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The Evolution of DeFi Across Four Financial Primitives

Photo by Hello I’m Nik on Unsplash

Financial Primitive 1: Liquidity

Almost everything comes down to liquidity, but we consistently underestimate its importance. Higher liquidity results in tighter spreads and greater market efficiency. Lower liquidity exaggerates market movements and amplifies sell-offs. It creates a flywheel on the way up but a cliff on the way down.

The opportunity cost of captive capital scaled along with DeFi and now v2s and v3s are fighting to achieve greater capital efficiency.

Collateral as Liquidity

Stablecoins play an enormous role in DeFi. Fiat-backed stablecoins are problematic (centralization, regulation, potential competition from CBDCs) and cryptocollateralized stablecoins present the most viable alternative. However, v1s relied on overcollateralization to maintain their peg and haven’t been able to scale. Purely algorithmic, uncollateralized stablecoins have never performed as intended and v2 attempts seem subject to the same shortcomings (incentive mechanisms that perform well above the peg, but not below).

DeFi v1 figured out how to use liquidity as collateral (LP tokens). v2 and v3 protocols are figuring out how to convert collateral into liquidity.

Unfortunately, liquidity alone does not result in stability. The real reason stablecoins collapse is a crisis of confidence below the peg. Addressing captive capital is not sufficient. Sound economic mechanisms are required to keep the stablecoin near its peg over time, and mechanism design is hard. Purely algorithmic stablecoins (Basis Cash, Empty Set Dollar) have struggled with mechanisms that require confidence in the future peg exactly when the present peg is failing. So-called Direct Incentives, which penalize trades away from the peg and reward trades towards the peg, end up pulling liquidity out of the system at the exact moment it’s most needed.¹⁰ Severe sell penalties mimic constrained liquidity and keep more capital captive, which is the problem we’re trying to solve in the first place. Other models attempt to solve for confidence first and improve capital efficiency over time, beginning with a fully collateralized token and letting the market adjust the collateralization ratio dynamically. As confidence goes up, so does capital efficiency. FRAX uses this model, but is currently backed by a basket of fiat-backed stablecoins. While the mechanism appears to be working, it’s unclear how it would hold up were it exclusively collateralized by uncensorable assets.

While the newest generation of stablecoins are focused on lowering collateralization requirements, we need to solve for confidence in the peg (effective mechanism design) before capital efficiency.

Liquidity as a Liability

We can’t talk about liquidity without talking about Uniswap, the dominant AMM. Uniswap played an important role in the rise of yield farming and liquidity mining, which, in turn, played an important role in Uniswap’s trajectory. After we learned (the hard way) that liquidity is not a moat, the focus moved from acquiring it to retaining it. Competing AMMs began moving up the stack to add higher moat/margin services like lending (Kashi Lending), borrowing a page from traditional fintech: acquire users cheaply and upsell credit products. Instead, Uniswap fundamentally rethought the AMM liquidity mechanism, resulting in a v3 that improves capital efficiency by up to 4000x, in special cases.⁷

The next generation of AMMs require less capital but result in more liquidity.

Liquidity Trade-offs

Superfluid collateral is a v1 concept that refers to the ability to tokenize locked capital (collateral or liquidity) in order to access liquidity or gain leverage on that capital. Staking derivatives extend this concept to staked assets (assets that secure proof-of-stake networks) via stake tokens (stETH, rtokens) that essentially allow staked capital to be deployed more productively elsewhere. Proponents of staking derivatives argue that without them, network token liquidity will suffer as a large portion of outstanding supply will remain captive. There are also concerns that validators won’t be incentivized to stake if/when they can earn higher returns on capital deposited elsewhere (DeFi protocols). In theory, staking derivatives could increase the percentage of ETH staked from 15–30% to 80–100%, since it removes the additional costs of staking compared to not staking.¹⁴

Financial Primitive 2: Leverage

Leverage amplifies gains (it’s the ultimate in capital efficiency) but also dramatically accelerates losses. Creating leverage is easy, controlling it is hard. We love it, until we hate it.

Leverage is easy in DeFi , controlling it is still hard.

Creating Leverage

Much of the frenzied activity during the DeFi Summer of 2020 was driven by active leverage strategies that relied on recursive yield farming and liquidity mining. While this activity has died down since then, we are starting to see new leverage mechanisms emerge. Element’s Yield Token Compounding is one example. When a user deposits collateral via Element, two tokens are minted: a principal token and a yield token. Let’s say a user deposited principal of 10 ETH at 20% APY. The token holder can sell the principal token at a discount. At a fixed rate yield of 10%, they would receive 9 ETH while maintaining exposure to the interest paid on all 10 ETH over time via the yield token. The user could then open a new position with the remaining 9 ETH and repeat, achieving up to 6.5x leverage.³ The ability to earn interest on the full principal amount, while being able to access the loan’s NPV, is unique relative to earlier lending protocols.

New lending protocols utilize the time value of money and the separation of principal and yield to allow users to benefit from (over)collateralization.

