6 Neural Network Prompts from a Top Trader: How AI Helps Make Money on the Crypto Market
A well-known crypto trader with an audience of over 200,000 followers on X, operating under the pseudonym Tyler Durden, shared a set of six prompts for neural networks that, according to him, significantly enhance his trading efficiency. These commands are not a magic pill but tools for deep analysis, which I will break down from a professional perspective.
Risk/Reward: The Foundation of Any Trade
The first prompt forces the AI to break down a specific trade into its basic components: entry point, stop-loss level, and target profit zone. The neural network calculates the ratio of potential loss to potential gain. This allows filtering out trades with an unfavorable risk profile before they are even opened.
Macro Overview: A View Beyond the Chart
The second prompt shifts the focus from technical analysis to fundamental macroeconomic factors. The AI assesses how key interest rates, inflation, and the strength of the US dollar affect the price of the selected asset. This approach is especially valuable during periods when the market moves not based on technical signals but under pressure from central bank decisions.
Liquidity Map: Where the Whales Hide
The third prompt aims to find zones of liquidity concentration — stop orders from retail traders and large institutional orders. The idea is that price often "gravitates" toward levels with high volumes. Understanding these zones helps anticipate market movements and avoid prematurely triggering one's own stops.
Correlation Matrix: The Illusion of Diversification
The fourth prompt analyzes how closely the assets in a portfolio are linked. If several positions move in sync, the portfolio only appears diversified but actually carries concentrated risk. The neural network identifies these hidden connections, revealing real rather than imaginary diversification.
On-Chain Signals: Eyes on the Blockchain
The fifth prompt uses public blockchain data — transaction history and wallet behavior. The AI looks for accumulation patterns (when large holders increase their positions) or distribution patterns (when they offload assets). Such patterns often precede price movements and serve as a powerful complement to technical analysis.
Portfolio Stress Test: "Black Swan" Scenarios
The sixth prompt tests the portfolio's resilience to adverse scenarios — for example, a sharp market crash. The neural network models drawdowns and shows which positions would suffer the most. This allows for an advance assessment of the maximum possible loss and identification of the weakest links in the portfolio.
My Comment as an Analyst: These prompts are an excellent demonstration of how AI can automate routine yet critically important tasks for a trader. However, it is important to remember that neural networks can make mistakes and generate false signals. They should be used as a powerful auxiliary tool, but the final decision should always remain with the human, considering all risks. Blind trust in AI is a direct path to losing your deposit.