Short selling strategy for counterfeit coins: how to use Prompt to write a bot that monitors abnormal signalsRecently, there have been many opportunities for knockoff and short selling, so I used AI to write surveillance and caught VOXEL last night. This article will explain the strategy logic and how to write Prompt to create a monitoring robot The current cryptocurrency market is experiencing heightened risk aversion due to various macro tariff policy uncertainties, resulting in insufficient liquidity of risk assets. Market makers holding a large number of counterfeit coins are facing difficulties: it is difficult to sell chips in the spot market, where can liquidity be found? The answer is the perpetual contract market! This provides us with an opportunity to dance with Zhuang. 1、 Strategic logic deduction How do market makers exit the perpetual contract market? The following is a step-by-step reasoning: 1. Banker's dilemma: Holding a large number of spot chips but insufficient market liquidity, selling directly will lead to a sharp drop in prices. 2. Perpetual contract solution: Short sellers are forced to buy spot or contracts during stop loss or liquidation, providing liquidity to the market maker. 3. Attracting bears: Market makers raise spot prices (affecting marker prices), inducing retail investors to be bearish and short on perpetual contracts. 4. Negative rate dividend: The increase in short positions leads to contract prices lower than spot prices, resulting in negative fund rates. Market makers hold long positions to earn rates and price differentials. 5. Exit strategy: Push the price to the resistance level or liquidation zone, forcing the bears to close their positions and buy. The market maker takes the opportunity to exit, and may even go short in reverse. The core of this strategy is to utilize the "buying" behavior of bears to create liquidity for the market makers. The core of this strategy is to utilize the "buying" behavior of bears to create liquidity for the market makers. 2、 Core monitoring indicators The changes in indicators that we can see throughout the entire process are: Extreme negative rate (high spot control by market makers) ->Abnormal increase in OI (establishment of long positions by market makers) ->Continuously breaking through resistance levels (obtaining more long liquidity to exit) ->Decrease in Long/Short Ratio (retail investors being stopped or liquidated) ->Decrease in OI, rate returns to normal level To capture the gap signal, we need to monitor the following key data: 1. Extreme negative Funding Rate: A negative value that is too large (such as<-0.1%) indicates that the market maker has a high degree of control over the spot market, and there is excessive participation of retail bears, which may lead to the market maker placing long positions. 2. Increase in open interest (OI): The rapid rise in OI suggests that the market makers are building a large number of positions to accept short chips from retail investors. 3. Breaking through resistance level: Price breaking through key points may trigger short liquidation. 4. Indicators return to normal: After clearing short positions, the long short ratio increases, OI falls, rates return to normal, and short selling is nearing its end. Among them, abnormal changes in funding rates and open interest (OI) are the pre indicators for capturing signals! This is the data we need to focus on monitoring! 3、 AI Prompt Core Can't you see through manual monitoring? Let's use AI and Python code to create an automated tool that captures abnormal signals in real-time and pushes alerts through Telegram Bot. The following are the implementation steps: 1. Data snapshot acquisition We need to obtain key data for perpetual contract USDT trading pairs from the Binance exchange API, including: -Mark_price (mark price) -Index price -Basis (basis) -Basic_percent (basis percentage) -Last_funding_rate (latest funding rate) -OI (Position) -Long_sthort_account_ratio (account long short ratio) -Top_trader_account_1s_ratio (long short ratio of large accounts) -Top_trader_position_1s_ratio (long short ratio of large holdings) -Taker_buy_Sll_ratio (active buying to selling ratio) (Note: If AI always fails to obtain data, search for relevant data on the official website and paste the specific API calling method to AI. API documentation link:) https://developers. (binance.com)/docs/derivatives） 2. Run and save data at regular intervals -Run the program every 5 minutes to obtain data for all USDT perpetual contract trading pairs. -Save the data to a data/{symbol}. csv file for future analysis. 3. Abnormal alarm logic Set trigger conditions, customizable: -When the absolute value of the funding rate is greater than 0.1% (i.e. last_funding_rate<-0.001 or>0.001), and -The average OI of the last 3 times/the average OI of the last 10 times is greater than 2 (short-term surge in OI), Push alerts through Telegram Bot to alert you of potential short selling signals. By using the above Prompt, you can have a robot that monitors short selling opportunities. After receiving the signal, pay attention to combining technical analysis to set take profit and stop loss. This opportunity always exists, quickly deploy your robot! AI Web3 BTC