AI Writing Strategy for Monitoring Abnormal Signals in Short Selling of Altcoins

Recently, opportunities for short squeezes in altcoins have been frequent. I developed a monitoring tool using AI and successfully captured $VOXEL. This article will explain the strategy logic and how to write a prompt to create a monitoring bot.

The current cryptocurrency market is affected by macro policy uncertainties, leading to increased risk aversion and a lack of liquidity in risk assets. Large holders of altcoins are facing difficulties: it is hard to offload their positions in the spot market, where will the liquidity come from? The perpetual contract market provides the answer, creating opportunities for us to collaborate with these large holders.

I. Strategy Logic Derivation#

How do large holders exit through the perpetual contract market? Here is a step-by-step reasoning:

1. The Dilemma of Large Holders#

They hold a large amount of spot positions, but the market lacks liquidity; direct selling would trigger a price crash.

2. Solution via Perpetual Contracts#

Short sellers are forced to buy spot or contracts when they stop-loss or get liquidated, providing liquidity to large holders.

3. Attracting Short Sellers#

Large holders raise spot prices (affecting the mark price), inducing retail investors to short and take short positions on perpetual contracts.

4. Negative Funding Rate Bonus#

An increase in short sellers leads to contract prices being lower than spot prices, causing the funding rate to turn negative, allowing large holders to profit from the rate and price difference.

5. Exit Strategy#

Push the price to resistance levels or liquidation zones, forcing short sellers to close their positions and buy, allowing large holders to exit, and even reverse to short.
The core of this strategy is to utilize the "buying" behavior of short sellers to create liquidity for large holders.

The essence of this strategy is to leverage the "buying" behavior of short sellers to create liquidity for large holders.

II. Core Monitoring Indicators#

Observable changes in indicators throughout the process include:
Extreme negative funding rate (high control of spot by large holders) -> Abnormal increase in OI (large holders establishing long positions) -> Continuous breakthroughs of resistance levels (securing more long liquidity to 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 high control of spot by large holders, with excessive retail short participation, suggesting that large holders may be positioning long.

2. Surge in Open Interest (OI)#

A rapid increase in OI suggests that large holders are accumulating positions by accepting retail short positions.

3. Breaking Resistance Levels#

Prices breaking key levels may trigger short liquidations.

4. Indicators Returning to Normal#

After short liquidations, the long-short ratio rises, OI falls back, and the funding rate normalizes, indicating the end of the short squeeze.
Among these, abnormal changes in funding rates and open interest (OI) are leading indicators for capturing signals! They need to be closely monitored.

III. Core AI Prompt#

Is manual monitoring inefficient? Use AI and Python code to create an automated tool that captures abnormal signals in real-time and pushes alerts via Telegram Bot. The implementation steps are as follows:

1. Data Snapshot Acquisition#

Obtain key data for the USDT perpetual contract 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 acquisition fails, refer to the official API documentation: 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 OI of the last 3 instances / the average OI of the last 10 instances > 2 (indicating a short-term surge in OI), push alerts via Telegram Bot to notify 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 continue to exist, so deploy your bot as soon as possible!

Original @AI Soros Kote

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AI Writing Strategy for Monitoring Abnormal Signals in Short Selling of Altcoins