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A large number of improvements in the liquidation mechanism: optimization of the liquidation threshold, anti-MEV, internal multi-collateral poolhow can germany buy bitcoin1. Combine mortgage rate and borrowing rate to customize the threshold of asset liquidation

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Like mainstream lending agreements, Euler requires users to ensure over-collateralization, that is, the value of assets is greater than the value of liabilities. When the value of liabilities exceeds a certain ratio of the collateral, it will allow the liquidator to liquidate the mortgagor's assets and repay the debt. But in the calculation of debt value, Euler also introduced the concept of borrowing factor. The liquidation threshold of each borrower is tailored to the specific risk profile associated with the assets they borrow and use as collateral. In other words, when the value of the borrower's risk-adjusted liabilities exceeds the value of the collateral, it may be liquidated. Specifically, compared to the original lending mechanism, Euler's mechanism also adds a multi-dimensional risk assessment of liabilities, which further improves the safety margin of liquidation.At present, the main liquidation incentive model adopted by mainstream lending agreements such as Compound is: the liquidator can purchase the mortgagor's assets with a fixed percentage discount. Under this mechanism, all liquidators face the same liquidation opportunity, and their potential profit percentages are the same, so they can only compete for liquidation opportunities by increasing Gas, where the high MEV value (Gas cost) becomes the liquidator’s The additional cost also increases the risk of the system. On the other hand, for mortgagors, the fixed asset discount auction rate also allows them to lose the opportunity to lose a lower liquidation penalty.In response to this problem, Euler’s plan is to use Dutch auctions in liquidation, which can ease the joint bid of liquidators and may also obtain lower asset liquidation losses for mortgagors. At the same time, Euler also provides a discount acceleration mechanism for the collateral provider, so that he is eligible to conduct self-liquidation before the liquidator conducts the Dutch auction and reduce the mortgagor's loss. The above two measures are to restrict miners from grabbing excessive MEV fees in the liquidation, so as to improve the overall security of the system in the liquidation storm.In order to further reduce the transaction cost of liquidators in liquidation, Euler also borrowed the stable pool model pioneered by the Liquity protocol and expanded it into a multi-collateral stable pool form, allowing lenders to provide liquidity to the stable pool of each loan market. Support liquidation.Liquidity providers in the stable pool earn liquidation collateral rewards by depositing eToken (a deposit certificate of the Euler protocol, similar to Compound's cToken). When the liquidation is in progress, the liquidator directly uses the liquidity from the stable pool to repay the debts of the borrower, and will proportionally reward the liquidation collateral obtained to the stable pool, that is, the lender can eventually replace it during the liquidation period. The currency is passively converted into liquidation mortgage assets.

For example: Euler provides a stable pool for the USDT that lends assets. The lender who is willing to participate in the stable pool can deposit their own USDT deposit certificate eUSDT into the stable pool as the counterparty of the liquidator, so that the liquidator is auctioning After obtaining the mortgaged assets, the mortgaged assets are replaced with the deposit users of the stable pool at a discounted price (after deducting their own income), which is equivalent to that the users of the stable pool purchase the collateral at a discounted price.Compared with Liquity which only supports the LUSD stable pool, Euler's multi-token stable pool contains specific types of tokens that have not been disclosed, but it is believed that it will still be based on stable currencies or mainstream currencies.This type of bridging scheme usually has a group of verifiers that monitor the "mailbox" addresses on the source chain and perform operations on the target chain based on consensus. Asset transfer usually works like this: lock assets on the "mailbox", and then mint the same amount of assets on the target chain. These validators usually deposit separate tokens as collateral to ensure the security of the network.

Type 2: Light clients & RelaysParticipants monitor events on the source chain and generate encrypted packaging proofs about past events recorded on the chain. These proofs will be forwarded to the contract on the target chain (such as "light client") along with the block header, and then verify whether an event is recorded, and perform operations after verification. This design mechanism requires some participants to "relay" the block headers and proofs. Although users can "self-relay" transactions, there is indeed an active assumption that the relay will continue to forward data. This is a relatively secure bridging design because it guarantees the effective delivery of trustlessness without trusting intermediate entities. But it is also resource-intensive, because developers must build a new smart contract on each new target chain to parse the source chain's state proof; the verification process itself requires a large amount of gas.Type 3: Liquidity networksThis is similar to a peer-to-peer network, where each node acts as a "router", holding a "library" of source and target chain assets. These networks usually take advantage of the security of the underlying blockchain; through the use of locking and dispute mechanisms, it can be ensured that routers will not steal users' funds. Because of this, a liquid network like Connext may be a safer choice for users who transfer large amounts of value. In addition, this type of bridge may be most suitable for cross-chain asset transfer, because the assets provided by the router are the original assets of the target chain, rather than derivative assets that cannot be completely replaced by each other.

