Session-Aware Oracle Programs
Overview
Session-aware oracles are Oracle Programs that adjust pricing behavior based on the active trading state of an underlying market. Rather than publishing prices uniformly, they apply session-specific logic depending on whether a market is open, closed, or in a scheduled maintenance window. This directly addresses the structural mismatch between reference markets such as US equities, indices, and futures, which trade on discontinuous schedules, and onchain markets that operate continuously and require predictable price updates.
Traditional oracle feeds often pause during off-market periods or resume with abrupt price changes, creating risk for leveraged and structured products. Prices may freeze while funding accrues, liquidity conditions can shift without reflected movement, and reopen gaps can trigger clustered liquidations. Session-aware oracles resolve this at the data layer by embedding session logic directly into the oracle program. Applications consume a single continuous feed whose behavior adapts per session, removing the need to manage multiple feeds or custom off-market logic while maintaining consistent and predictable risk behavior across all trading states.
Core Components
1. Session Detection
The oracle ingests session metadata that describes whether the reference market is actively trading, closed, or in maintenance. This may include trading hours, holiday calendars, and scheduled pauses.
2. Primary Pricing Logic
When the market is open and authoritative data is fresh, the oracle publishes prices derived from its primary data sources.
Parameters such as update cadence, aggregation, weighting and smoothing methodology, and data freshness thresholds are explicitly defined by the application at deployment and can be adjusted as market requirements change.
3. Fallback Pricing Logic
When markets close or primary data becomes stale, the oracle switches to configured fallback behavior rather than freezing.
Fallback logic may include:
Self-referencing oracle state
Time-aware smoothing or decay functions
Incorporation of onchain signals
Activation thresholds, decay rates, and weighting behavior are all deployer-configurable.
Inputs and Outputs
Inputs
Off-chain market prices
Session and calendar metadata
Elapsed time since last update
Oracle internal state
Output
A single continuous onchain price feed
Applications consume the output without needing to reason about market sessions.
Trade-offs
Session-aware oracles introduce additional logic at the oracle layer compared to static feeds. This increases configuration surface area and requires explicit parameter choices.
In exchange, they reduce application-level complexity and standardized session handling across all markets that consume the feed.
Use Cases for Session-Aware Oracles
Perpetual markets referencing equities or structured equity type markets
Structured products built on exchange-traded assets
Synthetic markets derived from dated futures contracts
Markets where liquidation and funding logic depend on continuous pricing
These use cases benefit from predictable price behaviour across overnight closures, weekends, and holidays.
Case Study: 24/7 US Equity Indices for Dreamcash HIP-3 Markets.
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