The altcoin short squeeze strategy utilizes AI to develop automated robotic programs that monitor abnormal movement signals.

Recently, opportunities for short squeezes in altcoins have frequently appeared. I successfully captured the $VOXEL market using an AI-written monitoring program. This article will analyze the strategy logic and prompt writing techniques, teaching you step by step how to create your own monitoring bot.

Currently, the cryptocurrency market is showing a risk-averse trend influenced by macro policies, with the liquidity of risk assets continuously shrinking. Holders of large amounts of altcoins are facing liquidity dilemmas: the selling pressure in the spot market is heavy, how to achieve chip turnover? The perpetual contract market is becoming a new battlefield for liquidity creation by large holders!

1. Short Squeeze Strategy Operation Mechanism#

How do large holders achieve chip turnover through perpetual contracts? The complete logical deduction is as follows:

1. Dilemma of Large Holders#

Huge spot positions
Direct selling triggers price collapse
Insufficient market depth makes it difficult to offload

2. Breaking the Dilemma with Perpetual Contracts#

Utilize forced buying during short stop-loss/liquidation
Create liquidity outlets through the contract market

3. Short Inducement Strategy#

Raise spot prices to influence the mark price
Attract retail investors to establish short positions

4. Rate Arbitrage#

Short positions push up negative funding rates
Large holders profit from holding long positions

5. Perfect Exit#

Push up to key resistance/liquidation zones
Short positions closing provide liquidity
Large holders complete chip turnover
Can reverse to short for a second harvest

The essence of this strategy is to utilize the forced liquidation mechanism of the contract market to turn shorts into liquidity providers.

2. Core Monitoring Indicator System#

A complete short squeeze market presents the following data characteristics:
Extreme negative funding rate → OI abnormal growth → Breakthrough resistance levels → Long-short ratio decline → Indicators return to normal

Specific monitoring dimensions are as follows:

1. Funding Rate Anomalies#

Negative value breaks the -0.1% threshold
Indicates high control by large holders
Signals excessive concentration of retail short positions

2. Surge in Open Interest (OI)#

OI short-term increase exceeds 100%
Large holders build positions by receiving short chips
3-period moving average/10-period moving average > 2

3. Price Breakthrough Behavior#

Breakthrough of key resistance zones
Triggers forced liquidation of shorts
Forms a liquidity release window

4. Indicators Return to Normal#

OI begins to decline
Funding rates approach normal values
Long-short ratio rebounds
Indicates the market is nearing its end

Changes in funding rates and open interest are the core indicators for early warning!

3. AI Monitoring Bot Setup Guide#

Achieve automated monitoring through Python + Telegram Bot, key implementation steps:

1. Data Collection Module#

Call the Binance perpetual contract API to obtain:

Mark price (mark_price)
Index price (index_price)
Basis data (basis)
Funding rate (last_funding_rate)
Open interest (oi)
Long-short account ratio (long_short_account_ratio)
Top trader position ratio (top_trader_position_ls_ratio)
Taker buy-sell ratio (taker_buy_sell_ratio)

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

2. Data Storage Plan#

5-minute level data scraping
Store by trading pair to data/{symbol}.csv
Historical data for trend analysis

3. Intelligent Alert System#

Set up composite trigger conditions:

Absolute value of funding rate > 0.1%
3-period OI average/10-period OI average > 2
Breakthrough of the upper Bollinger Band (20,2)
Trigger Telegram push when conditions are met

Once deployed, the bot will capture short squeeze signals in real-time. It is recommended to set dynamic take-profit and stop-loss in conjunction with technical analysis to seize certain opportunities amid market fluctuations!

Original @AI Soros Kote

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