It should be noted that any given bridge above is a two-way communication channel. There may be independent models in each channel, so this classification cannot accurately represent mixed models such as Gravity, Interlay, and tBTC. Because they all have light clients in one direction and validator nodes in the other direction.In addition, the design of a bridge can be roughly evaluated based on the following factors:

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Security: Trust and liveness assumptions, tolerance for malicious behavior, security and reflexivity of user funds.Speed: The delay time of transaction completion, and the guarantee of final certainty. There is usually a trade-off between speed and safety.Connectivity: The choice of target chains for users and developers, and the different difficulty levels of integrating additional target chains.Capital efficiency: economic mechanism, which sets the transaction cost of capital and asset transfer required to ensure the security of the system.

Statefulness: The ability to transfer specific assets, more complex states, and/or perform cross-chain contract calls.In summary, the trade-offs of these three design mechanisms can be evaluated from the perspective of the following figure:In addition, security is a scope, we can roughly divide it into the following categories:Trust-less: The security of the bridge is bound to the underlying blockchain it bridges. Unless the underlying blockchain is attacked by consensus-level attacks, users' funds will not be lost or stolen. In other words, this is not complete trustlessness, because all the economic, engineering, and cryptographic components of these systems contain trust assumptions (for example, there are no loopholes in the code).

Insured (Insured): Attackers can steal user funds, but they may be unprofitable in doing so. Because they need to provide collateral to participate in the network, and they will be punished for wrongdoing and malicious behavior. If the user's funds are lost, the agreement will compensate the user by confiscation of the attacker's collateral.Bonded (Bonded): Similar to the insurance model (for example, the economic benefits of participants are closely related to their behavior), except that the user's collateral is forfeited due to his mistakes and malicious behavior. The type of collateral is important for both the insurance and the mortgage model; endogenous collateral (protocol tokens as collateral) is more risky, because if the bridge fails, the value of the token is also likely to collapse, which further reduces Security guarantee for bridging.

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Trusted: Participants do not need to mortgage assets, and users cannot retrieve assets when the system fails or commits malicious behavior. Therefore, security mainly depends on the reputation of the bridge operator."External validators and federalism" are generally better in terms of state and connectivity because they can trigger transactions, store data, and allow data to interact with any number of target chains. However, this comes at the cost of security, because by definition, users rely on the security of the bridge rather than the source or target chain. Although most of the current external validator mechanisms are based on trust models, some require collateralized assets, and a subset of assets is used to insure end users. Unfortunately, their insurance mechanisms are usually reflexive. If the agreement token is used as collateral, it is assumed that the value of the token is sufficient to compensate the user's loss. In addition, if the mortgage asset is different from the insurance asset, it will also depend on the price flow of the oracle, so the security of the bridge will be downgraded to that of the oracle. If a trust model is not required, these bridges are also the least capital efficient, because they promote economic throughput and also need to scale up the scale of collateral.

"Light client and relay" is also better in terms of state, because the block header relay system can transmit any type of data. Although there are liveness assumptions due to the need for repeaters to transmit information, they are also very safe because they do not require additional trust assumptions. At the same time, they are the most capital efficient bridges because there is no need to lock any assets. However, these advantages come at the expense of connectivity. Every time a pair of chains is connected, the developer must deploy a new light client smart contract on the source chain and the target chain. The complexity of the contract is between O(LogN) and O(N) (the reason is between this The scope is because it is relatively easy to add chain support using the same consensus algorithm). There is also a significant speed flaw in the optimistic model that relies on fraud proofs, which may increase the delay to 4 hours."Liquidity networks" are strong in terms of security and speed because they are locally verified systems (that is, global consensus is not required). They are also more capital efficient than the external validator mechanism of the mortgage/insurance mechanism, because capital efficiency is related to transaction flow/volume, rather than security. For example, assuming that the transaction flows of the two chains are equal, and given a built-in rebalancing mechanism, the liquidity network can contribute to an arbitrarily large economic throughput.The trade-off lies in the state, because although the call data can be transmitted, its function is limited. For example, they can interact with data across chains, where the receiver has the right to interact based on the provided data (for example, using the signature information from the sender to call a smart contract), but there is no "owner" of the data for the transmission or the transmission belongs to Generalized state data (such as minting representative tokens) is not helpful.Building a strong cross-chain bridge is a difficult problem in distributed systems. Although there have been many attempts in this field, there are still some problems to be solved:Finality & rollbacks: In a chain with probabilistic finality, how does bridging deal with block reorganization and time thief attacks? For example, if any chain has experienced a state rollback, what will happen to users who send themselves from Polkadot to Ethereum?NFT transfers & provenance: How can bridges trace the provenance of NFT across multiple chains? For example, if there is an NFT that has transacted in multiple markets of Ethereum, Flow, and Solana, how are all these transactions and owners recorded?

Stress testing: In the case of chain congestion or protocol and network level attacks, how will various bridge designs respond?Although bridging unlocks more innovation possibilities for the blockchain ecosystem, if the team takes shortcuts in R&D, it may also bring great risks. The Poly Network cross-chain attack event has shown us the potential economic loss scale of vulnerabilities and attacks, and I estimate that there will be more large-scale attacks in the future. Although for bridge builders, the current network is highly fragmented and competition is fierce. But each team should be highly self-disciplined and prioritize security rather than release speed.

