Yield farming is the practice of staking or lending crypto assets to generate high returns, often in the form of additional tokens. It is the foundational activity upon which leverage is applied.

• Involves providing liquidity to DeFi protocols like Aave or Compound.
• Rewards are typically paid in governance tokens (e.g., COMP, AAVE) or a share of trading fees.
• Users earn yields by depositing assets into automated market maker (AMM) pools on platforms like Uniswap or Curve.
• This matters as it provides the base yield that leverage aims to magnify, but also introduces impermanent loss risk.

Collateralized borrowing is the process of depositing crypto assets as collateral to take out a loan in a different asset, a core mechanism for obtaining leverage.

• Protocols require over-collateralization (e.g., 150% collateral ratio) to secure loans against price volatility.
• Borrowed assets are then used to farm additional yield.
• A real example is depositing ETH as collateral to borrow stablecoins like DAI on MakerDAO.
• This is crucial because it allows farmers to access capital without selling their holdings, but liquidation occurs if the collateral value falls below a threshold.

Leverage involves using borrowed funds to increase the potential return (and risk) of an investment. In yield farming, it amplifies the farming position's size.

• Achieved by looping the process: farm yields, use yields as more collateral, borrow more, and re-invest.
• A 3x leverage position means for every $1 of capital, $2 is borrowed.
• A use case is using a leverage protocol like Alpha Homora to automate this looping on Ethereum.
• This matters as it can significantly boost APY but also multiplies potential losses from market downturns or yield drops.

Liquidation risk is the danger that a leveraged position will be forcibly closed if the collateral's value falls too close to the loan value, resulting in significant losses.

• Triggered when the collateral ratio hits a protocol's liquidation threshold (e.g., 110%).
• Liquidators can buy the collateral at a discount to repay the loan.
• An example: If ETH price drops 30%, an over-leveraged farmer may lose most of their collateral.
• This is the primary financial risk in leveraged farming, requiring active monitoring and risk management strategies.

DeFi Protocol Interactions refer to the interconnected use of multiple decentralized finance applications to execute a leveraged farming strategy, often requiring smart contract knowledge.

• A strategy might involve using Curve for stablecoin farming, Aave for borrowing, and a leverage aggregator like Yearn.
• Each interaction incurs gas fees and smart contract risk.
• Users must understand how to use wallets (like MetaMask), bridge assets, and approve token contracts.
• This matters because successful execution depends on navigating a complex, multi-step process across different platforms securely.

Capital Efficiency measures how effectively capital is used to generate yield. In leveraged farming, the goal is to maximize Annual Percentage Yield (APY) on the initial capital.

• Calculated by comparing the net yield (farm yield minus borrowing costs) to the user's initial equity.
• High borrowing costs or low farm yields can make strategies unprofitable.
• A real consideration is comparing the APY of a leveraged USDC/DAI pool against the interest rate for borrowing DAI.
• This is the ultimate metric for success, but it must be weighed against the substantially increased risks.

Forced liquidation occurs when the value of your collateral falls below the required threshold, triggering an automatic sale at potentially unfavorable prices.

• A sharp market dip can cause a cascade of liquidations, worsening the price drop.
• Example: Borrowing against ETH to farm, then a 15% ETH price crash triggers liquidation, selling your collateral at a loss.
• This matters as it can wipe out a user's entire position almost instantly, turning a paper loss into a realized one.

Code vulnerabilities in lending protocols, farms, or oracles can lead to the permanent loss of funds through exploits or hacks.

• Bugs can allow attackers to drain pools or manipulate price feeds.
• Example: A flash loan attack exploiting a rounding error to drain millions from a yield farming vault.
• This is critical because users are trusting complex, often unaudited, code with their borrowed and collateralized assets.

Diverging asset prices in a liquidity pool can cause a loss compared to simply holding the assets, which is amplified when using borrowed funds.

• Losses are 'impermanent' until you withdraw, but become permanent upon exit.
• Example: Providing ETH/DAI liquidity; if ETH price surges, you end up with less ETH than you started with.
• This matters because the farming rewards must outweigh this hidden loss, which is not guaranteed, especially in volatile markets.

Inaccurate price feeds from oracles can cause improper loan valuations, leading to faulty liquidations or allowing undercollateralized borrowing.

• A delayed or manipulated price can be exploited or cause unjustified liquidations.
• Example: A flash loan temporarily spikes an asset's price on a DEX, tricking the oracle and enabling an oversized borrow.
• This is a systemic risk as the entire protocol's solvency depends on accurate, real-time price data.

Economic model failure includes collapsing token rewards, changes in protocol rules, or unsustainable yields that vanish.

• High APY often comes from inflationary token emissions that can crash in value.
• Example: A farm's governance token loses 90% of its value, making the lucrative APY worthless in real terms.
• This matters because users take on debt expecting future rewards that may never materialize or retain value.

Amplified losses are the core danger, where leverage magnifies both gains and losses, increasing vulnerability to all other risks.

• A small adverse price move can result in a disproportionately large loss of capital.
• Example: 5x leverage means a 10% price drop against your position results in a 50% loss of your initial capital.
• This is fundamental, as it transforms manageable market fluctuations into existential threats to a user's principal.