What are the risks in DeFi?

The appropriate risk-return trade-off depends on an investor's risk tolerance. It is important to understand all the risks involved with DeFi that are powering the higher potential rewards.

Risks with Smart Contract Failure

Failures due to smart contract code can cascade due to the composability of DeFi

Due to the composable nature of protocols (think Money Legos 🧱) within DeFi, a key risk associated with them is smart contract failure.

Since every protocol or application is built with smart contracts interacting with one another in some form, smart contract failure in one of the core components could cause a ripple effect throughout the DeFi ecosystem.

This means that smart contract failure on the lower layers could lead to loss of funds in the protocols or applications that are built at the higher layers.

Mitigating Smart Contract Risks through Multiple Security Audits

These smart contracts have been put through multiple security audits like the Compound Protocol from reputable firms like Trail of Bits.

Risks with Stablecoin Pegs

Failure to maintain its desired peg could lead to loss of funds for Stablecoin holders

Stablecoins are designed to minimize price volatility relative to another asset by pegging to another currency (fiat, crypto) or commodity.

Stablecoins can fail due to collateralization and volatility risk together with flawed mechanism designs to maintain their respective pegs.

However, the main risks are associated with specific collateral types backing these stablecoins. Overcollateralization can help to reduce volatility risk but if the prices of the underlying collateralized asset drops too quickly, liquidation might not be enough to cover the full amount that was borrowed.

That being said, the risks are greatly reduced with a reasonable collateralization ratio and sound collateral types that have a monetary premium and deep liquidity like Ether or Bitcoin.

Losing a desired peg could cause loss of funds for stablecoin holders and that is why at Unagii we have decided only to work with the best, time-tested and widely accepted stablecoins like USDC (which is 1:1 backed by US dollars in a bank account issued by Coinbase) and DAI (decentralized crypto-overcollateralized stablecoin)

Market Risks

As with all new markets and technologies, other complex risks could exist with new Financial Platforms like Compound. One of these complex risks is Market Risk and better financial models are needed to better analyze these risks.

Platforms like Gauntlet have done thorough Risk Assessments like the one here : https://gauntlet.network/reports/CompoundMarketRiskAssessment.pdf

We use a rigorous definition of market risks to construct simulation-based stress tests that evaluate the economic security of the Compound protocol as it scales to underwriting billions of dollars of borrowed assets. These stress tests are trained on historical data and put through a battery of scenarios that represent the expected and worst case economic outcomes for the protocol. Our stress tests are constructed analogously to how transaction-level backtesting is done in high-frequency and algorithmic trading. These techniques are used to estimate the market risk of a systematic trading strategy before it is deployed to the market. As there are over $1 trillion US dollars of assets managed by funds that use these techniques to provide daily actuarial analyses to risk managers, we believe that these are the best methodologies for evaluating market risk. By modifying these techniques to handle the idiosyncrasies of cryptocurrencies, we are able to provide similar statistical power in these actuarial analyses

Here is their conclusion:

Our conclusions show that the Compound protocol can scale to a larger size and handle high volatility scenarios for a variety of collateral types. In particular, we find statistically significant evidence that even when Ether (ETH) realizes it’s maximum historical volatility, the Compound system is able to grow total borrowed value by more than 10x while having a sub 1% chance of default.

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