Cross-Collateral Complexity

While the early DeFi ecosystem relied mostly on recursive loops denominated in one asset (ETH), v2s expanded the complexity of lending protocols by allowing for multi-collateral systems, in which n assets can be borrowed against m collateral. Single-Collateral Dai evolved into Multi-Collateral Dai, Compound supported cross-collateral money markets, which Aave and CREAM expanded on by supporting more and more assets. Yearn’s StableCredit protocol allows users to mint synthetic debt positions to essentially swap collateral (functionality which Aave v2 supports via flash loans). Some protocols take it a step further and pool exposure to all of these assets, spreading counterparty risk across users. On Synthetix, when the value of any synthetic asset minted on the protocol increases, it raises the value of total debt in the system, while a user’s ownership of the total debt pool remains constant. This can result in outcomes where a user’s debt balance increases due to a price increase of an asset to which they have no direct exposure.² This cross-collateral complexity and cross-asset exposure improves functionality but also increases the likelihood of market contagion, whereby a sell-off in one asset causes a sell-off in others.

Controlling Leverage

Composability enables rapid innovation, but it also means that money legos can quickly become money dominos. Despite on-chain transparency, the difficulty of creating a cohesive view of leverage compounded across protocols means there is currently no easy way to understand how much credit is commodity credit versus circulation credit,⁹ which has implications for the solvency of the system. Solvency is particularly important in a system that, by design, has no lender of last resort. Additionally, while centralized venues liquidate underwater collateral themselves, avoiding counterparty risk, decentralized protocols rely on third-party liquidators to remove underwater debt from their balance sheets. These liquidators can choose to purchase underwater collateral from the protocol at a discount, but they can also choose not to, due to volatility, network congestion, and/or other market factors.¹² Liquity attempts to overcome this issue by creating a pool of funds that can be used for liquidations. In this model, LPs agree in advance that their liquidity will be used to buy collateral at a discount during liquidation periods. While this enables the protocol to lower loan collateralization ratios to 110% and offer a fixed rate of 0% interest, LPs could end up buying collateral as prices are falling, which could come at a much higher cost.

Financial Primitive 3: Risk

There is one ratio that is nearly inescapable in finance: risk/reward. The idea is simple: higher returns require more risk. With one exception (financial primitive 4), it is extremely difficult, if not impossible, to break this ratio.

Binary Risk

Volatility products allow market participants to take a binary view on market risk and are a critical piece of market infrastructure. The VIX, an index representing the market’s estimate of future volatility, is a cornerstone of traditional financial markets. CeFi markets already offer some vol products (FTX MOVE), but DeFi markets have few equivalents. Protocols like Volmex are working to create a volatility index while Benchmark Protocol’s stablecoin uses the VIX as an input to its stability mechanism. INDEX Coop seems like a natural candidate for a DeFi native volatility index and Opyn has expressed interest in creating a “DeFi VIX” as well.

Risk on a Sliding Scale

Emerging DeFi protocols are developing “risk-matching engines” to pair market participants that prefer less risk with those that prefer more. Most are approaching this via multi-token systems that separate speculative versus non-speculative aspects of a protocol and redistribute cash flows accordingly (Saffron, BarnBridge, Element). For example, Element splits principal and yield, allowing users to purchase the NPV of the principal (basically a zero-coupon bond) or take up to 10x leveraged exposure to the yield.⁸ BarnBridge splits cash flows into fixed yield and variable yield. Variable yield holders get upside above a fixed rate but subsidize the fixed yield token holders in the case of a shortfall. Similarly, Saffron splits risk into senior and junior tranches. Senior tranches except lower yields in exchange for coverage from junior tranches in the event that things go south. More yield = more risk.

Risk tranches have become toxic in the past, namely when they’ve tried to circumvent the risk/reward ratio. The CDO² will forever be my favorite example of clever financial engineering, packaged to look like a riskless instrument when it was actually full of risk.

Financial Primitive 4: Arbitrage

There is one important exception to the risk/reward ratio and that is arbitrage. Arbitrage creates (theoretically) riskless profit opportunities and it plays a critical role in price discovery, which is one of the things smart contract platforms are best suited for.⁴ The Kimchi premium is a perfect example. Buy an asset for $55,000 in the U.S. and sell the same asset for $65,000 in South Korea. Riskless profit.

v1s focused on cross-protocol arbitrage, v2s/v3s are focusing on chain-cross arbitrage

Arbitrage increases market efficiency (the degree to which market prices reflect all available, relevant information) but it also results in narrower spreads and normalized yields, eliminating temporary advantages between protocols. As market efficiency increases, so does competition. True protocol innovation, and not just incrementalism, will be required to maintain dominance in this environment.



Zero Knowledge Blog is a blog that looks into the tech that will power the emerging Web3 and the community that is building it. Here we are able to take the ideas explored on the Zero Knowledge Podcast and go deeper with them, showcasing new insights and perspectives.

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Justine Humenansky, CFA

if it’s not a dao, why do it? former ballerina. currently @ rabbithole