Liquid Staking and Restaking Explained: LSTs and LRTs

DeFi faces interconnected technical and systemic risks including smart contract bugs ($3.6M DAO hack, $20M losses), oracle failures enabling price manipulation via flash loans, admin key vulnerabilities leading to rug pulls, liquidity crises in over-collateralized loans, governance failures from whale influence, and stable coin de-pegging risks. These risks demonstrate how interconnected DeFi protocols create cascading vulnerabilities where one weakness can compromise the entire system.

DeFi's composability creates complex risk loops where multiple protocols depend on each other. When users deposit ETH into liquid staking tokens, then borrow against those positions to create leverage loops, the entire system becomes interconnected. This creates 'stacking risk on risk on risk' where a failure in one component can cascade through the ecosystem. The distinction between monolithic and modular protocol architectures significantly impacts risk management, with monolithic models requiring 'all or nothing' risk assessment.

Systemic risk in DeFi refers to the potential for problems in one protocol to cascade through interconnected systems. While DeFi protocols are designed to be isolated, complex interconnections between platforms can create pathways for risk propagation. Liquidity pools and Automated Market Makers (AMMs) enable automated trading without traditional order books, using mathematical formulas to determine prices based on pool balances. DeFi platforms enable users to take leveraged positions by borrowing assets against their collateral, with leverage ratios ranging from 2x to 25x or higher, with corresponding risks of liquidation.

DeFi contracts feed on each other, creating compound risks that must be evaluated through probability assignment and compounding. Reflexivity creates circular risks where contracts destabilize each other, as seen in the Terra Luna UST case where de-pegging forced more Luna sales, decreasing price and reducing peg sustainability. Debt spiral risk occurs when companies have more liabilities than assets, leading to runs where more withdrawals increase failure probability. The DeFi Graph maps all smart contract dependencies to understand how risks propagate through the ecosystem, enabling systemic risk assessment that traditional finance cannot achieve due to opacity.

The Terra/LUNA crisis exposed systemic vulnerabilities in DeFi, demonstrating how interconnected protocols can amplify risks. True DeFi protocols offer transparency through on-chain auditable positions, whereas centralized platforms present opaque exposure risks. Curve pools containing multiple stablecoins create systemic risk because adding more speculative coins increases overall failure probability—unlike traditional diversification, where additional assets reduce risk. This highlights the need for better risk differentiation between stablecoins and yield products, as well as improved risk communication to help users understand underlying exposures beyond headline yields.

Liquid staking dominates blockchain ecosystems due to three interconnected forces: (1) Natural capital-labor division—users delegate staking rather than operate validators, especially as ether increases in value; (2) Superiority of liquid staking—tokens provide both yield and liquidity, enabling use as collateral, trade, or transfer; (3) Network effects—tokens compete directly with native tokens as money, creating winner-take-most dynamics. These forces make sustainable competition among liquid staking protocols extremely difficult. The pragmatic view accepts this reality and focuses on mitigating centralization risks through structural safeguards rather than opposing market forces. This thesis explains why Lido continues growing despite criticism—it represents the inevitable outcome of market forces acting on user preferences for convenience and utility.

Major liquid staking protocols differentiate through validator selection models and entry barriers. Lido maintains a permissioned operator set of 29 entities, offering 3.8% APY but facing regulatory concentration risks. Rocket Pool enables permissionless participation but requires $80+ bonding plus RPL tokens, creating a $25,000+ barrier. Stader reduced this to $4.40 with minimal governance token exposure, democratizing validator access. On Ethereum, permissionless node operators enhance decentralization, addressing concerns about government pressure on centralized validator sets. As staking rewards decline with increasing participation, capital efficiency becomes essential, though concentration risks necessitate distributing value across multiple protocols with continuous security improvements.

Liquid staking protocols like Lido on Ethereum create centralization risks because they allow stakers to earn yield while simultaneously using staked tokens for other purposes (selling, leveraging, lending). This 'double dipping' creates perverse incentives where participants maximize profits rather than securing the network. The liquid staking tokens accumulate liquidity in other ecosystem parts, creating network effects where the most liquid contracts attract more users. This concentration of staking power in few large providers poses risks to network decentralization and security.

