AT's performance today was indeed fierce—surging 59% in 24 hours, soaring from a certain price level all the way up to 0.1687. On the trading surface, buy orders flooded in, and the 15-minute candlestick chart almost had no room for any pullback, as if it was climbing steadily along the 7-day moving average. The bullish momentum appears unstoppable.

However, behind this madness, there's a more worth pondering issue: when an asset experiences such drastic volatility, what does the price we see on the exchange truly represent?

In the crypto market, liquidity is dispersed across various platforms, and wash trading is not uncommon. The price differences between different exchanges can sometimes be astonishing. Simply put, a seemingly straightforward "price" in this world might correspond to a hundred different trading realities. The price you see on Platform A might be very close to that on Platform B, or it could be worlds apart.

This raises a deeper question: for traders, what is a reliable reference? For DeFi protocols relying on on-chain data, how can they avoid being "deceived" by abnormal data from a single platform?

For example, if AT suddenly surges on one platform, does the trading activity elsewhere synchronize? Is there a significant pricing discrepancy in the derivatives market? Will smart contracts that use this price for liquidation or collateralization suffer losses due to distorted data from a single source?

At this point, the value of decentralized oracle networks becomes evident. Their role is far more than just "feeding prices." Essentially, they act as a filter for market consensus.

Their workflow is as follows: aggregating data from multiple independent nodes, which obtain information from different exchanges and liquidity pools. Once enough data is collected, a consensus verification mechanism is used to filter and validate the information, ultimately outputting a "trustworthy price" that on-chain smart contracts can rely on.

The benefits of this approach are clear. Even if the price on one exchange is temporarily manipulated, the output of the decentralized oracle can remain stable. Why? Because it has already filtered out anomalous, outlier data points, reflecting a broader market reality.

For assets like AT, which are highly volatile, this mechanism is especially important. The greater the volatility, the higher the risk of single-point distortion, and the easier it is to exploit. Through multi-source data aggregation and consensus verification, decentralized oracles can significantly reduce this risk, ensuring that on-chain applications receive more accurate and trustworthy price information.