Shanzhai Coin Short Squeeze Operation: Method for Building Anomaly Signal Monitoring Robot Using AI

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

The current cryptocurrency market is exhibiting 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 limited liquidity channels. The perpetual contract market is becoming a new battleground for these holders to cash out, which also creates opportunities for keen traders to follow the big players.

I. Short Squeeze Strategy Mechanism#

Decoding the cash-out path for big players in perpetual contracts:

1. The Dilemma of Big Players#

Huge spot holdings
Direct selling triggers 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 up the negative funding rate
Big players' long positions continuously incur funding fees
Spread profits combined with funding fee profits

5. Perfect Exit#

Price pushed to key resistance/liquidation zones
Forced liquidation of shorts provides buying pressure
Big players 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 complete short squeeze indicators:
Extreme negative funding rate → Abnormal growth in OI → Breakthrough resistance level → 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 threshold
Verification indicator for spot control
Early signal for big players' positioning

2. Surge in Open Interest (OI)#

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

3. Price Breakthrough Behavior#

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

4. Indicator Normalization#

OI retracts from high levels
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 Solutions#

Building an automated monitoring system with three major modules:

1. Data Collection Layer#

Obtain 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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