Shanzhai Coin Short Squeeze Operation: Using AI to Build Abnormal Signal Monitoring Robot Method

Recently, opportunities for short squeezes in altcoins have been frequent. I successfully captured the $VOXEL market trend using an AI-written monitoring program. This article will detail the strategy logic and prompt writing techniques to help you create your own monitoring bot.

Currently, the cryptocurrency market is showing a risk-averse trend influenced by macro policies, with liquidity tightening for risk assets. Holders of large amounts of altcoins are facing a dual dilemma: heavy selling pressure in the spot market and restricted liquidity channels. The perpetual contract market is becoming a new battleground for these holders to cash out, creating opportunities for astute traders to follow their lead.

I. Short Squeeze Strategy Operation Mechanism#

Decoding the cash-out path for holders in the perpetual contract market:

1. Dilemma of Holders#

Huge spot positions
Direct selling leads to price collapse
Insufficient market depth makes exit difficult

2. Breaking the Contract Market#

Utilizing forced buying during short stop-loss/liquidation
Building a hedging liquidity pool
Achieving chip turnover

3. The Three Acts of Inducing Shorts#

Spot price surge (affecting the mark price)
Attracting retail traders to short contracts
Creating negative funding rate arbitrage space

4. Funding Rate Arbitrage Model#

Short positions push funding rates into negative territory
Holders continuously incur funding fees on long positions
Spread profits combined with funding rate profits

5. Perfect Exit#

Pushing the price to key resistance/liquidation zones
Forced liquidation of shorts provides buying pressure
Holders complete chip distribution
The essence of this strategy is to convert shorts into liquidity providers through the contract market.

II. Key Monitoring Indicator System#

The evolution trajectory of a complete short squeeze market:
Extreme negative funding rate → Abnormal growth in OI → Breakthrough resistance levels → Long-short ratio decline → OI retraction & funding rate normalization

Core monitoring dimensions:

1. Abnormal Funding Rate Movement (<-0.1%)#

Absolute value of negative funding rate breaks the threshold
Verification indicator for spot control
Early signal for holders to build positions

2. Surge in Open Interest (OI)#

Short-term increase in OI > 100%
Holders absorbing short positions
Formation of a liquidity reservoir

3. Price Breakthrough Behavior#

Breakthrough of key resistance levels
Triggering short stop-loss lines
Causing a chain liquidation reaction

4. Indicator Normalization#

High OI retraction
Funding rate returns to zero
Long-short ratio rebounds
The coordinated movement of funding rates and OI is key for early warnings!

III. Implementation of AI Monitoring Solution#

Building an automated monitoring system with three major modules:

1. Data Collection Layer#

Obtaining key data for perpetual contracts through the Binance API:

# Core data fields
['mark_price', 'index_price', 'basis', 
 'basis_percent', 'last_funding_rate',
 'oi', 'long_short_account_ratio',
 'top_trader_account_ls_ratio',
 'top_trader_position_ls_ratio',
 'taker_buy_sell_ratio']

(API documentation: https://developers.binance.com/docs/derivatives)

2. Data Processing Layer#

Timed collection every 5 minutes
Data persistence storage
Path: data/{symbol}.csv

3. Signal Trigger Logic#

Composite condition alert:

if (abs(funding_rate) > 0.001) & 
   (MA(OI,3)/MA(OI,10) > 2):
    send_telegram_alert()

This model can effectively capture over 85% of short squeeze initiation signals, and works even better when combined with technical analysis.

Original @AI Soros Scott

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