Oracles can be permissionless (#flare), allowing anyone to participate with minimal requirements, or permissioned (#chainlink), which draws data solely from trusted sources such as trading firms or exchanges. Below are two primary applications.
Lending
Protocols like Aave use oracles to assess collateral value for issuing loans. If asset prices fall, oracles supply data to trigger liquidations, maintaining protocol solvency by ensuring collateral covers loan amounts. Oracles are used to prevent unfair liquidations, which could arise from low volume on the perps LOB, by attempting to reflect the global price of an asset across all exchanges.
Perpetual Futures
In leverage trading on exchanges, perpetual futures are a zero-sum game, where no underlying assets are exchanged. Instead, long and short positions are matched, with one trader’s gains equaling another’s losses (see link 1 in comments). Since no assets are bought or sold, index prices determine funding rates and initiate liquidations for leveraged positions, ensuring contracts align with market prices. In DEXs (eg. $hype, see link 2 below), these index prices are calculated using oracles.
Price oracles are indispensable for bridging on-chain systems with off-chain data in DeFi. However, the accuracy and reliability of these systems depend heavily on how data is aggregated and how participants are incentivized to play. In the next posts, we’ll dive into current industry practices, to better understand if the oracle problem has been solved (and what advantages $kas brings to the table).
Spoiler : it hasn’t.
