Recently, many opportunities for short squeezes of altcoins have emerged in the market, so I developed a monitoring system with the help of AI and successfully captured the market trend of $VOXEL last night. This article will elaborate on the strategy logic and guide how to write a prompt to build a monitoring bot.
Currently, the cryptocurrency market is experiencing heightened risk aversion due to the uncertainty of macro tariff policies, leading to insufficient liquidity in risk assets. Traders holding large amounts of altcoins face challenges: it is difficult to offload their positions in the spot market, where will the liquidity demand shift? The answer lies in the perpetual contract market! This provides us with an opportunity to collaborate with traders.
I. Strategy Logic Derivation#
How do traders exit through the perpetual contract market? Here is the step-by-step reasoning process:
1. Trader's Dilemma#
Holding a large amount of spot positions, but the market lacks liquidity; direct selling would trigger a price crash.
2. Perpetual Contract Solution#
Short sellers are forced to buy spot or contracts when they stop-loss or get liquidated, thus providing liquidity to traders.
3. Attracting Short Sellers#
Traders raise the spot price (affecting the mark price), inducing retail investors to go short and establish short positions on perpetual contracts.
4. Negative Funding Rate Bonus#
An increase in short sellers leads to contract prices falling below spot prices, causing the funding rate to turn negative, allowing traders holding long positions to earn funding and price difference profits.
5. Exit Strategy#
Push the price to resistance levels or liquidation zones, forcing short sellers to close their positions by buying, allowing traders to exit, and even potentially shorting back.
The core of this strategy lies in leveraging the "buying" behavior of short sellers to create liquidity for traders.
The core of this strategy lies in leveraging the "buying" behavior of short sellers to create liquidity for traders.
II. Core Monitoring Indicators#
Observable changes in indicators throughout the process include:
Extreme negative funding rate (reflecting high control of spot positions by traders) -> Abnormal increase in OI (indicating traders establishing long positions) -> Continuous breakthrough of resistance levels (to obtain more long liquidity for exit) -> Long/Short Ratio decreases (retail investors being stopped out or liquidated) -> OI decreases, funding rate returns to normal levels.
To capture short squeeze signals, the following key data must be monitored:
1. Extreme Negative Funding Rate#
A large negative value (e.g., <-0.1%) indicates that traders have high control over spot positions, and retail short sellers are overly involved, suggesting that traders may be positioning for long.
2. Surge in Open Interest (OI)#
A rapid increase in OI suggests that traders are absorbing a large amount of retail short positions.
3. Breaking Resistance Levels#
Prices breaking key points may trigger short liquidations.
4. Indicators Returning to Normal#
After short liquidations, the long-short ratio rises, OI falls back, and the funding rate returns to normal, indicating that the short squeeze is nearing its end.
Among these, abnormal changes in the funding rate and open interest (OI) are leading indicators for capturing signals and should be closely monitored!
III. AI Prompt Core#
Is manual monitoring unable to cover all situations? Let’s use AI and Python code to build an automated tool that captures abnormal signals in real-time and pushes alerts via Telegram Bot. The steps to achieve this are as follows:
1. Data Snapshot Acquisition#
Obtain key data for perpetual contract USDT trading pairs from the Binance exchange API, including:
- mark_price (mark price)
- index_price (index price)
- basis (basis)
- basis_percent (basis percentage)
- last_funding_rate (latest funding rate)
- oi (open interest)
- long_short_account_ratio (account long-short ratio)
- top_trader_account_ls_ratio (large trader account long-short ratio)
- top_trader_position_ls_ratio (large trader position long-short ratio)
- taker_buy_sell_ratio (taker buy-sell ratio)
(Note: If AI fails to acquire data, you can refer to the official website for relevant data and paste the specific API call method to AI. API documentation link: https://developers.binance.com/docs/derivatives)
2. Scheduled Execution and Data Saving#
- Run the program every 5 minutes to obtain data for all USDT perpetual contract trading pairs.
- Save the data to data/{symbol}.csv files for subsequent analysis.
3. Abnormal Alert Logic#
Set custom trigger conditions:
When the absolute value of the funding rate > 0.1% (i.e., last_funding_rate < -0.001 or > 0.001), and the average of the last 3 OI / average of the last 10 OI > 2 (indicating a short-term surge in OI), push alerts via Telegram Bot to notify of potential short squeeze signals.
With the above prompt, you can create a bot to monitor short squeeze opportunities. After obtaining signals, combine them with technical analysis to set take-profit and stop-loss levels. Such opportunities persist, so it is advisable to deploy your bot as soon as possible.
Original @AI Soros Kote
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