A well-known crypto trader under the pseudonym Tyler Durden, whose X audience exceeds 200,000 followers, shared working prompts for neural networks. According to him, these commands significantly simplify the trading process and help generate profits. Let's break down six key prompts that everyone serious about the market should adopt.
Risk/Reward
This prompt forces the neural network to analyze a specific trade through the lens of the potential loss-to-profit ratio. The output provides the trader with a suggested entry point, stop-loss level, and target profit level. This approach helps assess in advance whether the expected return justifies the risk taken and avoids trades with an unfavorable ratio.
"Apply the risk/reward framework to [my trading setup]. Calculate the optimal entry point, stop-loss level, and target levels."
Macro Overview
This prompt shifts the focus from a specific asset's chart to the broader economic picture. The neural network assesses how key macro factors—interest rates, inflation, and dollar strength—affect the price. This is especially useful when market movement is driven not by technical signals but by central bank decisions and overall economic sentiment.
"Use macro analysis to evaluate [the asset]. Assess how interest rates, inflation, and dollar strength influence the price direction."
Liquidity Map
This prompt is aimed at identifying zones where liquidity is concentrated: clusters of stop orders from retail traders and large institutional orders. The idea is that price often gravitates toward levels with significant volume. Understanding these zones helps predict where the market might move in search of liquidity and avoid triggering one's own stop-loss.
"Create a liquidity map for [the asset]. Identify where clusters of stops and institutional orders are most likely concentrated."
Correlation Matrix
This prompt analyzes how closely related the assets in a portfolio are. If several positions move in sync, the portfolio only appears diversified but actually carries concentrated risk: in a market reversal, they all decline simultaneously. The neural network helps uncover such hidden connections and assess real, rather than apparent, diversification.
"Use correlation analysis on [my portfolio]. Identify hidden risk concentration between assets."
On-Chain Signals
This prompt uses blockchain data—public transaction history and wallet behavior. The neural network looks for signs of accumulation, where large holders increase positions, or distribution, where they offload assets. Such patterns sometimes precede price movements and serve as an additional signal for technical analysis.
"Apply on-chain analysis to [Bitcoin/crypto asset]. Identify accumulation or distribution patterns based on wallet behavior."
Portfolio Stress Test
This 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 assess the maximum possible loss in advance and understand which assets make the portfolio most vulnerable.
"Use stress testing to evaluate [my portfolio]. Model drawdown scenarios and identify the weakest positions."
It's important to remember: working through neural networks does not guarantee profit. AI can make mistakes. It is crucial to double-check everything and make decisions independently, considering all possible risks.
Expert opinion: Using AI for trading is a powerful tool, but not a panacea. These prompts do help structure analysis and save time, but they do not eliminate the need for critical thinking and a deep understanding of the market. Always verify the neural network's conclusions with your own analysis.