Pyth

Pyth: Overview

Pyth is an open-source real-time on-chain market data feed. Pyth's market data is contributed by over 95 first-party publishers, including some of the biggest exchanges and market making firms in the world. Over 150 protocols on 40+ blockchains trust Pyth to secure their applications.

Meridian uses Pyth's following price feeds on Meter.io Network

PairPrice DeviationID

ETH/USD

0.5%

ff61491a931112ddf1bd8147cd1b641375f79f5825126d665480874634fd0ace

MTRG/USD

1%

20d096e088a9b85f8cf09278965b77aeb05c00769e2ddeda5ea2d07ea554b283

USDC/USD

0.5%

eaa020c61cc479712813461ce153894a96a6c00b21ed0cfc2798d1f9a9e9c94a

USDT/USD

0.5%

2b89b9dc8fdf9f34709a5b106b472f0f39bb6ca9ce04b0fd7f2e971688e2e53b

Pyth Design: Data Sourcing

Pyth allows market participants to publish pricing information on-chain for others to use. The protocol is an interaction between three parties:

  • Data providers submit pricing information to Pyth's oracle program. Pyth has multiple data providers for every price feed to improve the accuracy and robustness of the system.

  • Pyth's on-chain oracle program on Pythnet combines providers' submitted data to produce a single aggregate price and confidence interval.

  • Applications such as Meridian read the price information produced by the oracle program. More specifically, Pyth allows users to “pull” prices onto the blockchain when needed. Those prices become publicly available for everyone on that chain.

Pyth's Design Goals:

1. Robustness: The aggregation algorithm ensures resilience against manipulation. Even if one provider submits an outlier price, the aggregate remains stable.

2. Weighted Accuracy: It appropriately weighs data sources based on their accuracy levels. This prevents less accurate sources from overly influencing the aggregate price.

3. Reflective Confidence Intervals: The aggregate confidence interval reflects the variation between prices reported by different providers. During normal market conditions, it aligns with individual providers' confidence intervals, but widens during instances of significant price divergence across exchanges.

For an in-depth explanation of the pricing mechanisms, consult Pyth's Technical Documentation.

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