In the Crypto Assets market, the accuracy of data is crucial. However, many people tend to only focus on the price values when using Oracle Machine data, often overlooking the reliability of the data. For example, when different Oracle Machines report slightly varying Bitcoin prices, how can one determine which is more accurate? The Pyth network introduces the concept of "confidence intervals," providing users with a powerful tool to assess the reliability of the data.

The confidence interval is actually a representation of the possible margin of error for the current quote. For example, if Pyth shows that the price of Bitcoin is $30,000, the confidence interval is ±0.1%, which means that the actual price is likely to fall between $29,970 and $30,030. In contrast, if the confidence interval is widened to ±1%, it indicates that the reliability of the data is relatively low.

Pyth calculates confidence intervals by comparing quotes from multiple data sources. For example, it may take into account quotes from institutions such as Binance, Coinbase, and Jane Street. If these prices are close together, the confidence interval will be smaller; if there are clearly deviating outliers, the system will discard them to ensure that the calculated interval accurately reflects the fluctuations in market prices.

In financial application scenarios, the importance of confidence intervals is self-evident. Taking the clearing mechanism as an example, using data with a small confidence interval can improve the accuracy of the liquidation price and reduce the risk of false liquidation. Some lending protocols even explicitly state that liquidation will only be performed if the confidence interval is less than a certain threshold, which effectively protects the interests of users.

For the average user, the confidence interval can be thought of as a kind of "risk indicator". If an oracle provides data with no confidence intervals, or if the intervals are too large, this may indicate that the reliability of the data is questionable. Users should be cautious when using platforms that rely on such data. By exposing its confidence interval information, Pyth not only demonstrates confidence in the quality of its own data, but also provides users with a more transparent and reliable basis for decision-making.

With the continuous development of the crypto market, services like Pyth that emphasize data transparency and reliability will undoubtedly play an important role in building a healthier and more stable crypto ecosystem.