Popular crypto trader under the alias Tyler Durden, whose X audience exceeds 200,000 followers, shared a set of six prompts for neural networks that he actively uses in his trading. These queries cover key aspects of market analysis—from risk management to macroeconomics. Let's break down each one.
Risk/Reward
The first prompt forces the AI to break down a specific trade through the lens of the potential loss-to-profit ratio. The trader gets clear guidelines: entry point, stop-loss level to minimize losses, and target profit-taking level. This approach allows for an advance assessment of whether the expected return justifies the risk taken, filtering out trades with unfavorable ratios.
Macro Overview
This prompt shifts focus from a specific asset's chart to the overall economic picture. The neural network evaluates how key macro factors—interest rates, inflation, and dollar strength—affect the price. This is extremely useful when market movement is driven not by technical signals but by central bank decisions and overall economic sentiment.
Liquidity Map
The prompt is aimed at identifying zones where liquidity is concentrated—clusters of retail traders' stop orders and large institutional orders. The idea is that price often gravitates toward high-volume levels. Understanding these zones helps predict where the market might move in search of liquidity and avoid triggering one's own stop-loss.
Correlation Matrix
This prompt analyzes how closely assets in a portfolio are linked. If several positions move in sync, the portfolio only appears diversified but actually carries concentrated risk: in a market reversal, they all drop simultaneously. The neural network helps uncover such hidden connections and assess real, rather than imaginary, diversification.
On-Chain Signals
This query uses blockchain data—public transaction history and wallet behavior. The neural network looks for signs of accumulation, when large holders increase positions, or distribution, when they offload assets. Such patterns sometimes precede price movements and serve as an additional signal for technical analysis.
Portfolio Stress Test
The last prompt tests the portfolio's resilience to adverse scenarios. The neural network models potential drawdowns—for example, a sharp market decline—and shows which positions would suffer the most. This helps pre-assess the maximum possible loss and understand which assets make the portfolio most vulnerable.
Expert opinion: Using such prompts is a smart step toward systematizing trading. However, it's important to remember that AI can make mistakes, and all decisions should be double-checked independently, considering all possible risks. A neural network is a tool, not a replacement for analytical thinking.