrow Markets, Siren, Hegic, Friktion, Opyn Squeeth, Dopex, Premia, Shield, Pods, Deri, etc. Unlike base primitives, these protocols are directly exposed to market risk. Therefore, when it comes to collateral, in almost all such protocols we see some risk-aversion measures involved to hedge the flow and LP assets.

In Arrow markets, the collateral (primary pool) is hedged dynamically with an insurance component (insurance pool). Agents contributing to the liability of the pool are charged proportionately along with the aforementioned mechanism. It helps in controlling the cost of capital for the primary pool. Though the protocol hasn’t been deployed on main-net yet, theoretically this mechanism could hedge the risk to protocol’s liquidity pretty well. On the other hand, protocols like Siren avert risk to the system’s capital by providing structural flexibility to the components involved with the flow of collateral. Automated market maker (AMM) layer has been separated from the settlement layer along with a ‘diversification’ approach to LPs’ capital by distributing them among different markets.

Hegic, as described earlier, distributes the risk as well as gains among LPs. But as they are option writers, their capital accrue opportunity cost from being locked up. To compensate, hegic’s initial implementation allowed LPs to withdraw up to 20% of their capital from the liquidity pool anytime before expiration. But what happens when requested amount of capital isn’t available? Then they stand in a queue! Yeah literally, their requests are lined up in a queue, and are executed immediately whenever the liquidity is available. So, I don’t think this helps in making your protocol anymore efficient with its liquidity. Now, you know the reason behind a drastic fall in the TVL, right?

On the contrary, protocols like Friktion, Dopex and Deri avert risk to collateral in the system by restricting the in and out flow of the capital for a certain period of time. Apart from this feature, Dopex has laid an intelligent piece of infrastructure to manage and protect the collateral present in its system. LPs in Dopex act as ‘option writers’ where they retain the USD value of their capital if the asset price goes up, while their token value (for ex. ETH) is retained if the asset price goes down. It has single staking option vaults (SSOVs) where they (LPs) can deposit their collateral and earn a yield on it in the form of $DPX emissions, as well as the premium. If their collateral is lost (as a result of position expiring in-the-money), $rDPX emissions (equal to 25–30% of their loss) are released as a compensatory measure. In a recent update Dopex has introduced on-chain atlantic options to make the whole process more capital efficient. These are european-style options where the collateral deposited by the option-writer can be borrowed by a borrower for a funding-fee in exchange for an underlying token (ex. ETH) as a collateral. In this way, there is significant reduction in opportunity cost on writer’s collateral.

Similar mechanism of LPs being ‘option writers’ is followed by Siren and Hegic. Siren has a bilateral tokenization mechanism. Option writer mints two ERC-1155 tokens, buyer (b) and writer (w). They can then sell the b token to the option buyer for a premium. B token holder has the right to execute the contract at the strike price, while the writer with the w token earns a premium, as well as can withdraw the underlying after the expiration.

When we consider Opyn Squeeth (based on paradigm’s power perps), it attracts liquidity in the system by capping the downside for its derivative token. It allows users to long or short a special index like eth². Long squeeth (oSQTH) isn’t a leveraged position and hence by taking a long position it’s impossible to get liquidated. The only detrimental factor to your position is constant funding rates being paid by long-to-short squeethers. On the other hand you will definitely get liquidated if you are short squeeth (sSQU), though you can surely earn some funding by taking this risk!

Pricing Mechanisms

Option positions, minted by an isolated engine, are traded in a free-market. And hence there are a number of ways to decide their worth or price. One of them being the Black-Scholes (BS) also called the Black-Scholes-Merton model, which was found to be the most popular one in our review. This model tries to estimate the theoretical value of derivatives using five input variables — the strike price of an option, the current asset price (spot), the time to expiration, the risk-free rate, and the volatility. Standard BS model assumes that options could not be exercised before their expiration, and hence can only be used for european-style options.

If the research findings of the Potion Labs on BS are to be believed, then it poses significant risks to LPs. This model, given its underestimation of risk in highly-volatile markets like crypto was found to produce bankruptcy for major crypto assets. So, even though it’s considered the industry standard, there’s certainly no harm in keeping some caution.