Although the ultimate ideal state is to build a "isomorphic bridge" shared by all things, the reality is that there is probably no single "best" bridge design. Different types of bridges will be suitable for different specific applications (such as asset transfer, contract invocation, token minting, etc.).In addition, the best bridge should be the most secure, connectable, fast, capital efficient, cost-effective, and censorship-resistant. If we want to realize the vision of the "blockchain internet", these attributes need to be maximized by us.

So far, we have not constructed the optimal bridge. There are several interesting research directions for all bridging types:Reducing the cost of block header verification: The cost of block header verification for light clients is very high. If this problem can be solved, it will bring us closer to achieving fully universal and trustless interoperability. An interesting design is to bridge to L2 to reduce these costs. For example, implement the Tendermint light client on zkSync.

Shift from a trust-based model to a mortgage model: Although the capital efficiency of mortgage verifiers is much lower, the security of "social contracts" is not enough to protect billions of dollars in user funds. In addition, the fancy threshold signature mechanism does not reduce trust; this group of signers still belongs to a trusted third party. Without collateral, users actually hand over their assets to an external custodian.Change from a mortgage model to an insurance model: Loss of assets is the last thing users want to encounter. Although verifiers and repeaters of mortgage assets can prevent malicious behavior to a certain extent, the agreement should go further and directly use the confiscated funds to compensate users.Expanding the liquidity of the liquidity network: The "liquidity network" can be said to be the fastest bridge for asset transfer, and there are some interesting design trade-offs between trust and liquidity. For example, the liquidity network may be able to use the mortgage verifier model to outsource capital supply, where routing may also be a threshold multi-signature with mortgage liquidity.Bridge aggregation: Although the use of bridges may follow the law of exponential for a specific asset, an aggregator like Li Finance can improve the experience of developers and end users.

Nowadays, many GameFi projects continue to emerge, and provide a variety of participation methods and play-to-earn and pledge functions. So, how to judge which projects can be held for a long time and can add value? How to find potential NFT agreements?The calculation of agreement income is the focus of value investment.

First of all, let's take a look at what is the agreement income? What is the difference with income?Let me talk about the definition of revenue. Revenue measures the return of all participants, that is, the total cost paid to the contract supplier. For example, the fees paid to liquidity providers in AMM, the transaction fees of decentralized exchanges, and the amount of interest on the lending platform in DeFi. Revenue is obtained by charging a rate to the total flow of the agreement. Simply put, revenue refers to the total fees paid by end users of blockchain or decentralized applications. These revenues will eventually be distributed to token holders, liquidity holders and protocol libraries.

GMV (Gross merchandise volume) refers to the total flow of the agreement, which represents the transaction volume of the blockchain or the transaction volume and borrowing volume of decentralized applications. For decentralized exchanges, GMV is the total transaction volume, and for lending agreements, GMV is the total borrowing volume.The fee rate is the fee charged to GMV, which can be the transaction fee of the blockchain, the transaction fee of Dapp, or the interest rate of the loan.

Income calculation formula:GMV * Take Rate = RevenueTotal transaction volume * rate = project revenue (total fees paid)The total revenue is distributed between the agreement and its Token holders and supplier participants (miners/validators, liquidity providers, lenders, etc.). For early-stage projects, 100% of the revenue is usually distributed directly to supplier participants. In the long run, the revenue sharing model will be more diversified, and the agreement and its owners can also get a share of the total revenue.

Agreement revenue represents the cash flow of the agreement. The agreement collects costs from users and is calculated as a percentage of total revenue.The difference between agreement income and income

Revenue is the amount that users pay for the use of the contracted service. These revenues are obtained by the supplier participants who provide the basic service, and the contractual revenue refers to the amount of revenue actually obtained by the Token. This actually represents the bottom value of the agreement, which is the profit margin. In other words, just as early-stage startups and growth companies do not pay dividends to shareholders, not every agreement allocates cash flow to Token.Cost refers to how much of the agreement income is used for grants, wages, and audit fees. That is, the sum of all costs and expenses paid according to the implemented on-chain governance recommendations.

Income: How much funds are distributed to Token holders as dividends, ie = agreement income-cost and difference.To sum up in one sentence, revenue is the amount that users pay to the agreement, which is mainly the income brought by the provider of the underlying service, and the agreement income is the cumulative income brought by Token. Agreement revenue represents profit and is the basis of the agreement.

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Perspectives of a 2x entrepreneur turned VC at @UpfrontVC#

Mark Suster

Written by

2x entrepreneur. Sold both companies (last to salesforce.com). Turned VC looking to invest in passionate entrepreneurs 〞 I*m on Twitter at @msuster

Both Sides of the Table

Perspectives of a 2x entrepreneur turned VC at @UpfrontVC, the largest and most active early-stage fund in Southern California. Snapchat: msuster

Mark Suster

Written by

2x entrepreneur. Sold both companies (last to salesforce.com). Turned VC looking to invest in passionate entrepreneurs 〞 I*m on Twitter at @msuster

Both Sides of the Table

Perspectives of a 2x entrepreneur turned VC at @UpfrontVC, the largest and most active early-stage fund in Southern California. Snapchat: msuster