What can the liquidation map help us with? In life, it's like Gaode Map, which marks the locations where traffic accidents occur / 🚗 heavy traffic that is prone to congestion.

Kingfisher official website introduction: Can be used for directional trading (predicting price trends), high-risk return reversal trading (identifying potential reversal points), risk management (adjusting stop-losses).

We can proactively identify market risks and sources of volatility, and implement the following strategies based on this information:

1. Breakout Trading: Identifying breakout zones and retracement ranges. Breakout trading primarily relies on price fluctuations after a breakout, which are typically triggered by the activation of liquidation clusters. When the price breaks through a liquidation cluster area (such as a large number of short positions), you will see the system being force liquidated, with a large number of positions being closed, driving rapid price fluctuations.
2. Scalping: Taking advantage of short-term rapid fluctuations
3. Stop Loss Control: To avoid being hunted by stop losses, you can accurately pinpoint these stop-loss positions set at key points.
4. High Liquidity Interval Trading: High liquidity areas usually refer to places where the concentration of open interest (OI) in the market is high, especially in areas where prices are close to key liquidation clusters. The liquidation map can help you identify liquidity-dense areas, where price fluctuations are smaller and relatively stable.
5. Volatility Prediction: Predict the start and end of price fluctuations, choose the most suitable timing to enter the market, and conduct reverse trades or short-term arbitrage during small pullbacks after liquidation.

The kingfisher (翠鸟) is a real-time listening and clearing map calculation algorithm, and only this company in the crypto circle has achieved this. The algorithm is very complex and the computational load is significant.
Through the distribution of open interest (OI) for each cryptocurrency, the concentration of positions in various leverage ranges, and the distance between the mark price and the liquidation price.
Then, through reverse calculation: if the price triggers a certain range, how much position will be liquidated.
This means that the data is accurate and real-time, the distribution is dynamically updated, and what you see is the real unliquidated group, rather than the expected liquidation price inferred from historical liquidation events through algorithms.