Siren, Lyra, Dopex, Premia, Pods, Rysk and Auctus all use BS to price the options either directly or with some modifications. It is used with some modifications to price options at Siren, Lyra, Dopex, Premia and Rysk. Siren uses a mix of BS and the pricing mechanisms of Opyn (orderbook at 0xarbitrage), whereas Lyra takes a strike-adjusted implied volatility (IV) approach with BS to reach a theoretical price. Dopex prices options similarly to that of Lyra. And if we talk about Premia, it takes into account IV skew, position-size, pool capital supply and demand, along with the standard BS mechanism — making the whole process ‘liquidity sensitive’. Rysk on the other hand uses BS with an IV skew, portfolio delta and utilization.

Apart from this, protocols like Arrow Markets, Hegic and Deri price options according to different sensitivities. Arrow markets has a risk-sensitive approach to pricing. Along with some complex optimization, their pricing relies on risk assessment of AMM as well as on the chosen hedge by the engine. Their documents state:

It can be shown that this formulation sets prices in a way that is equivalent to the case where the market maker is optimizing a CARA utility function over future payouts.

Hegic on the other hand has a time-sensitive approach. Price of an option contract on Hegic depends on its intrinsic value as well as on amount of time until it expires. While pricing of options on Deri depends on the trade size optimized by volatility-sensitive mechanisms.

Opyn Squeeth though is based on an index, uses Uniswap V3 Pools. Ribbon probably has the most unique pricing mechanism compared to other option protocols. It sells the options (minted through Opyn by their theta vaults) using gnosis batch auctions. Here all the options are sold in only one clearing price. Figures below illustrate the intricacies involved in this process.

In these auctions, bids are arranged from highest to lowest once all the bids are placed. They are sold in the same order (see fig above). Ribbon’s option sales is decentralized as the price discovery occurs on-chain. It might be a possibility that they soon shift to a silent-auction mechanism.

But What About Adoption?

“Simplicity is the ultimate sophistication” — Leonardo Da Vinci. Though the nerds might get really fascinated with all the complexities involved in on-chain options, it’s not really good for their mass adoption. It’s really not a wise decision to ignore that corporate giants are paying millions of dollars everyday just for a moment of your attention.

Any product which requires a lot of sensory effort to use it, is simply not gonna make it! And hence, products which are easy to interact and use are going to win this game. This is probably one of the reasons why strategy vaults are getting popular with option protocols. Users can simply deposit their capital in these vaults and earn the advertised yield on it without worrying about any complex mathematical equations operating inside it.

So if we have to arrange these protocols in order of the ‘ease’ in which they can be used. Thetanuts, Dopex, Ribbon, Rysk, Jones DAO, PsyFinance, Katana, Friktion, Opyn Squeeth (Crab Strategy) would probably be the easiest as they provide their users with yield generating strategy vaults. While protocols like Siren, Opyn, Lyra and Pods could be classified somewhere in between as one can buy option-positions for a premium at a certain strike-price or tokens representing option positions (oTokens on Opyn) on them. Whereas protocols like Oddz, Auctus, Hegic and Premia are more suitable for professional traders. They provide users with variety of products which lets you generate customized positions.

What lies ahead?

In an ecosystem where wars have been brewing in on the back of derivatives (all thanks to DeFi’s composability), this doesn’t really end here. Options though chief vehicles of risk-hedging in boring traditional finance, are certainly a lot more than that in a highly-innovative decentralized finance. As crypto market gets bigger, derivatives are only going to grow from here. But surely not until the major challenges regarding efficiency and engineering of liquidity, accuracy of pricing, and information gap on derivatives are appropriately addressed. I would still remain very hopeful specially looking at innovative products from Rysk and Potion Labs. And in the end, no one really knows how many Heisenbergs are currently working on some byzantine derivatives operating from their underground labs 👀

Author is a Decentralized Finance (DeFi) researcher and analyst at Polygon with special emphasis on fundamentals, on-chain activity and social-media narratives. Their other interests include studying Attention Economy, Rumor Networks and Cognitive Design of Cryptocurrency Protocols. They like to do gardening, scroll twitter and explore different movie genres in their free time. They can be reached on twitter at 0xlol