Liquid staking has become a dominant DeFi trend with rapidly growing TVL. The Shanghai upgrade will enable bidirectional staking, currently impossible due to a 2% loss when unstaking. Currently, only 13% of Ether is staked compared to 60-70% on competitors like Cardano and Solana. Once Shanghai enables risk-free liquid staking, demand could potentially triple. This creates a sustainable asset model where holders receive 4-5% rewards while maintaining collateral utility. Increased liquid staking leads to more gas fees burned and Ether locked, creating a positive feedback loop for the network.

Liquid staking protocols must navigate fundamental tensions in validator selection: decentralization versus network performance, community governance versus protocol control. Different chains adopt varying strategies—Cosmos Hub and Osmosis use community-led councils evaluating validators, while Celestia uses copy-staking delegating proportionally to all validators. Stride adapts its approach to each chain's preferences, demonstrating how liquid staking protocols must balance multiple competing objectives. This iterative progression from minimal intervention to increased opinionation reflects broader challenges of aligning liquid staking protocols with host chain interests while maintaining trust minimality.

This video explains a four-layer strategy to maximize Ethereum accumulation through liquid staking and restaking protocols. The strategy involves depositing Ethereum into liquid staking protocols (Layer 2), selecting specific blockchains for staking (Layer 3), and then depositing the staked tokens into DeFi projects on those blockchains (Layer 4). This approach allows investors to earn points from multiple projects and blockchains with a single investment, potentially qualifying for multiple airdrops. The video emphasizes that while this strategy can be profitable, it involves risks and requires diversification across multiple projects. Key projects mentioned include EigenLayer, Puffer Finance, StakeStone, Ether.fi, Kelp, and Renzo, with Linea, Scroll, and Mode being the primary blockchains for Layer 3.

The halving event is primarily an informational event that creates market sentiment rather than a direct price driver. The massive institutional capital flowing into crypto through ETFs creates price movements that dwarf the halving's impact, representing a fundamental shift from supply-side mechanics to demand-side institutional adoption. Ethereum's transition to Proof of Stake enabled liquid staking protocols like Lido, allowing users to stake any amount of ETH and receive liquid staking tokens. Liquid restaking protocols like EigenLayer allow users to restake their liquid staking tokens to earn additional rewards while maintaining liquidity. The Pendle protocol enables users to purchase yield tokens representing future staking rewards, enabling strategies like earning 10-12 ETH worth of yield tokens for each ETH staked.

The execution process involves: (1) Staking ETH with Ether.fi to receive eETH liquid restaking tokens, (2) Managing gas fees by timing transactions during low network congestion (ideally low teens), (3) Adding tokens to wallet by importing contract addresses from block explorers, (4) Tracking yields and points through the portfolio dashboard. Users can unstake at any time or swap on DEXs. The process requires understanding that liquid restaking tokens represent staked ETH deposited with EigenLayer, allowing continued asset utility while earning restaking rewards.

The speaker explains the economics of liquid restaking tokens (LSTs) like Renzo, Kelp, and Swell. He notes that the total value locked (TVL) in these protocols is around 15-17 billion dollars, but the actual value proposition is questionable. He explains that if users deposited $1 and received $1 in tokens, the token would need to be valued at $17 billion to justify the TVL, which is economically unsustainable. The speaker describes this as a 'game of DOP' (Dutch Auction) where expectations exceed reality. He notes that many users who deposited large amounts have received minimal returns, with some receiving only $800 for hundreds of thousands of dollars deposited over 30 days.

Liquid staking tokens like LBT (Lombard BTC) represent a new form of tokenization that brings yield-bearing capabilities to Bitcoin. When users stake their Bitcoin through Babylon, LBT is minted as a liquid representation that can be used in DeFi protocols including Uniswap, Curve, Gearbox, Morpho, and Aave. Restaking allows users to stake their LBT tokens to participate in the security of the Lombard network, creating a dual-tranche system with different risk-return profiles. No-consensus networks (NCN) represent a new paradigm where validators offer services without requiring consensus. Security markets are evolving from simple double-signing mechanisms to complex applications including insurance, tranching, and dual-tranche systems.