# Oracles

To ensure accurate trading conditions and reliable price data, **Storm Trade** on the **TON blockchain** integrates two advanced oracle solutions — [**Stork**](https://docs.stork.network/) and [**Pyth Network**](https://pyth.network/).

***

## ⚡ Stork

**Stork** is a next-generation oracle designed for ultra-low latency. It updates price feeds in **less than 1 millisecond**, aggregating data from top centralized exchanges. All data is verified via digital signatures and delivered to TON through **WebSockets**.

### 💡 Key Advantages:

* 🕒 **Ultra-low latency** — lightning-fast updates for real-time accuracy.
* 📶 **Efficient aggregation** — off-chain data collection to minimize delay.
* 🌐 **Wide coverage** — data sourced from leading global exchanges.
* 🧪 **Optimized for derivatives** — ideal for futures and high-frequency trading.

📘 Learn more: [Stork Documentation](https://docs.stork.network/stork-for-real-time/what-is-stork-for-real-time)

***

## 🔗 Pyth Network

**Pyth Network** aggregates price data from over **65 sources**, including crypto exchanges, stock markets, and forex providers. Built on **Solana's infrastructure**, it transmits data to TON via the [**Wormhole protocol**](https://wormhole.com/), enabling secure cross-chain integration.

### 💡 Key Advantages:

* 📊 **Diverse data sources** — accurate pricing from a broad range of markets.
* ⚙️ **High-frequency updates** — up to **700+ price updates per second**.
* 🔐 **Cross-chain compatibility** — secure delivery via Wormhole bridge.

📘 Learn more: [Pyth Documentation](https://pyth.network/)

***

## 🧮 How Prices Are Formed on Storm Trade

On the **Storm Trade** platform, a **single unified price** is now used, formed through aggregated liquidity:

* 📉 **Index Price** — calculated based on aggregated data from **Stork** and **Pyth**, taking into account trading volumes across various exchanges. Outlier values are discarded for greater accuracy.
* ⚖️ **Market Price** — no longer exists as a separate dynamic price. Since the Storm v2.5 update, **Market Price is always equal to Index Price** and is delivered by the oracle. Trade execution price is determined with aggregated liquidity from leading CEXs (Binance, Bybit, etc.), eliminating price impact from large orders and ensuring fair conditions for traders.

***

### 🛠️ How the New System Works

* 🏦 **Liquidity Aggregation** considers the average order book depth on top CEXs and liquidity for longs/shorts.
  * **BTC & ETH** — 0% spread for any volume.
  * **TON & NOT** — 0% spread, but market depth is taken into account.
  * **RWA (real-world assets)** — fixed spread of 0.015% for any volume.
  * **Other pairs** — dynamic spread based on liquidity and CEX data.
* 📊 **One chart, one price:** traders see a single price and chart, with no hidden slippage or confusion between Index and Market Price.
* 🏹 **Minimal slippage:** trades are executed at a fair price, as close as possible to those on major exchanges.
* 🔒 **Position closing — no spread:** traders receive exactly the price displayed in the interface, with minimal signing lag.

***

### 🌟 Advantages of the Storm Trade Approach

* 🪞 **Transparency:** no hidden pricing mechanisms.
* ⚖️ **Fairness:** trade execution is as close as possible to the real market price.
* 🧩 **Convenience:** traders do not face two different prices or charts.

🏄 *Storm Trade has implemented aggregated liquidity to provide the best conditions for traders and eliminate confusion between Index Price and Market Price. Now, a single price is used, formed by the oracle and confirmed by external markets.*


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.storm.tg/protocol-mechanics/price_feeds.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.